2. Senior Projects 2022
Design and Development of Virtual Reality Engineering Laboratory for Remote Education
Project ID = SDP222301
Supervisor: Dr. Osama Halabi
Ahmed Ammar, Mohamed Al-Yazidi, Abdul Aziz Al Hams
The COVID-19 pandemic has highlighted the importance of online learning in the educational system. However, this form of learning lacks the hands-on experience that is crucial for practical subjects. To address this issue, this project opens the door to a new technique for remote education that is Virtual Reality (VR), a technology that has gained significant attention as a tool to improve the educational process through engaging users in an immersive environment where they will have an experience almost identical to attending real (physical) classrooms/laboratories. This project utilizes the waterfall methodology which is a linear project management approach characterized by a sequential process, where progress flows steadily downwards like a waterfall (hence the name). The aim of this project is to use VR technology to create a virtual reality laboratory (VRL) for distance learning. The VRL is a virtual replica of a university laboratory, where students can learn and practice experiments from anywhere in the world. Additionally, the VRL allows students to participate in simulations and group learning exercises with their classmates. Overall, the VRL provides distance learning students with a unique and interactive experience that helps them better understand complex ideas and theories through experiential learning. Through experiments conducted on a number of different student groups, which test their learning ability in both the real and virtual environments, and by evaluating each environment’s (virtual/physical) learning effectiveness on the students, this project proves that virtual learning is equally as efficient as traditional physical learning and could in some cases be even more effective.
Internship Application
Project ID = SDP222302
Supervisor: Dr. Mohammad Saleh
Nawaf Al-Sowadi, Abdulaziz Al-Kubaisi, Sultan Alemadi
In today's rapidly evolving technological landscape, we have transcended numerous boundaries, allowing machines and algorithms to perform a vast array of tasks and jobs with little to no human intervention. These advancements offer numerous benefits, including enhanced efficiency, precision, and productivity while alleviating unnecessary burdens. In this context, we have identified a pressing need for a comprehensive system to streamline and manage all aspects of the internship program at Qatar university, ensuring seamless communication among all parties involved. Our project is dedicated to creating an innovative and user-friendly system that addresses the challenges faced during the internship process, improving the overall experience for examiners, mentors, trainees, employers, and focal points. By developing cutting-edge software, we aim to provide course coordinators with a highly accessible platform for obtaining essential information and significantly enhancing communication. Moreover, this system will automate many tedious tasks, increasing efficiency and convenience. The Key achievements of our project include a request management function between coordinators and employers, the ability for trainees to view offers, distinct user profiles for each user type, grading capabilities, live chatting, and much more. These novel features set our design apart, making it unique and impactful for all parties involved. For trainees, this streamlined approach provides ample opportunities to showcase their skills and potential to prospective employers. By cultivating an environment that fosters personal and professional growth, our project ultimately aims to enrich the internship experience for all.
EDUSHARE, a Learning web application for young children
Project ID = SDP222303
Supervisor: Mr. Zeyad Ali
Marwan Hashish, Bader Salameh, Mohamed Abdelmoety
Nowadays millions of children do not have access to learning and let alone to go to school, due to various reasons, including poverty, pandemics, displacement as a result of wars which resulted in a huge refugee crisis that is on the rise around the world, according to UNHCR there were about 3.5 million school-age refugees who had 0 days of school in 2016, and the number is expected to rise with current Russian invasion on Ukraine [1]. Edushare is a humanitarian web application project that aims to educate people who have been left behind by war and the CORONA pandemic and give them the opportunity to attend school digitally, as our web application is a platform that offers free fundamental courses that cover basic elementary skills that are taught by instructors who are volunteering to support the cause, the courses offered are conducted as recorded live sessions. We hope to start working together with humanitarian organizations in Qatar to identify the locations of the students who are in need and to identify any potential logistical assessments of such places and their readiness to use our services. The importance of this project lies in the fact that it addresses the future of children and young people. Research has shown that the likelihood of a young person returning to education decreases significantly the longer they are absent from school. Therefore, it is crucial that we address this issue and work towards improving the opportunities and outcomes for this group.
Crowd Control using Drones: Crowd Counting Approach
Project ID = SDP222304
Supervisor: Prof. Sumaya Al-Maadeed, Co-supervisor: Dr. Omar Elharrous
Ahmad Al-Kubaisi, Jassim Al-Kaabi, Mohammed Al-Marri
Crowd control is a growing concern in many public spaces in the State of Qatar. To better monitor and manage the situation, this project proposes a new method of crowd counting using drones or unmanned aerial vehicles (UAVs) equipped with crowd-counting hardware (Raspberry Pi 4 equipped with camera). The focus of this project is on detecting and counting the number of people in a given area using a machine learning algorithm called SCAR (Spatial/Channelwise Attention Regression Networks). This new approach to crowd control can help authorities more effectively manage and plan for large gatherings, while also reducing incidents of overcrowding and ensuring public safety.
Resale Platform For University Students
Project ID = SDP222305
Supervisor: Prof. Cagatay Catal
Skander Charni, Syed Zubair, Mohammed Omar
The high living and tuition costs in Qatar can make it challenging for students to manage their budgets and make informed purchasing decisions. To address this issue, we propose the development of a mobile application that provides an e-commerce platform for students on campus to buy and sell goods, offer services, and make requests. This application will be available on both Android and iOS devices, which are commonly used by students in universities. In addition to helping students save money by buying and selling second-hand items, the application also promotes sustainability by encouraging the reuse and recycling of items. By using the application, students can reduce their environmental impact and save resources while also potentially creating a small business to earn extra income. Overall, the proposed mobile application provides a convenient and accessible platform for students in Qatar to buy and sell goods and services, while also promoting sustainability and financial literacy.
Degree Pilot
Project ID = SDP222306
Supervisor: Prof. Qutaibah Malluhi
Ahmed Abdelhamid, Muhammed Abdushakkoor, Hani Jafer
Our senior project tackles the challenges surrounding course registration and study planning by providing an innovative solution that empowers students with efficient tools and valuable resources. It addresses the prevalent problem faced by students during course registration in universities. The existing registration systems often lack adequate planning tools, leading students to resort to manual methods such as using spreadsheets to plan their courses. This process is time-consuming, error-prone, and fails to offer comprehensive guidance. Additionally, students encounter difficulties in identifying courses available in specific semesters, potentially causing delays in graduation if not managed appropriately. To overcome these challenges, our project introduces a user-friendly solution that enables students to create study plans and semester schedules effortlessly. The system provides a simple interface, allowing students to customize their study plans by intuitively moving courses around through a drag-and-drop feature. Crucially, the system actively alerts students when their modifications may have adverse consequences, such as not meeting prerequisite requirements or causing delays in their graduation timeline. Furthermore, our solution allows students to create and manage multiple study plans, offering flexibility in exploring different academic pathways. Students can designate one plan as their main study plan, which serves as a foundation for semester scheduling. By utilizing the courses outlined in their study plan, the system generates optimal combinations of course sections without any scheduling conflicts while taking into account any user preferences. This streamlined scheduling process significantly reduces the time and effort required during the registration period, enhancing the overall efficiency of course selection for students. In addition to the study planning and scheduling features, our solution incorporates a comprehensive course and instructor review system. Students can provide valuable feedback and insights about the courses they have taken and the instructors they have studied under. This review data not only benefits students in making informed decisions but also forms the foundation for future enhancements, such as utilizing machine learning algorithms to provide personalized section recommendations to students. Through the development and implementation of our solution, we have achieved significant milestones. Our system effectively addresses the challenges faced by students in course registration and study planning, empowering them with an intuitive interface and intelligent warnings to make informed decisions. By streamlining the scheduling process and integrating course and instructor reviews, we believe our system will enhance the efficiency and effectiveness of the overall university experience for students. In conclusion, our senior project presents a comprehensive solution to the challenges associated with course registration and study planning. With an emphasis on user-friendly interfaces, our solution empowers students to navigate their academic journeys effectively, save time during registration, and make informed decisions for a successful and timely graduation.
Biometric Student Attendance System
Project ID = SDP222307
Supervisor: Prof. Khaled Shaban
Abrar Hossain, Mohammed Albadr
Tracking attendance of university students is an important process in order to ensure better grades and compliance with university rules. However, many universities like Qatar University rely on traditional check in methods which are found to be time consuming and prone to unauthorized check-ins. Our project is about developing an attendance system which uses biometric data like facial features, fingerprint and voice for checking in attendance. This ensures that no unauthorized student checks in, since one can only use their biometric data which cannot be shared. This, however, should be done keeping in mind privacy issues as well as technical drawbacks of certain biometric data form. Usage of biometric data significantly decreases the chance of false check ins, which is why we propose this as a solution to the currently used attendance method in Qatar University. Although there are many similar products in the market, our project provides a system which is more integrated towards Qatar University and it addresses unauthorized checking in problems found in said university. Our solution can positively impact the performance of students of Universities .
QBills: A Common Billing Application
Project ID = SDP222308
Supervisor: Dr. Khaled Khan
Mohamed Ghoul, Adel Hasan, Saoud Al-Khelaifi
With the increasing number of companies and organizations in Qatar adopting online payment platforms for their customers, it has become increasingly inefficient for people to pay their bills individually using different payment platforms. People still must navigate multiple online platforms or physical branches to pay their bills, which can take time, effort and require using several login credentials, which expose them to data breaches and identity theft. Moreover, people can quickly lose track of their bills and due dates because they use different platforms that need separate types of reminders. This can lead to late penalties or service interruptions and harm credit scores. Furthermore, the current process can become challenging for people to obtain a comprehensive view of their bill payments and expenses from multiple billing organizations, which introduces another level of difficulty in budgeting or managing finances. To address these issues, we have developed a centralized payment platform called QBills for managing multiple bills from different service providers. QBills takes the form factor of a mobile application and features a user-friendly interface that is easy to navigate, making it simple for users to pay their bills quickly and easily. A key feature of QBills is the ability to pay their bills for different services, in addition to allowing the user to track and manage their bills. QBills will also generate digital payment receipts and enable the user to generate expense reports for any time range of their choice. This allows the user to better manage their finances. QBills will also provide valuable features such as notifications, reminders, and alerts to help users avoid late payments and penalties. This project aims to simplify the bill payment process for users, saving them time, effort and improving their overall experience. By providing an efficient way to pay bills, users will have peace of mind knowing their bills are being taken care of. The app will provide its users with a comprehensive overview of their bills, aiding them in making better short and long-term financial decisions.
Virtual Reality Training for Improved Public Speaking Skills
Project ID = SDP222309
Supervisor: Dr. Osama Halabi
Ghazi Eladawi, Karim Zayed, Omar Amin
The fear of public speaking is a prevalent and often incapacitating anxiety that poses challenges for individuals, particularly students, when it comes to effectively delivering presentations in academic environments. To mitigate this concern, we have successfully implemented a virtual reality (VR) training system specifically designed for presentation skills development. This VR simulation faithfully reproduces real-life presentation scenarios and incorporates a responsive virtual audience that reacts to the presentation in real-time. By employing biometric measurements, such as heart rate, along with comprehensive analysis of eye movement and hand gestures, we are able to evaluate user performance and response during the presentation. Our hypothesis has been confirmed through meticulous testing conducted on a representative sample of users, wherein we recorded heart rate, eye tracking scores, and hand movement scores. These evaluations revealed notable improvements in scores and a reduction in heart rate after three training sessions. Users who engaged in this VR simulation training demonstrated enhanced confidence, diminished stress levels, and tangible advancements in their public speaking abilities. By providing a secure and controlled environment, particularly for students, we have effectively facilitated the practice and cultivation of proficient presentation skills.
Wasselni – Share Car application
Project ID = SDP222310
Supervisor: Prof. Saeed Salem
Abdulaziz Al-Sadi, Mohammed Al-Hussain, Ahmed Al-Obahi
Nowadays, Traffic congestion is a major problem that continues to worsen, and there are numerous factors contributing to it. At the same time, the cost of using public transportation and delivery services has become expensive. We created this application that is based on people sharing their cars with others to go to a specific destination chosen by the driver. The project is a mobile application called “Wasselni” that offers a solution for sharing a car with others for a trip to the same destination which will help in traffic congestion. The application’s main purpose is to connect drivers who want to share their car with passengers who want to go to the same desired destination. The application features route-tracking, location sharing, real-time notifications to help users find the most suitable trip with its simple and intuitive interface. The application is built using a combination of technologies such as flutter and firebase to insure a seamless user experience. We believe Wasselni can significantly impact and simplify the life of its users.
QinternshipU
Project ID = SDP222311
Supervisor: Mr. Mohammed Mohammed
Mohammed Al-Mohannadi, Mohamed Abdelkarim, Abdulla Ahmed
This abstract provides a concise overview of our project, highlighting its objectives, key achievements, and important conclusions. The project focuses on streamlining the internship process by transitioning from traditional paperwork to a digital information system. The aim is to enhance organizational efficiency, accuracy, and security while facilitating communication between students and organizations. Our comprehensive internship program offers students the opportunity to apply for internships at any organization, while simultaneously allowing organizations to post internship offers. The system also features a tracking and evaluation component, enabling coordinators to monitor intern progress throughout the program and provide timely feedback and support. Evaluations from both interns and host organizations contribute to ongoing program improvement, ensuring its alignment with the needs of all stakeholders. This project demonstrates the successful implementation of a digital internship management system, showcasing its potential to revolutionize the internship experience for students and organizations alike. The final report encompasses the culmination of our project, taking into account the progress made since the interim report. Relevant sections from the interim report have been revised and updated to reflect the changes implemented during the subsequent phase. The abstract has been enhanced to provide a comprehensive summary, emphasizing the project's key achievements and essential conclusions. Additionally, the final report adheres to the prescribed structure, incorporating necessary sections such as an introduction, methodology, results, discussion, and conclusion. The content of the report has been meticulously reviewed to ensure coherence and compliance with the project guidelines and grading rubrics. Throughout the document, the present and past tenses have been employed to accurately depict completed project tasks, avoiding future tense usage. The Table of Contents, List of Figures, and List of Tables have been diligently updated to facilitate easy navigation and reference. To ensure the highest quality of the final report, valuable feedback from our supervisor has been incorporated, addressing any concerns or issues raised during the review process. It is important to note that while this report template serves as a guide, modifications have been made to align with the nature of our specific project, in consultation with our supervisor. Lastly, we express our commitment to continuous improvement by acknowledging the novel aspects of our design. Our project's uniqueness lies in its successful implementation of a digital internship management system, revolutionizing the way internships are organized and executed. The impacts of our engineered solution extend to enhanced efficiency, accuracy, and security in internship processes, as well as improved communication and options for both interns and host organizations. This final report signifies the culmination of our project, encompassing the full scope of our accomplishments, insights, and recommendations. Through meticulous planning, rigorous execution, and continuous collaboration, we have achieved a successful outcome that sets the stage for future advancements in the field of internship management.
MARAFEQNA: Facilities Management App
Project ID = SDP222312
Supervisor: Dr. Abdelkarim Erradi
Mahmoud Talkhan, Ezeldin Ahmed, Omar Alkashef
Qatar University provides a lot of facilities and services for its students. However, most of the students don’t know about them, and others don’t know how they can reach them. Thus, we intend to collect all these services in just one place, which will make it easier for all the students to easily know about them and be easily reachable. This project aims to build an augmented web application for Qatar University students. This project will solve the most important issue, which is why a lot of students don’t know about these facilities. It will gather all these facilities & services and put them in one place in an interactive way, which will attract the students to reach & use these services easily. Moreover, the students will be able to book any kind of facility they need most simply. The importance of these facilities is not about just having fun, the same as the gym, pool, and sports fields, it is also about studying, as they can use the study rooms in the library for studying their classes & finishing their projects.
Q-Pick: The Smart Shopping Assistant
Project ID = SDP222313
Supervisor: Dr. Abdulaziz Al-Ali
Ahmad Abounahia, Mohamed Mohamed, Amir Adalbi
Shopping is an essential part of everyone’s day-to-day life, whether it’s grocery shopping or any other type of shopping. However, in today’s fast-paced world, people often struggle to find the time to complete their shopping needs efficiently. While shopping, people always have difficulties trying to navigate and find items they are looking for in the store, especially if it is their first-time shopping there. Q-Pick utilizes BLE beacons to offer an innovative solution that makes the shopping process much easier and faster. Q-Pick is a mobile application that helps shoppers navigate within the store through utilizing BLE beacons and indoor map. The map displays the optimal route to guide the shoppers through the shortest path to all of their list items. Furthermore, the application includes more features such as creating shared shopping lists that can be collaboratively edited by multiple users, adding items to the list by simply taking a picture of them, and locating items on shelves by providing the row number where the item is located on the shelf.
Brailliance: Braille Educational Platform
Project ID = SDP222314
Supervisor: Prof. Khaled Shaban, Co-supervisor: Abdel Razek Aly
Khaled Omar, Ibrahim Shahid Ullah, Mahin Ullah Mahin Ahsan Ullah
Throughout the Covid-19 pandemic, online learning has taken a spotlight both to highlight its importance in such difficult circumstances in the education sectors all around the world and its short-comings in delivering the same quality of education when compared to face-to-face. For some students it was a simple switch from the physical in person attendance to online attendance but for many, this was a troublesome experience. Visually impaired students have had a very difficult time to acclimate with the online education as it is commonly a tiresome experience for them to navigate the complexities of various websites, especially young primary school students who have not had any formal in-person braille learning yet. Our solution to this problem is to create an educational platform for visually impaired students which is interactive with a physical device which will translate the texts on the screen of the computer into braille characters on that physical device. The student could feel the characters by the sensation of touch and learn what they might encounter or “read” when navigating accessible physical spaces as well as produce those symbols for others to read. This educational platform will be immensely helpful as there is a very real shortage of braille educators in the world. Students and their parents must often move between cities simply to get access to an educator who is well versed in braille. Here we make an application that specializes in making this possible by having video chat session and connecting to a braille device which is Bonocle. The app will bring teachers and students closer and make education a lot easier for them and Braille learning will be more interesting for them as a lot of Visually Impaired People never really learn braille. We work on making the app possible by making it more accessible for the visually impaired.
Rifq: A one-stop pet care application in Qatar
Project ID = SDP222315
Supervisor: Dr. Saleh Al-Hazbi
Joza Almarri, Moza Alshahwani, Sara Al-Hajri
Pets of different kinds have accompanied humans for centuries, and as our religion teaches us to be merciful to animals and as our "Fitrah" guides us to act rightfully, we saw problems that affected animals considering today’s lifestyle, such as pet displacement, stray or injured animals, missing pets, and a lack of solutions that accommodated the need for a quick, simple, and easy way that reaches out to animal lovers and pet owners to offer many needed services in a one-stop destination. With the high number of stray animals that we notice every day, animals may get injured and mistreated. Although there are shelters here in Qatar, many do not know they exist as a solution to offer a helping hand to those animals, and some do not have the time. Another aspect of this problem is pet owners and their pets' needs, as well as the possibility of their pets going missing. Also, one major issue we are hoping to address is the lack of animal welfare culture to help those animals. Therefore, we decided to make an application that is easy to use and provides many services needed by pet owners and those who would like to act and aid one helpless soul at a time. Our application offers features like reporting missing, injured, and stray pets, as well as a dedicated section to show shelters and animal clinics in Qatar and how to reach them. Also, users can offer a pet for adoption or sell a pet. Consequently, users can adopt or buy a pet. Another important feature of our application is a shop where vendors can display their products, from animal food to toys and equipment to everything pet owners may need. Moreover, spreading awareness is a very important goal of ours, and one way to reach that goal is to have a blog in the application to educate on animal wellness and provide tips and tricks that ease taking care of a pet. The expected services from developing this application will benefit animal lovers and pet owners, as well as spread awareness about animal welfare.
LabSpace
Project ID = SDP222316
Supervisor: Dr. Mohammad Saleh
Fatima Al-Suwaidi, Fatima Al-Kuwari, Fatima Jamal
In recent years, the number of students and faculty has drastically increased in Qatar University, especially in the College of Engineering. This increase comes as an advantage as a whole; however, it comes with many challenges, especially concerning the laboratories and the equipment inside. Many lab items that are borrowed by either faculty or students end up being lost, while others who are in need for these items might face difficulties finding items when needed. This problem includes many losses, including monetary, time and emotional loss. The proposed solution to this challenge is to have an efficient application that can successfully track every item in all laboratories in the university, whether it has been borrowed or being used in an alternative lab. The new application will be able to track the person who has requested borrowing it, the date and time it has been borrowed and its whereabouts in the campus. The application’s functional requirements include the ability to request borrowing an item, booking laboratories on specific times, tracking an outbound equipment, and returned equipment. Also, each person will have a unique user ID (such as university ID) and login information. This whole project will require a precise barcode system on each of the items in the laboratory. This labeling system will make it very easy to track every item, as it will automatically and immediately reflect on the application once someone has borrowed it. Faculty can also pick and choose equipment beforehand to use them in classes, guaranteeing that all the required equipment will be available for their labs. Also, the ability for faculty and students to book a lab will be evident on the application, where no duplicate bookings can occur. The damaged item can therefore be reported by students or staff by the barcode on the item, which can reflect instantly on the application. The final advantage to this new system is the ability for admin staff to track the inventory levels of all lab equipment and the ability for them to see damaged equipment when reported on the system. This will enable the university to always keep the correct stock of items and order new equipment with accurate numbers as they will see the overall inventory levels. Also, it will help the admin staff analyze which equipment have been mostly used by faculty and students and which equipment has not been used. Admin staff can also create new items (for new equipment coming in), view item details such as suppliers and cost per item and finally, edit and archive the items.
Nadulk: Chalet Booking App in Qatar
Project ID = SDP222317
Supervisor: Dr. Saleh Al-Hazbi
Hajer Alyafei, Noora Al-Marri, Amna Mohamed
Individuals look for entertainment in life to help alleviate life's stresses and difficulties, and chalets have become popular gathering places in Qatar due to cultural support and the fact that they are often less expensive than booking a hotel. However, booking chalets has become increasingly difficult as there is no central platform for promotion and booking as those present in other gulf countries. Customers have to ask family and friends for recommendations, and owners have to use social media for promotion and WhatsApp for booking, leading to difficulties managing communication with customers. To address this issue, a proposed solution called the Nadulk Application has been created. This application will make the process of booking a chalet easier for both customers and owners, allowing owners to manage chalet listings and customers to view photos and descriptions to book a chalet. The application is designed to solve customers and owners of chalets problems and facilitates the booking and managing chalets process using the mobile app.
Q Parking: An online application for people in Qatar to rent their parking spots
Project ID = SDP222318
Supervisor: Dr. Moutaz Saleh
Noora Al-Marri, Maha Al-Thani, Hanan Qasem
Due to the major events Qatar is holding nowadays and the enormous amount of people attending these events, the number of car drivers has increased, which led to the need for more parking slots. Tourists living in Gulf countries are travelling to Qatar by cars, and many visitors are renting cars in the country, which is causing traffic on the roads and parking areas. Therefore, we thought of having a mobile application that allows people in Qatar to rent their free lands as parking to gain money while also decreasing crowding. On the other hand, car drivers will have the opportunity to reserve their parking slot before arriving at their desired location and will be able to choose their preferred parking slot. To develop this mobile application, we have used Kotlin language in android studio and Firebase database as the storage. This project was divided into two parts, the first part was designing the screens, the second part was adding the functionalities to the screens. After completing this project, we gave our families, friends, and colleagues the opportunity to try the services provided and give us their feedback. Hence, to reserve a parking space as a customer they were able to use a map to search for the place they were heading to and look at all the parking areas around it. Conveniently, each parking spot had its own set cost, availability slots displayed, and reviews listed from previous tenants. Moreover, Q Parking gives the opportunity for private companies to take advantage of their unused parking lot by renting it after their working hours in order to get some money. We hope Q Parking will reduce the traffic congestion on roads, decrease harmful emissions from vehicles and provide a better method for finding, reserving, and paying for parking to make ease life and save more time.
WEvents: A Mobile Application for Events Planning and Organizing
Project ID = SDP222319
Supervisor: Dr. Saleh Al-Hazbi
Fatima Qassim, Anwar Al Hakawati, Shaikha Al-Asiry
Life is full of joyful moments that are worth celebrating and creating memories that last a lifetime in individuals' hearts. By organizing events, individuals share these memories with others as opportunities to communicate and share news and unforgettable experiences. In some communities, organizing significant events is a chance to gain reputation and status. Above all, organizing an event is not easy; what is supposed to be a happy and enjoyable time could turn into a stressful experience because organizing an event requires thinking and keeping in consideration different aspects, including the number of guests, venue, food, and drink. Moreover, the organizer has to search for good and trusted vendors to supply their needs without exceeding the budget limit. However, some people tend to avoid the daunting task and hire a professional planner. Each planner has a unique style and finding a planner that can meet one’s expectations is a challenging task. Some planners use different platforms to display their work and advertise their services. Nonetheless, some of these planners are not trustworthy as they pass off other people's work as their own. This project aims to provide a solution in the form of a mobile application “WEvents”, that could assist people in organizing major events and finding appropriate event supplies. For meticulous people, it is an opportunity to view and select event related items provided by different suppliers with their descriptions and price; the app will help them organize an event from scratch without exceeding the budget while recommending budget-friendly items and supplies depending on their event type. Planners can upload their contact details on WEvents, while clients can easily choose between planners and the available options. WEvents combines all types of supplies in one platform where users can easily scroll through different supplies categories. Moreover, Wevent supports local businesses; vendors and event planners will profit by being reachable to targeted audiences, thereby expanding their businesses. In this application, our goals have been accomplished by providing user friendly application that modified and enhanced traditional event planning process. Users are now able to easily and effortlessly search, filter, and organize their supplies. Also, for people who want to hire event planners they can easily find and communicate trusted companies or personal planners, we significantly improved efficiency. In addition, it is now a valuable opportunity for vendors to advertise their products and services to targeted groups of customers. Overall, our project has transformed traditional event planning into a fun, easy, enjoyable experience for everyone.
Maritime Cyber-Attacks Simulation
Project ID = SDP222320
Supervisor: Dr. Noora Fetais
Sarah Al-Qershi, Shumokh Saleh, Amina Al-Mukhani
Technology has changed all aspects of our lives, and almost all sectors incubated the use of technology in some way to advance operations by making them more efficient and effective. However, introducing of new technologies often raises some new security concerns, which are usually not handled in the early days of adopting new tech. One of the sectors that is actively being adapted to the risks introduced by new technologies is the maritime sector in response to the growing number of cyber-attacks and the damages incurred on human life, wildlife, and property. Therefore, having a system capable of simulating scenarios and visualizing risks of compromised sub-systems, with detailed visualization of its consequences, and the suggested counter measurements to be taken by the captain and sailing crew at each stage of the cyber-attack. That system has scalability in mind so that all possible maritime cyber-attack scenarios can be included in the future. This will be crucial to accelerate the process of adopting technologies in the maritime sector since it allows new threats to be addressed as soon as possible, crew members to be well trained to handle new threats, and decision makers to allocate budget and take critical decisions without the need to have deep technical knowledge of the new tech. Moreover, VR or MR headsets can be incorporated to improve the immersion and the overall user experience once the basic building blocks of the system are implemented.
Emergency evacuation simulation using artificial intelligence
Project ID = SDP222321
Supervisor: Dr. Osama Halabi
Razan Malluhi, Meriem Boussaa, Marwa Malluhi
The safety of all individuals should be a top priority. Therefore, the safety of humans should be ensured in all buildings, including schools, workplaces, malls, and stadiums. To accomplish this, we developed a simulation that models human behavior during an emergency evacuation within a building. We achieved our goal by simulating an emergency evacuation in a large building. This simulation features artificially intelligent agents that utilize NavMesh path-finding algorithm (A*). Our NavMesh intelligent agents can evacuate any building or environment they are placed in, big or small. We have also successfully developed a machine-learned agent that uses deep reinforcement learning (RL) to enable the training and development of neural networks to allow the agents to navigate and exit various small-scale environments efficiently. Both types of agents can navigate and avoid obstacles, including other agents, as they work towards their goal of exiting the building. In addition to incorporating AI, we created realistic human agents that resemble and move like real humans for a more realistic simulation experience with the use of 3D human characters and animations.
Continuous Motion Detection Tiny Machine Learning
Project ID = SDP222322
Supervisor: Mrs.Amelle Bedair
Asmaa Almarri, Alreem Keshaish, Noora Al-Kaabi
Recent developments in microprocessor architecture and algorithm design have enabled the use of advanced machine learning algorithms on small microcontrollers. This area of research is known as TinyML (Tiny Machine Learning), or embedded machine learning. TinyML is important because it allows devices to process and analyze data locally, without the need to send raw data to a remote server for processing. This can be useful in a variety of situations, such as when there is limited or no connectivity, or when data privacy is a concern. The main goal of our project is to design an intelligent embedded system to recognize continuous hand motion. The final product incorporates a data acquisition system, inference engine, and an output unit to display the recognized motion. We chose Arduino Nano 33 BLE Sense as the hardware platform, which integrates the main motion sensor; the accelerometer. As a software tool, we used the Edge Impulse framework, a platform for developing machine learning systems on edge devices. It enables easy collection of real time sensor data, digital signal processing, feature extraction, build of classifier neural network and live testing. The success of this motion recognition system could potentially create opportunities in the market as this technology can be a core to services with different benefits. For example, teachers seeking an adaptive learning solution to allow children to independently learn geometric shapes, physiotherapists looking to track arm movement exercises for their patients, or even people with some disability to communicate. This technology can be especially useful in conditions that affect body movement, such as Parkinson's disease, multiple sclerosis, or stroke. In the industrial domain, continuous motion detection can be used to identify potential issues before they become critical. For example, a machine may exhibit minor vibrations or changes in motion that, if left unchecked, could lead to more serious problems down the line. By detecting these early warning signs, maintenance can be scheduled to address the issue before it becomes more serious. We were able to design a continuous motion recognition system in 3D and 2D spaces. The inference engine demonstrated a satisfactory level of performance with more than 90% accuracy.
IPattern: Islamic-Inspired Pattern Generation Using Generative Adversarial Networks
Project ID = SDP222323
Supervisor: Dr. Moutaz Saleh
Slafa Al-Dulaimi, Alaa Abashar, Roudha Al-Rumaihi
The prevalence of Islamic patterns design and its strong influence on other societies is undoubted. However, the incorporation of technology into people's daily life resulted in a noticeable shift in their interests to acquiring instant computer-generated content. Not to mention, the nature of producing Islamic art patterns requires dedicating long hours to the craft. Subsequently, these patterns have not caught up with today’s latest technological advances, and it is feared that these patterns will potentially be overlooked and lose importance over time. In this project, we seek to close the gap between technology and Islamic patterns by using one of the most recent deep learning algorithms, Generative Adversarial Networks (GANs). Specifically, we focus on GANs that are used to generate art. To begin, we start by exploring different architectural models of GANs to assist us in choosing a base model. Then, we proceed with testing the chosen model by collecting a significant number of images, feeding these images to the network, and discussing the results obtained. During the first training attempts, we show examples of GANs failure detected by image replication and discuss how the problem was resolved. Additionally, after producing the trained network and resulting images, we apply multiple techniques to improve the variety and quality of the images, such as applying truncations. Finally, the results were analyzed using quantitative methods by producing graphs and metric scores, and qualitative methods by subjecting the results to Islamic design experts.
SWIFT: A mobile auction solution
Project ID = SDP222324
Supervisor: Prof. Qutaibah Malluhi
Sadia Sultana, Tooba Aziz, Sara Afaneh
Online auctions have gained significant popularity in recent years, becoming an essential part of the electronic marketplace. The flexibility they offer, compared to fixed-price purchases, has been a key driver of their growth. With the convenience of using smartphones, buyers and sellers can participate in auctions from anywhere and at any time, connecting with a larger audience and fostering a competitive and diverse marketplace. Online auctions contribute to sustainability by enabling the sale of second-hand goods. In Qatar, unique car plate numbers are highly valued for personalization purposes, often commanding a premium price. Through online auctions, individuals can connect with buyers who appreciate these distinctive identifiers, promoting reuse and recycling. This fosters individuality and personal expression within the automotive community while leveraging the convenience and broad reach of online platforms. It creates a dynamic marketplace for sought-after items, including car plate numbers and other unique goods. To enhance the auction experience and provide a more inclusive platform, we introduce SWIFT, a user-friendly mobile application designed to offer a secure and innovative auction platform in Qatar. SWIFT creates new opportunities for buyers and sellers to connect and engage with each other. Users can auction a wide range of items, not limited to rare ones, from anywhere in the world. This global accessibility enables individuals to access and purchase products that may not be readily available locally. SWIFT distinguishes itself with its simple and intuitive interface, streamlining the auction process and making it easily accessible to a broader audience in Qatar. By prioritizing user-friendliness and removing entry barriers, SWIFT aims to foster a vibrant online auction community, enabling individuals to buy and sell various items effortlessly. Whether you are a passionate buyer or looking to sell unique products, SWIFT provides a convenient and user-friendly platform to participate in online auctions and explore a diverse marketplace.
Pythra’a: A 2D game for supporting pre-college students learning the Python programming language
Project ID = SDP222325
Supervisor: Dr. Moutaz Saleh
Mariam Elmoghazy, Raghad Aqel, Shaikha Al-bader
Students tend to forget the importance of learning programming languages or would not be interested in learning them unless required in their career path. However, the reality is that all majors and careers will require at least some basic knowledge in programming sooner or later; therefore, learning how to code has become essential. Additionally, computer programming courses are a crucial aspect of STEM education that comes with many challenges. Many students struggle to master programming fundamentals, which results in discouragement and disinterest in learning. Using gamification in programming courses has been recognized as a potential technique to increase student engagement and positively impact learning. Therefore, we proposed a web portal game that aims to help pre-college students learn the python programming language and prevent those challenges from occurring. The game is designed and structured to give pre-college students an enriching experience to learn programming on their educational journey while also generating a deep understanding of the main programming principles using diverse problems. A reward system and a players’ scoreboard are developed to immerse students in the game, increasing their motivation and competition among their peers. Using gamification to teach programming enhances the interest of pre-college students and optimizes their learning experience.
Eat Healthy: Recommended Recipes from Your Own Kitchen
Project ID = SDP222326
Supervisor: Dr. Tamer Elsayed
Aldana Al-Mousawi, Maymona Abul Bashar, Deema AlNaimi, Hissa Al-Misned
Recently, the priority of health and wellness has been increasing among people from various age groups and backgrounds, especially after the significant growth in diseases and epidemics. According to CDC, Obesity is a common, serious, and costly disease [3]. Consequently, the increased rate of obesity among children and adults is the main cause of the increase in multiple cardiovascular diseases as well as several types of cancers, which results in serious problems and high costs for individuals and countries. The State of Qatar is one of the top-ranking countries in terms of obesity rate, and that caused the government to focus more on solutions for this issue. The most important priority that the country’s 2030 vision supports is human development and empowerment, which calls for healthy individuals that can think and support the development of their society in multiple fields of profession. Eat Healthy application provides users with several healthy recipes that can be filtered according to desired ingredients and diet types. In addition, the application includes a feature that allows the creation of a kitchen group for people sharing the same kitchen, to help in preparing food by knowing the available ingredients in their kitchen and recommending recipes based on the available ingredients. In this project, we developed a healthy lifestyle application that focuses on the aspect of healthy eating to help in improving individuals’ daily eating habits and perhaps enhance their health. Potentially, this will assist in reducing the risk of diseases and cancers caused by obesity and negative eating habits. The application helps users track their calories and daily water intake as well as calculating their body mass Index (BMI). The application impacts individuals from various backgrounds and cultures as it provides international recipes, which makes the application accessible across multiple regions especially people living in Qatar and across users from different age groups. This is achieved through developing an application that has a user-friendly interface that is simple and easy to use. Moreover, the project used multiple coding techniques to help in performing calculations accurately on the back end of the application. Similar ways of coding and algorithms of chatting applications have also been used to create kitchen groups. Also, the application provides sorting and filtering options based on user preferences and favorites, as well as recommending recipes based on the user behavior using the Jaccard similarity matrix and filtering algorithms.
Noxa Control An AI-Enabled Browser Extension Tool for Harmful Content Management
Project ID = SDP222327
Supervisor: Prof. Saeed Salem
Rahaf Al-Athhearhe, Zain Manna, Khulood Hassan
With the rapid advancement of the digital world, where almost every aspect of our lives has shifted to the online realm, it is crucial to address the potential risks and harm associated with online-content consumption. One of the major concerns is the exposure of children to disturbing and harmful material, which can have significant psychological and mental consequences. In response to this issue, our senior project aims to design a comprehensive tool that enables guardians to protect themselves and their children from harmful online content by effectively monitoring their activities on browsers and social-media platforms. Our project's core components include an Artificial Intelligence (AI) model for content detection, a feature-rich Google Chrome extension, and a dynamic website. To explain, the AI model will detect inappropriate content while the user is browsing. The extension, based on the recommendation of the AI model, will control what content is to be hidden or shown, and collect data that will be used for generating reports and browsing behavior analysis. The website, which is connected to the extension, is where users can register, login, and request reports. Through the successful development of our project, we have accomplished significant milestones and reached meaningful conclusions. The AI model we utilized from Hugging Face Company demonstrates promising accuracy in detecting harmful online content, which has the potential to contribute to efficient and reliable protection of children. The feature-rich Google Chrome extension provides seamless integration with the AI model, offering guardians precise control over content visibility. The dynamic website facilitates user management and report generation. Our project's conclusion emphasizes the need for ongoing research and innovation in the field of child protection in the digital realm. While our accomplishments are noteworthy, we recognize that technology and online platforms are constantly evolving, necessitating continuous improvement and adaptation to address emerging challenges.
A Temporary Traffic Management System Using Unmanned Aerial Vehicles (UAV): Qatar University Congestion as a Use Case
Project ID = SDP222328
Supervisor: Dr. Ahmed Badawy
Radwan Aly, Fahad Al-Otaibi, Khalid Al-Otaibi
Congestions and traffic in cities of the world are a frustrating major issue during this era due to the growth of the world population. For instance, Doha’s population is increasing rapidly throughout the years with many nationalities from all over the world coming to Qatar, which led to the increasing number of enrollments in Qatar University. Hence, it led to high traffic congestion which is very hard to solve especially during rush hours which are around 12PM-3PM. As a group, we decided to fix this issue with the use and involvement of the Unmanned Aerial Vehicle (UAV) Systems, which are also known popularly as Drones. Our objective in this project is to design a UAV based system that can detect traffic jams and operate as temporary traffic lights. Being the eye from the sky will enable for adjusting the on and off (red and green). We are using Qatar University’s traffic jam as a use case, however, our solution can be generalized to other scenario and events to solve temporary traffic jams, where no traffic infrastructure is installed. In this report, we will address this issue by visualizing the actual problem with implementations using hardware and software based designs by using UAVs. We will acknowledge this problem with pure justifications and deep analysis as to why we need the UAV in order to solve this issue. Furthermore, we will discuss some design constraints, background and other related work regarding the same issue and also using the UAVs by previous works done. Assumptions will also be made along with our proposed solution. In the end, we will visualize our project plan to the reader by including the timeline.
Intelligent Door Lock
Project ID = SDP222330
Supervisor: Prof. Sumaya Al-Maadeed
Abdulaziz Al-Binali, Ali Al-Mohannadi, Nawaf Al-Hemaidi
Security systems have always been a necessity for many businesses and individuals to protect valuables and to control access. With covid-19, the general population’s knowledge about transmittable diseases and viruses has significantly grown and people have become more wary about touching surfaces because the covid-19 virus can be transmitted through surfaces, due to that, the need for touchless systems has grown and the market for facial recognition systems became a necessity. In our research, we were not able to find any touchless facial identification door system in the market that also sends SMS alerts to an administrator. The main goal for our project is to create a door lock with real time facial recognition capabilities that would not require its users to touch any button to start the recognition process and would simply start recognizing people as soon as they step into the door region. Whether it was dark or bright the system will be able to recognize a person using ambiance sensors to light up the door region if it was dark, sound an alert and notify an administrator through SMS in case an intruder was present at the door. With the help of artificial intelligence and advanced image processing techniques, we will be able to combine all the other supporting functionalities like controlling the electric door lock, the LCD display, controlling the ambiance lighting and alerting using a microcontroller. With all these, we will be able to create a complete system that will be able to recognize a person and either open the door or display a message to the person if not recognized in real time without the need for any interaction from the individual trying to access the door.
A cardiac auscultation device with abnormal heartbeat recognition system using deep learning
Project ID = SDP222331
Supervisor: Dr. Mohamed Al-Meer
Abdelrahman Algharabat, Faisal Al-Emadi, Fahad Al-Hammadi
Cardiovascular diseases (CVDs) refer to a group of disorders that affect the heart and blood vessels, including coronary artery disease, heart failure, and stroke. CVDs are a leading cause of death worldwide, accounting for an estimated 17.9 million deaths each year. Early diagnosis of CVDs can greatly reduce the mortality rate and the healing cost. The goal of this project is to build a light-weight device for detecting CVDs from sound recordings (i.e., phonocardiograms or PCGs). The proposed solution is based on a deep learning model known as 1-dimensional Convolutional Neural Networks (CNNs) that recognizes and classifies heart sound recordings into normal or abnormal. We have used the PhysioNet 2016 dataset to train the deep learning model and tested out model on PhysioNet 2016 and other PCGs datasets. Our system shows excellent classification results with accuracy above 95%. To allow easy use of the smart model, it has been integrated into a raspberry pi device and connected to stethoscope for real-time recording and analysis. The developed device has been tested on various cases and scenarios and shows excellent performance in recording, analyzing and recognizing normal and abnormal heart sound recordings.
Monitoring Asthma Patients via GPS Smartwatch
Project ID = SDP222332
Supervisor: Dr. Khalid Abualsaud
Tasfia Asma Anika Muslim Uddin, Lolowa Al-Sada, Duha Al-Meraghi, Reem Al-Malik
The global burden of respiratory disorders is increasing and affecting all generations. According to the World Health Organization (WHO), around four hundred million people worldwide are suffering from Asthma and Chronic obstructive pulmonary disease (COPD) alone. In our project, we want to draw attention to patients aged ten years and above. There could be many reasons why asthma cases have increased in our region, especially in Qatar. These include exposure to allergens, tobacco smoke, dust, and sandstorms. It came to our attention that tracking such patients is essential to trace their health condition and disease progression. Our goal is to improve the patient's quality of life by managing symptoms and making it easier to seek help in the event of future attacks via a smartwatch. Through this smartwatch, the patient's symptoms will be controlled by monitoring the oxygen levels in their blood, heart rate, and other meteorological parameters such as temperature, humidity, and air quality that can easily exacerbate asthma symptoms when they vary. Additionally, caregivers can view the patient's condition by the notification alert and locate the patient during the attack via a GPS tracker to get the necessary assistance. Not to mention that all real-time and collected data can be shared with the chosen caregivers. This would be achieved using the microcontroller ESP32 and sensors for tracking the parameters. A pulse oximeter and heart-rate sensor MAX30102 were employed to monitor the oxygen saturation and heart rate. In addition, a primary temperature-humidity sensor, DHT11, and an air quality sensor MQ135 will be used to detect any meteorological variations. The NEO- 6M GPS MODULE was also used for location monitoring. We attached an additional lithium-ion battery with a battery management system (BMS) to distribute the voltage to each component as needed.
Guidy: All the way to your graduation
Project ID = SDP222333
Supervisor: Dr. Khaled Khan
Moza Al-Kaabi, Ghada Al-Bader, Sara Al-Shammari
Many students face difficulties, especially newly enrolled students, in understanding, scheduling, and registering for courses every semester. Some students can’t visit the advisor’s office often due to their busy study schedules. In most cases, the free time of students does not match the time slot timeslot of the advisor. Furthermore, students want to learn more about the courses they intend to enroll in to better prepare themselves. There are currently no websites that bring together QU students and alumni to share their experiences and relevant information and papers. As a result, developing a single platform that allows students to plan directly from their study plan. They can also learn more about course materials. They can also monitor their study progress and performance, view their grades, and organize their various events and deadlines. This would significantly aid students in their university journey by allowing them to exchange knowledge and experiences in their major and other courses. Furthermore, the contributors (students and alumni) to make useful resources available to the students. Students can download and utilize those materials to improve their knowledge and achieve good performance. Moreover, the site will provide students with additional important services that will help them in their academic careers such as adding notes for each course. In addition, students can manage their time through the “To-Do’s and calendars to be more productive. This proposed app is a consolidation of many useful study-related features that a student needs in a single platform.
Automated Sustainable Hydroponic System
Project ID = SDP222334
Supervisor: Prof. Uvais Qidwai
Amna Al-Muhannadi, Aqila Khatoon, Hiba Hassan
Non-traditional farming techniques such as hydroponics are becoming more common because soil farming contribute to environmental degradation and negatively impact human health. Hydroponics is the practice of growing plants in a nutrient solution without soil. It is the preferable option when compared to soil farming since it yields more in a short time span, requires less water and can be used all year long, so seasonal crops are no longer in scarcity. However, there are some limitations that it undergoes including root rot, overwatering and sensitivity to changes in the environment it is placed in. These problems can be overcome by keeping it in a controlled system that regulates any change that can affect the hydroponic plants. Therefore, in this project a cost-effective hydroponic system that manages the plant growth parameters through the use of microcontrollers, sensors and actuators will be built. It will utilize solar energy to power the system and it will have an integrated camera that monitors the health of the plants grown in it through the use of TinyML.
Asthma Assessment Device for Pediatric Patients
Project ID = SDP222335
Supervisor: Dr. Khalid Abualsaud
Asma Al-naimi, Fatemeh Ahmadizadeh, Muneera Al-ghafran
Asthma is a common lung illness that causes breathing difficulties. It affects people of all ages and generally begins in childhood; however, it can also appear in adults for the first time. There is presently no cure, but there are basic treatments that can help keep the symptoms under control [1]. This project aims to monitor asthma attacks for pediatrics under twelve years according to the following parameters: oxygen blood level, respiratory rate, and pulse rate. The resulting measures would be compared to pre-determined health standards. The respiratory rate is calculated and deduced by analyzing the result of air pressure sensor. The pulse rate and oxygen level are obtained from an oximeter. These measurements were compared with the normal health status to decide if the child has an asthma attack or not. The result is given within two minutes. The values of the three parameters and the final status of asthma are displayed on the screen. The main advantage of the project is that it is a monitoring device that can be used in a hospital or at home where parents can constantly check the status of their children in a short period of time without having to go to the hospital.
Automatic Health Status Verification System Implemented with Face Recognition – Based Access Control
Project ID = SDP222336
Supervisor: Dr. Armstrong Nhlabatsi
Fatima Arab, Mozna Al-Hajri
During the COVID pandemic, one of the main problems that arose regarded the security and safety of the people while visiting public places such as malls, cafes, restaurants, or any place that may be crowded during both weekdays and weekends. As one of the steps towards addressing this problem, the government of the State of Qatar made it compulsory that all people visiting public places must carry with them a smartphone to show their COVID status in the Ehteraz application to security personnel. However, some people were cheating the system by taking advantage of vulnerabilities in the health status verification that made it possible to show/provide fake proof of health status with the Ehteraz application in several ways. Ehteraz application is a mobile application from the Ministry of Public Health (MOPH) to monitor the health of the public by providing the status of individuals’ health and the vaccination they received. However, some people find ways to circumvent the access control provided by Ehteraz. Two common circumvention methods were used. The first method was to use someone else's Ehteraz information. The second method was to use a screenshot of good health status to get into the wanted public places without facing the restriction of displaying their real health status via the application. To address the vulnerabilities in health status verification, in this project, we propose an application that uses facial recognition to retrieve the most-up-to-date health status of a visitor to a public place. The application uses a camera with a face recognition feature which can detect faces and link them to the health status, stored in the MOI database. Along with the automatic gate to allow or deny the person entry due to their health status. In this way, the cheating of the system can be resolved and the monitoring of the spread of the COVID-19 virus will be done efficiently. The main objective of our project is to minimize the possibility of people cheating on the current health status verification system and thus minimize the spread of the COVID-19 virus while not forcing people to show their status manually to security men, every time they visit public places.
Design of a Smart Lifebuoy Using Machine Learning
Project ID = SDP222337
Supervisor: Prof. Cagatay Catal
Reem Al-Ghanim, Ebrar Zeynep Sirin, Bakhita Al-Marri
Safety in aquatic facilities is a crucial concern worldwide, as drowning incidents continue to pose a significant threat to individuals of all ages. One of the primary responsibilities of a lifeguard is to observe and monitor individuals swimming in aquatic facilities to ensure their safety. However, lifeguards can be affected by external factors such as weather conditions, poor visibility due to crowds, and other distractions, which can impede their ability to perform their duties effectively. In addition, not all aquatic facilities have lifeguards, making it challenging to maintain safety in such locations. To address these issues, we propose a smart lifebuoy design that incorporates a machine learning algorithm called YOLO to detect and rescue drowning individuals faster than a human lifeguard. The smart lifebuoy is equipped with an ESP-32 microcontroller, two brushless DC motors, and an ESP-32 camera connected to an FTDI module for real-time image processing and classification. The smart lifebuoy moves around autonomously in a designated area, using computer vision tools to scan for unusual activities in the water. Once the YOLO algorithm detects a drowning incident, the device sends an alert to a lifeguard along with an image of the incident. The lifeguard then reviews the image and approves the rescue operation. Upon receiving approval, the smart lifebuoy quickly and efficiently moves towards the drowning individual to perform the rescue. Our design aims to provide a more cautious and sharp-eyed approach to rescuing individuals from drowning. By using YOLO, the smart lifebuoy can detect drowning incidents faster and more accurately than a human lifeguard. Moreover, the device can monitor aquatic facilities for extended periods without being affected by external factors such as weather conditions, fatigue, or other distractions, making it an efficient and effective solution for maintaining safety in aquatic facilities. In addition to its primary objective of detecting and rescuing drowning individuals, our smart lifebuoy design has other useful features. For instance, the device can record and store images of its surroundings to provide useful information to lifeguards for future reference. The device can also send real-time video feeds to the lifeguard, allowing them to monitor aquatic facilities more effectively. One of the significant advantages of our design is that it is semi-automated, with the lifeguard still involved but with an easier task. By waiting for human approval before initiating a rescue, we maintain a high level of safety and ensure that the device operates optimally. Our design provides an innovative and effective solution for ensuring safety in aquatic facilities, and we believe that it has the potential to save many lives in the future.
Configurable Wireless Sensors for Posture Correction
Project ID = SDP222338
Supervisor: Dr. Abdel Ghani Karkar
Abeer Mohiddin, Hagr Abdelhamid, Marim Abdelhamid
With technological development, many jobs became easier to perform. However, sitting for long hours may lead to the prevalence of back pain, especially for those who work at offices. For example, engineers, accountants, public service employees, teachers, and even students. In addition, due to the COVID-19 pandemic, the transition to remote work and sitting for long periods became mandatory around the world. Therefore, proposing a solution to reduce improper postures while sitting for a long time raised more attention for society. To the best of our knowledge, existing posture adjustment devices that are available in the market are not adaptable as the user does not have the ability to specify the number of sensors that can be used according to their needs. In this work, we propose a system that is capable of alerting the user when it detects an improper posture. The system enables the user to choose the required sensors and use them according to their needs. A mobile application is developed to manage and control the sensors. Additionally, the user can designate where the sensor will be mounted to the back region and used to gauge the posture. To be clearer, the user can select the appropriate back parts from the mobile application and attach the devices based on their selection. The system is usable as each device is attached to an elastic belt which ease wearing it. In addition, designing PCB of the circuit makes the device more usable as it becomes lighter. The proposed solution can be used to protect the back from such diseases that may occur due to sitting for long hours.
Robotic water taxi
Project ID = SDP222339
Supervisor: Prof. Uvais Qidwai
Malak Alrawashda, Reham Eshbair, Sara Al-Ali
Every year, a lot of boat accidents happen because of the difficult conditions such as bad weather. Furthermore, in order to reduce the human intervention as well as to avoid the human errors, we are trying to use Artificial Intelligence to manufacture a smart boat which will be used to transport people autonomously. It will be designed to make it more efficient to deal with various conditions by itself. Our team specializes in designing and manufacturing smart robots and automated systems that can read the data of the surrounding environment using sensors that have the ability to determine the path and track surrounding obstacles, such as a laser sensor, then we can analyze that data using Arduino programmed algorithms in a programming language such as C that can convert it into information that can be used by the robot's special operators such as motors which are able to implement these algorithms that depend entirely on the closed control system to be able to correct the path and process the inputs continuously. By using this smart boat, a lot of human lives can be saved from disastrous boat accidents which happen due to the bad weather conditions or human errors.
Detecting Cardiovascular Diseases Earlier with a Portable Carotid Ultrasound Device.
Project ID = SDP222340
Supervisor: Prof. Sumaya Al-Maadeed
Ala El-Bardini, Fatima Al-Mannai, Maryam Al-Kuwari
Increasing lifestyle trends, such as diabetes and high cholesterol, will lead to an increase in cardiovascular disease and stroke worldwide. These people are at a higher risk of developing cardiovascular disease than those without it. As a result of strokes, patients quality of life can be impacted and significant financial and social responsibility is borne by the health care system. During atherosclerosis, the arterial walls become thicker and less elastic. It is possible for this pathology to remain undetected for a long period of time. Blood vessel blockages caused by plaques are the primary underlying cause of strokes. Therefore, early detection of atherosclerosis is crucial. Using AI, this project will develop a system that obtains Doppler images from individual carotid arteries and transmits them wirelessly to a Raspberry Pi. This server application is designed to process deep learning models and to use them to detect carotid stenosis early. In order to display the user's condition on the touch screen, the Raspberry Pi should be able to identify and classify the arteriolar thickness as normal or abnormal. A doctor will be notified directly by email if the user is in a dangerous condition. Real-time monitoring of plaque in the common carotid arteries would be feasible in both clinical settings and at home with the proposed solution.
Robust Autonomous Driving car using Safe Deep Reinforcement Learning
Project ID = SDP222341
Supervisor: Prof. Junaid Qadir
Saeid Houti, Abdullah Hoseiny
In this project, we focus on coming up with artificial intelligence (AI)-based solutions for the autonomous control of small-scale but realistic autonomous driving (AD) cars. An AD system is an instance of embodied intelligence that is software controlled. This means that the agent must be able to sense its environment, localize its position relative to the surroundings, plan the next steps while avoiding obstacles, and correct the steering angle. Currently, deep reinforcement learning (DRL) has garnered attention from autonomous driving systems as it holds the potential to facilitate self-learning and adaptive behaviors, thereby enhancing decision-making and performance in intricate and ever-changing driving scenarios. However, just looking at the DRL raises some issues. Recent advances in DRL indicate that adversarial attacks exist and can severely degrade the performance of the AD system during the evaluation of DRL models. In view of the massive interest in applying DRL in AD systems and the key role of reinforcement learning (RL) in safe artificial intelligence, encouraging cutting-edge research in the area of adversarial research. In this project, we investigate the potential security risks associated with DRL systems in AD environments that rely on visual input for vehicle control, using the open-source Duckietown platform for robotics. We demonstrate that current DRL algorithms are inherently susceptible to attacks by designing a general state adversarial perturbation. Our strategy involves evaluating how attacks can manipulate the agent's decision-making process and using this understanding to create a corrupted environment that can lead the agent towards low-performing policies. Taking our research a step further, we have implemented state-of-the-art security techniques to strengthen the agent's resilience against the proposed adversarial attacks. We present our state perturbation method along with comprehensive empirical analysis and evaluation. Additionally, we showcase effective security techniques aimed at preventing the agent from encountering catastrophic situations.
RecoDrone - Reconnaissance 2D/3D Indoor Mapping Drone
Project ID = SDP222346
Supervisor: Dr. Abdulaziz Al-Ali
Hadieh Abdul Majeed, Mallak Abu Nimeh, Sara Al-Mahmoud
The use of unmanned aerial vehicles (UAVs) has increased dramatically over the past decade. In addition to entertainment and surveillance, drones and other UAVs are nowadays used for military operations. Aside from outdoor uses, drones' exceptional maneuverability makes them particularly valuable in enclosed spaces where it would be dangerous for soldiers to enter, especially when the ground terrain is too rough for ground vehicle deployment. The RecoDrone project proposes the idea of an indoor autonomous drone capable of mapping and data-gathering operations. The project’s aim is to allow a UAV equipped with low-cost sensors to perform autonomous exploration tasks in indoor environments while simultaneously mapping the blueprint of the space and modeling the floor terrain in three dimensions. The RecoDrone will accomplish this by performing two-dimensional simultaneous localization and mapping of rooms utilizing a low-cost Slamtec 2D RPLidar sensor installed on top of a COEX clover 4 drone. The final map will be shown through the user interface website. On the drone's underside is the CygLidar D1 dual 2D/3D laser sensor. This sensor is in charge of gathering 3D point clouds of the objects and terrain located underneath the drone during flight. Lastly, a graphical user interface web application is used to communicate between the drone and the client PC using Wi-Fi. The client can view the maps generated by the drone as well as other information about the drone's system such as the camera, battery percentage, drone coordinates and the drone status. The client will also be able to control the drone manually through the user interface whenever needed. This project provides a progressive perspective on indoor mapping using UAVs for future innovation in the military field.
Virtual Reality Wearable Telexistence System Deployment and Evaluation Environment (V-TX)
Project ID = SDP222347
Supervisor: Dr. Mohammed Al-Sada, Co-supervisor: Dr. Osama Halabi
Eman Al-Shaer, Muneera Al-Yousef, Fatima Alyafei, Bushra AlArqaban
Telexistence robotic systems are rising in prominence, especially after the covid-19 global pandemic that posed various restrictions on social gatherings and physical interactions. Wearable telexistence systems are a specific type of telexistence systems, which are worn by one person (surrogate) and controlled by another remotely (robot controller). Despite the importance of telexistence systems, designing, fabricating, testing, and deploying requires prolonged and costly processes. Therefore, this research project aims at developing the first virtual reality based wearable telexistence system. The main design objectives of our project: to provide an environment that enables engaging multiple simultaneous users within the VR environment, including surrogate, robot controller, and the experimenter, where these users can engage in direct verbal communication within the VR environment. In addition, enable users to import and use various types of telexistence robotic systems, which includes various robotic designs, wearable or stand-alone systems and various types of telexistence/telepresence control methods. Moreover, different designs provided for VR environments, such as classrooms, parks, oil-rigs or industrial locations. Finally, allow the HRI researchers and practitioners to design various usability and deployment scenarios, by selecting from various imported robotic systems, control methods and VR environments that suit their research and evaluation objectives. To the best of our knowledge, this virtual reality system is the first of its kind, as it specifically focuses on deploying and evaluating wearable telexistence systems while involving multiple users, environments, control methods and robot types. Accordingly, our system comprises three different sub-systems sides: robot controller, surrogate controller, and experimental system. They are all connected to the main PC through different ways. PC installed inside of it the Unity3D software which includes the VR environment and our (V-TX) virtual robot above the surrogate which is controlled by the robot controller itself. The experiment can test our new system with the given user interface (UI) and it's simply and clearly designed and easy to use for everyone. The hardware components we need to use to achieve our purpose in project is PC, keyboards, mouse, VR headset (HMD), hands joysticks and VR trackers. Finally, we have made a clear and basic design to our system architecture that shows how three different sub-systems components interact and work together provided with key legend.
Efficient Polar Codes Implementation to 5G
Project ID = SDP222349
Supervisor: Dr. Muhammed Azeem
Asmaa Aslam, Hala AlMaadeed, Aljohara Al Hajri
Due to noise during transmission, errors are introduced into the binary data delivered from the transmitter to the receiver. Methods of error detection are used to determine if the receiver has received valid or corrupted data. And error correction is used to rectify errors noticed during data transmission from sender to receiver. Polar codes have captured the attention of academics and industry alike over the last decade, to the point where the 3rd generation partnership project (3GPP) chose polar codes as a channel coding scheme for the 5th generation wireless networks (5G) standardization process [1]. In this project, Polar codes are implemented on 5G network. The transmitted signal in the design goes through a channel called the binary erasure channel (BEC) which has been proven to be an explicit and efficient channel to encode and decode on. With the use of successive cancellation, which is a method for decoding that enhances the error-correcting of polar codes we obtain a dependable communication channel to transmit all wanted information without the fear of errors. Moreover, the implementation will be on the user plane unlike most implementations of polar codes which are mainly on the control plane. Therefore, the main objective of this project is to validate those Polar codes have low latency, excellent error-correcting performance, and low complexity making them easier to implement on 5G transmission.
Efficient Pandemic Detection Using Wearable Sensors and Machine Learning
Project ID = SDP222350
Supervisor: Dr. Elias Yaccoub
Zaineh Abughazzah, Mahnoor Akhund, Ayah Abdel-Ghani
More than two years into the coronavirus disease 2019 (COVID-19) pandemic, we have observed that the measures put in place for societies to manage the spread of this disease are insufficient. For example, contact tracing mobile applications used to curb the spread of COVID-19 like Ehteraz need more enhancements to allow health care professionals to understand the disease better and to lessen the burden on hospitals and medical centers. After analyzing the current measures available, we have concluded that the need to develop intelligent solutions to remotely self-monitor COVID-19 symptoms to help rapidly identify and detect suspected positives has become increasingly important. Therefore, the intelligent solution we propose is introducing a Bluetooth Low Energy (BLE) wristband connected to a dedicated mobile application to intelligently draw conclusions from the data (COVID-19 symptoms) it collects. To complete our project, we have broken it down into milestones. The objective of our first task was to develop a machine-learning-based model to detect whether a case is positive or negative from cough sounds. Our goal here was to develop this model based on simple signals that can be collected by the suspected patients at home. Therefore, this task proved to be our proof-of-concept, where we investigated the applicability of our idea on COVID-19 datasets. We then augmented the techniques from this task with body temperature, heart rate, and saturation of peripheral oxygen (SpO2) measurements. In this task, we explored ways to improve COVID-19 detection results when the decision is based on a conglomerate of COVID-19 symptoms: temperature, heart rate, and SpO2 values. Then, we implemented a testbed using the wearable sensor module MAX30102 and a mobile application for detecting infection. As part of our design, we incorporated ESP32 microcontroller for BLE transmission, augmenting the functionality of the wristband. The sensor module (MAX30102) is used to detect common COVID-19 symptoms by taking measurements for temperature, heart rate, and SpO2 levels. This data is then forwarded by microcontroller via BLE to the mobile application when a BLE-enabled smartphone is in proximity. The data from coughing sounds is collected from the user’s mobile phone’s microphone through the mobile application. In brevity, the algorithm of the mobile application is designed to intelligibly draw conclusions on the status of a person’s health and inform the person in a user-friendly way using the colors (Green: for good health, Yellow: to be cautious about their health, and Red: to immediately get checked).
SurgiVision: Tele-mentoring system for open surgeries
Project ID = SDP222351
Supervisor: Prof. Amr Mohamed
Abhigyan Kishor, Ahmed Soliman, Abdallahi Mohamed Mouemel
The global clinical burden is increasing, and access to good surgical care is extremely dependent on the geographical location of the patient. Telementoring is a possible solution to these problems. Telementoring can be defined as the use of technology to transfer the expertise and knowledge of a remote surgeon (mentor) to a less skilled local surgeon (mentee) during surgery, leveraging intelligent interaction and efficient telecommunication. Open surgeries are critical because they require intrusive intervention with cutting tools to open the body wide in order to manipulate the internals of the patient, hence, very special skills are needed for surgeons who perform this type of operation. Therefore, many challenges arise in the context of telementoring, including versatility of devices for different types of surgeries, processing, and communication overheads, which need to be minimized in order to facilitate efficient interaction between surgeons. In this project, we propose a telementoring system for open surgery that uses Azure Kinect device to capture the depth map along with the RGB image of the ambient surgical site. Multiple Kinect devices are used to avoid occlusion and create a complete 3D model. The information from the Kinect is processed locally using a microcontroller that converts the captured information to a 3D model. The 3D model from each Kinect is sent to the local server that stitches them into one 3D model and sends it to the remote site. The 3D model is rendered at the remote site in an immersive virtual environment that the remote surgeon can experience through the Oculus Rift VR headset. The mentor can use the Oculus Rift controllers to move virtual surgical tools, those virtual tools and their movements are rendered as holograms, that the mentee can see through the Microsoft HoloLens, at the local site. The mentee can replicate the movements of the hologram to perform the surgery in the same way that the mentor would have. This approach allows the mentor to get a better visual understanding of the surgery, while giving the mentee a more immersive mentoring experience.
Traffic Signals Control System
Project ID = SDP222352
Supervisor: Dr. Mohamed Al-Meer
Abdelrahman Mohamed, Saad Shaat, Abdulaziz Alyafei
This project is designed to create an intelligent traffic system to regulate traffic flow for cars and pedestrians. This project aims to reduce traffic congestion and accidents at intersections through several technologies, including adding a timer on traffic lights. Thus, drivers will be notified of the time remaining until they can cross the street or stop when the traffic light changes from green to red. Also, the timer will be able to change time by increasing or decreasing traffic congestion on that road. An infrared sensor will detect traffic jams at a certain distance on the road. Moreover, the system detects if the vehicle is crossing when the traffic light is red using a laser sensor; Based on this, all traffic lights will be red, and the one which was in a green state becomes a yellow state, and at the same time, the alarm (buzzer) activated. This concept is also applied to pedestrians' traffic lights, so the buzzer is activated if pedestrians cross the road while the pedestrian traffic light is red. An alarm will notify all drivers and pedestrians that something wrong has occurred, and everyone must stop. This project was done with ESP32 (microcontroller) and compiled using Arduino IDE (C language).
IntelliCoach - Athlete Performance Tracking System
Project ID = SDP222354
Supervisor: Dr. Abdulla Al-Ali
Nirvana Aladal, Ameena Tolfat, Sara Alabdulla
Sports have expanded over time, with development not only in competition but also in research. Sport studies are inextricably linked to its inherent aspects such as physical fitness, performance, and production. In this project, information on the integration of wearable devices to enhance athletic performance tracking has been gathered from subfields of research. Although there are multiple wearable technologies available on the global market to aid in sports activities, they have various limitations. Despite Qatar being one of the most forward-looking and advanced athletic nations on the globe, wearable devices are scarce in the Qatari market. Zooming in on the impediments of the existing products, one major evident setback is the lack of a communication system embedded into the wearable. Communication is crucial in sports. Coaches guide their players to ensure that they are functioning to their full capacity, which frequently necessitates immediate communication during physical activity. Intellicoach, a low-cost, user-friendly wearable gadget designed to help coaches and athletes, will be created as part of this project. The major function of this gadget, which is designed to be worn on the chest, is to gather data on an athlete's activities and relay it to the coach, while also allowing for immediate real-time communication between the two. The device has a GPS to track the athlete's location and movement, a number of sensors working with artificial intelligence to measure heart rate and perform gait analysis, and a microphone and a speaker for real-time communication with the coach. This data is then wirelessly sent to the coach's portable through Wi-Fi. The coach may then watch an analysis of the athletes' activities while communicating with them via the handheld microphone and speaker. Due to the limitations of existing wearable sports devices, which range from high prices to a lack of necessary features, and even the fact that such devices are not available in Qatar, it is clear that Intellicoach has the potential to be adopted by the Qatari and international sports markets, as it will not only be the only wearable sports device available for an affordable price in the Qatari market, but it will also cover for the shortcomings that the existing devices have.
Secure Automated Delivery of Critical Goods with RFID-based Tracking and Authentication
Project ID = SDP222355
Supervisor: Dr. Elias Yaccoub, Co-supervisor: Dr. Mohammed Al-Meer
Hala Aburajouh, Maryam Al-Hail, Chaza Araji
The purpose of this project is to deliver goods securely and autonomously to the destination without anything being stolen or taken by mistake. Nowadays, there are a lot of robots that are so smart and do almost everything, but the problem is that none of those robots (especially the delivery robots) have a security system that protects the goods until they reach their destination. Our system, which is composed of an autonomous robot, application, RFID reader, and RFID tags is the solution for this problem. The tag will be read by the reader until it is removed from the robot. After the object is removed from the robot, the reader will determine whether the GPS location matches the location to which it should be delivered; if so, the user and administrator will receive notification that the delivery was successful, and the database will be updated. Otherwise, an alert will be sent to the user's mobile app and the reader on the robot to return the item. If the item is not returned, an alert is sent, and the order is marked as misdelivered. Later on, all misdelivered items will be handled by the administrator who will take appropriate action.
5G Traffic Management Drone
Project ID = SDP222356
Supervisor: Prof. Amr Mohamed
Ayaa Zahra, Mariam Al-Aloosi
Detection and categorization of objects are well-studied aspects in many ways. The gulf times news reports that there were 629 traffic cases overall in July 2022, representing a monthly decline of 15.7% and an annual increase of 24.3%. The majority of traffic collision cases within the same month involved injuries (92.4%), then severe injuries (4.5%), respectively. Additionally, 20 fatalities were reported, which represents 3.2% of all traffic incidents [1]. Also, the cameras that are available right now in roads do not capture all the hazard situations therefore, a solution like mobile cameras that goes around the highway to try to detect all scenes that can be unsafe is of high importance. AI-based solutions employed in autonomous driving provide strong proof of human trust in these approaches. The task at hand is to detect and identify vehicles through short videos captured by a drone camera. The purpose of this project is to create a system that can identify cars, type, estimated speed, distance between cars, identify traffic jams on the highway in a variety of conditions. The goals are to combine hardware and machine learning to create an autonomous drone and to utilize machine learning (ML) to recognize vehicles. The drone will be able to independently gather information of vehicles with specific positions.
No Child Neglectfully Left Behind - Artificial Intelligence-Based Children Car Safety System
Project ID = SDP222357
Supervisor: Prof. Junaid Qadir
Noora Al-Kunji, Hadeel Alshammari, Wadha Al Marri
This project aims to prevent child fatalities caused by leaving them alone in vehicles, particularly in places prone to inclement weather. Tragically, such situations are not rare and can occur on both school buses and private vehicles. In September 2022, a child died due to excessive heat after being left in an unventilated school bus in Qatar, inspiring us to develop a solution to prevent similar tragedies. Our system comprises an embedded device and AI software that detects the presence of children in a vehicle after all doors have been closed. When the system detects the presence of a child, it sends a text message to the caregiver's phone. If no action is taken after receiving the text message, the system sounds an alarm to warn nearby individuals, facilitating a swift intervention to save the child. By implementing AI-based detection systems, we can significantly reduce the risk of child fatalities due to being left unattended in closed vehicles. Our work underscores the critical role of technology in enhancing child safety in various environments. This project demonstrates the potential of technology to address important social issues and safeguard vulnerable populations.
Smart Real-Time Accident Detection System
Project ID = SDP222358
Supervisor: Dr. Elias Yaccoub
Aisha Omar, Sara Al-Hajri, Taif Alrawashda, Reem Al-Kuwari
Traffic accidents claim the lives of many people worldwide every day. Building an automatic traffic accident detection system is an effective way to reduce traffic fatalities. A second goal is to reduce the time between an accident and the arrival of first responders. In recent years, built-in vehicle automatic accident detection has become more popular and used in many applications. However, they require maintenance and are not available in all cars besides being expensive. Every vehicle must be equipped with an automatic system that will quickly notify the emergency department following the accident. Researchers have proposed several automatic road accident detection methods. But in our project, we are going to use the pulse oximeter and heart rate sensor (MAX30102) and connect it to the mobile application to send an emergency message to ensure the driver is not injured or harmed. We will achieve that by combining the sensor measurements with readings from an accelerometer and a microphone that can detect the sound of a car crash. Additionally, a heart rate sensor will be included that will detect the level of the user's heartbeat and can be used to determine if he is injured as well as his current health condition. This data will be stored in a database, allowing us to save information about the user such as their location and state to notify the emergency team.
Ash: A Stealth Drone
Project ID = SDP222359
Supervisor: Dr. Abdulla Al-Ali
Syeda Rizvi, Fatimaelzahraa Ahmed, Noof Qassmi
Drones have become a popular tool for illegal activities such as political attacks, causing serious threats to global security. In order to address this issue, our project aims to demonstrate the limitations of current drone detection systems by constructing a stealth drone, which is called “Ash”. The current drone detection systems focus on detecting the drone based on it is Radio Frequency (RF) signature and its appearance using computer vision. The designed drone will be capable of operating in three different modes which are Wi-Fi, 915 MHz radio frequency signals, and autonomous mode using global positioning system (GPS). The project objectives include building the drone from scratch. In addition, communicating with the ground station on 915MHz frequency with a low signal power. The drone will be camouflaged to evade detection by optical sensors. In this project, we are evading the RF analyzers and the optical sensors drone detection systems. We are using LoRa technology to transmit on 915MHz using chirp spread spectrum (CSS) modulation technique, which is not commonly used by drones. This makes it difficult to be recognized by the RF analyzer as a drone communication signal. To evade detection by optical sensors, we are camouflaging the drone by adding an air balloon envelope on top of the drone's frame. This makes it appear as a flying air balloon to the detection systems, which should confuse these systems that use computer vision and artificial intelligence. To sum up, this project illustrates the importance of detecting drones accurately and the need for anti-drone systems to adapt to new technologies and tactics used by operators of unauthorized drones. By highlighting the weaknesses of current anti-drone systems, we aim to contribute to the development of more effective technologies to protect global security. This is because the current drone detection systems have some limitations such as RF detection systems does not cover the entire frequency spectrum and usually scans for 2.4 GHz up to 5 GHz.
Haptic Gloves Handball Goalkeeping Training System
Project ID = SDP222360
Supervisor: Dr. Noora Fetais
Ahmed Ibrahim, Sayer El-Hadidy, Renz Jesmar Chuateco
The growing interest in harnessing Virtual Reality (VR) and haptic feedback for sports training has led to innovative approaches in skill development and performance enhancement. In handball, there is a need for immersive and accessible training tools for a wide range of players. This Computer Engineering Senior Design Project combines a Unity-based handball simulation with DIY haptic feedback gloves to create an immersive, cost-effective, and versatile training experience tailored to the needs of goalkeepers. The primary objectives of the project included developing affordable VR gloves with haptic feedback for tactile sensations in virtual interactions, creating a convincing handball simulation in Unity with various training scenarios for diverse skill levels, bridging the gap between real and virtual worlds by immersing players in an environment where they can play and feel simultaneously, and facilitating skill development by breaking down complex motor skills into subskills for targeted practice and assessment. Our methodology involved researching and identifying suitable components and techniques for constructing cost-effective DIY haptic feedback gloves, designing, and assembling gloves incorporating selected haptic feedback components with necessary hardware and software, and developing a handball simulation in Unity, focusing on realistic physics, diverse training scenarios, and seamless compatibility with the gloves. Consulting with coaches and players ensured authenticity and relevance. We implemented a system for breaking down motor skills into subskills, allowing targeted practice and assessment in the simulation, with performance metrics and data analysis providing feedback and tracking progress. Finally, we tested and validated the VR glove and handball simulation system, refining the design based on feedback from users and experts in the sport. The project successfully yielded a custom-made, affordable VR glove with haptic feedback capabilities, providing tactile sensations and force feedback during virtual interactions. The handball simulation in Unity featured realistic physics and diverse training scenarios, immersing players in a comprehensive training experience. The system demonstrated the ability to break down complex motor skills into subskills, facilitating targeted practice and assessment. User feedback and performance data indicated a positive impact on skill development and overall training effectiveness. The outcomes of this project have significant implications for the future of handball training and sports training in general. The integration of VR and haptic feedback technology offers an accessible and engaging alternative to traditional training methods. Practicing complex motor skills in a simulated environment enables players to focus on specific aspects of their performance, potentially accelerating skill development. The immersive nature of the virtual environment can help maintain player motivation and engagement. Despite limitations in replicating the full range of real-world interactions, the promising results highlight the potential for further exploration and refinement of VR-based training systems in handball and other sports. This project successfully combined DIY haptic feedback gloves and a Unity-based handball simulation to revolutionize goalkeeping training, demonstrating the potential of this platform to improve athletes' performance and serve as a valuable training tool for handball clubs, coaches, and players across various skill levels and demographics.
Minimizing Human Mistakes in Health Care with Technology
Project ID = SDP222361
Supervisor: Dr. Mahmoud Barhamgi
Yaser Al Amour, Yazan Hajar, Sultan Al-Boinin
Human mistakes in healthcare systems can have serious consequences, such as increasing mortality and accelerating morbidity, whether it is a surgical error, a management error, or hospital infection due to poor hand hygiene and instrument sterilization. In this paper, we will discuss the development of an IoT-based system to improve hospital management and prevent infections due to hand hygiene, with a focus on nurses and doctors, and to improve hospitals’ job routines in general with minimal cost. The system’s main jobs are monitoring safety distance, recording staff cleanse state and serving as cloud information for the hospitals. The monitor part is based on ESP32, a cheap and powerful microcontroller that will help in monitoring the safe distance for the patient and alarm in the case of close distance without clearance state, and another ESP32 to record hospital items quantity and send it to the server to alarm, in case of missing or low storage items. The server can be implemented using Raspberry Pi as a communication port between other microcontrollers and other applications. For management, RFID cards will be used to identify and store the patient’s information and send it server for easy access. Also, it can store hospital staff information that can be controlled with web and mobile applications for better management. They can also enter a checklist to keep a record of all daily activity of the patient. The web application interface will also have information that is related to the patient’s state to allow them to view their current condition, time to take medication, and other general tips entered by their doctors to improve patient safety after they leave the hospital. Some changes have been made to our Senior Design 2, where some parts have been deprecated. The most important change is removing the use of ESP32-CAM and using Raspberry Pi 4 model B with attached camera. Another important change is we have not implemented a web interface application for records and patients visits. Instead, we only use a normal desktop application. Finally, some of the solutions have been removed as they’re not necessary or hard to implement. The final design consists of Hand Hygiene compliance system, medical Package stock refilling monitoring, and finally, patient records applications.
Massar - Course Schedule Planner
Project ID = SDP222363
Supervisor: Dr. Abdelkarim Erradi
Taimoor Hussain, Mohamed Ahmed, Omer Ahmed
Every semester, students at Qatar University have trouble picking the right courses while being convinced that their registration decisions are the best ones. Additionally, the information needed to make informed decisions is scattered in many systems including the department websites, Banner, and Blackboard. This can make it difficult for students to make informed decisions about their course choices and stay on track with their program study plans. Students may want to know if they are able to take a certain course in a different semester than originally planned by the program department. And if so they may wonder how it will affect their graduation time. To address these issues, we developed Massar as an interactive web application that allows students to easily access and query their program study plan and the associated course details. This enables them to better understand their degree requirements. Then they can define and update a personalized study plan and track their progress, including visualizing their completed courses and the remaining ones. This is a significant improvement compared to the current static web pages and PDF-based study plans, which do not offer these features. The interactive study planner was designed to replace these traditional methods and provide a more user-friendly, interactive, and queryable visualization of their study plan coupled with the ability to assess the impact of common registration decisions. This will yield increased students' capacity to adhere to their program study plans and graduate on time. Additionally, the proposed solution allows greater collaboration and timely feedback from other stakeholders, particularly the academic advisers and the program coordinator. This guides students to success to avoid unneeded setbacks and complete their degrees on schedule while following a study plan aligned with their career aspirations.
Qatar’s Real Estate Platform (Q-REP)
Project ID = SDP222364
Supervisor: Dr. Tamer Elsayed
Maha Almaraisi, Nashwa Al-Shamasi, Maryam Al-Eshaq
Property hunting is something that almost everyone goes through in their life. Finding the desired estate to buy or rent can take time and effort. However, technology can make this process easier. This project aims to make looking for suitable real estate in Qatar easier and more quickly accessible; it will also make it easier for agents to list estates for sale or rent and provide new features to communicate between agents and customers. This program targets more than just real estate companies. It also aims to help private clients list their properties. In addition, an application targeting Qatar's residents will be developed to help them search for an estate. This project would greatly help Qatar’s real estate business since there is no similar application.
Intelligent System Controller using GPS to clear the Fastest Path for Emergency Vehicles
Project ID = SDP222365
Supervisor: Dr. Hela Chamkhia
Ayesha Balideh, Roaa Hajar
Traffic lights are designed to regulate traffic flow and avoid accidents. Individual well-being and safety, as well as the entire functioning of society, are dependent on safe driving and traffic safety. The traffic light system has been enhanced over time to provide road users with safe roadways by enforcing regulations and norms. The current traffic light system allows emergency vehicles to pass through red traffic lights if they are transporting a critically ill patient, despite the fact that the traffic system may endanger the patient's life. The overall goal of this project is to change the current traffic system that allows ambulances to cross while there is a red light in front of them, putting the lives of the patients inside the ambulances and the cars surrounding them in danger. The project goal is to find a solution to this problem while reducing the time spent traveling to the hospital. The existing traffic light system can be further improved by implementing a control center that will select the shortest and safest route for emergency vehicles to their destination based on the current location of the emergency vehicles. The control center can use this data to make informed decisions about traffic lights along the route and adjust them in real-time to ensure the ambulance moves smoothly and safely. When an ambulance vehicle approaches an intersection, the movement should be smoother; to increase the safety of ambulance drivers and passengers. As a result, the ambulance will arrive safely, and there will be fewer car accidents caused by rushing through red lights.
Penetration Testing on SCADA System of a Maritime Vessel
Project ID = SDP222367
Supervisor: Dr. Noora Fetais
Dhabya Al-Khulaifi, Shaikha Al-Khulaifi, Amna Alyafei
Cybersecurity of maritime vessels has received minimal attention, which resulted to limited solutions for cyber-attacks prevention. Therefore, this project aims to highlight how cyber-attacks can cause damaging effects on the marine industry by raising awareness about cyber-attacks in the maritime industry. This was achieved by showing a cyber-attack, on the Supervisory Control and Data Acquisition (SCADA) system of maritime vessel, that can happen in real life. We built the virtual Industrial Control System (ICS) with a ventilation subsystem, to create a realistic system. The hardware of the project consists of many components including a Raspberry Pi, Arduino Uno, temperature sensor, and fans. The fans will be automatically switched on/off according to the data sent to the actuators by the Master Terminal Unit (MTU) through the Modbus protocol. The changes must be shown on the Human Machine Interface (HMI). During the penetration test, the data displayed on the HMI will be misleading and will fail to show the correct output of the real-time process. Our project will allow any student/trainee to safely execute a penetration test on a maritime vessel's SCADA system without causing harm to real life systems as we have done in this project.
Irregular Motorcycle Delivery Driver Behavior Detection
Project ID = SDP222370
Supervisor: Dr. Ahmed Badawy
Abdullah Khalili, Yahya Almzayyen, Marwan Al-Shayeb, Hussein Al-Abboodi
Ensuring the safety of motorcycle delivery drivers is a significant challenge, as irregular driving practices can lead to accidents and impact road users' lives. This senior design project aims to develop a comprehensive system for detecting and reporting irregular driving behaviors among motorcycle delivery drivers, such as speeding, weaving through traffic, making prohibited shortcuts, using pedestrians’ crossing roads to make a U-turn, and getting close to other vehicles. The system integrates a variety of hardware components, including a lidar sensor for detecting the distance of nearby objects, a gyroscope for measuring handlebar tilt, a C615 USB webcam for object detection, a GPS sensor for tracking latitude and longitude, a Teensy 4.1 microcontroller, Arduino UNO and a Raspberry Pi v4. The software component of the project utilizes a YOLOv7 machine-learning model to analyze the distance between the driver and objects and identify irregular driving behaviors. The YOLOv7 model effectively detects and reports these behaviors to relevant authorities or supervisors by processing sensor data and camera data, enabling appropriate corrective actions. The proposed system not only contributes to reducing accidents involving motorcycle delivery drivers but also has the potential to be adapted for other types of vehicles, further enhancing overall road safety. This comprehensive, innovative approach to monitoring and improving driver safety will significantly impact the computer engineering field and the broader logistics industry.
Computer Vision & Artificial Intelligence Application: Diagnosis & Prognosis of Diseases Causing Lower Back Pain
Project ID = SDP222371
Supervisor: Dr. Jurlind Budurushi
Ibrahim Demdoum, Talha Punjabi, Mohammed Arif
An application of Computer Vision and Artificial Intelligence techniques geared towards diagnosing potential diseases causing Lower Back Pain (LBP). LBP is a highly prevalent condition that imposes a huge economic, physical, and psychological burden upon individuals and businesses. In 2017 it was estimated that 7.5% of the global population suffer from LBP, or around 577 million people. Over and above that, approximately $134.5 billion was spent solely on treatments, individuals contributed $12.3 billion out of their own pockets for these expenditures. While there exist a considerable number of related works aiming to diagnose LBP, current research and projects focus solely on using neural network techniques, due to the substantial performance of deep learning algorithms. Furthermore, these works rely completely on medical imaging (MRI) as input to the model. That is based on the fact that MRI is prevalent in medicine as a method to diagnose pathologies related to the lumbar spine. To the best of our knowledge no model (related work) incorporates imaging findings with medical markers to train a diagnostic model. Using only medical imaging as an input to train AI models creates a ground truth limitation. Since such input relies on fallible radiologist diagnosis to train the model, the model will never surpass the radiologist’s accuracy. Even if ground truth limitation is ignored, sometimes imaging findings do not correlate with the patient’s condition, for example, the degree of disc displacement in MRI imaging shows no correlation with what patient’s subjective symptoms suggest. By introducing other relevant objective inputs to the model, such as blood work, subjective pain, or biomechanical markers/parameter, the model would surpass the radiologist’s accuracy regarding its’ diagnosis. This project introduces a system that adopts a holistic approach to LBP and its diagnosis. Thereby, both patients’ medical parameters and imaging are used for training the AI model, to yield a more accurate diagnosis. In this project we developed a computer-aided diagnosis (CAD) system, utilizing an amalgamation of a neural network classifier (CNN) and a classical machine learning classifier (KNN), as a means to diagnose LBP causes, such as bulging discs. The system takes MRI as an input for the CNN model, and patients’ medical parameters as an input for the KNN model. The system was capable of diagnosing bulges in the lower back with an accuracy of 81.81% despite database and privacy limitations. While the same system using only a CNN classifier did not surpass 70%.
Dine-able - A platform for Placing Reservations in Dine-in Restaurants
Project ID = SDP222373
Supervisor: Dr. Armstrong Nhlabatsi
Hassan Falahi, Ahmad Al-hayder, Fahad Bin Shahbal
Dine-able is a web application that allows users to easily make reservations for a table in any fine dining restaurant around the world. The web application allows diners to make a complete end-to-end booking without any human intervention, such as contacting the restaurant to ask for available tables and waiting for their reply. The application provides an option that allows diners to have their order prepared before reaching the restaurant, so they do not have to wait for a long time. The web application is designed to assist customers with disabilities by showing them if the restaurant is accessible to people with special needs. Moreover, it also shows them all the accessible features that a restaurant has in place for them. It shows them the services that the restaurants have, such as wheelchair-accessible entrances, handicap parking, disabled-friendly bathroom, and braille menus. Dine-Able is engineered in a way that enhances the dining experience for customers with varying allergies. It offers a unique feature that presents users with a customized menu based on their allergic condition. The web application also provides users with the choice of the menu for each restaurant according to their diet. This makes it easy for people on different diets to choose their meals. The application can dynamically customize the menu for vegans, vegetarians, and also people on the keto diet by only showing them dishes that suit their specific dietary preferences. In addition, Dine-able allows restaurants to increase their operational efficiency and customer satisfaction levels, which will positively affect their revenues. The web application is engineered in a way that allows restaurants to easily have control over their tables, timings, and dishes. Restaurants can also track bookings and orders easily.
“TW”: True Walk
Project ID = SDP222374
Supervisor: Dr. Mohamed Al-Meer, Co-supervisor: Dr. Muhammad Chowdhury
Hadil Aldhubiea, Lolwa Alkuwari, Muneera Alsemaih
In recent years, the world has been massively influenced by technological developments in numerous aspects, especially in the field of health and wellbeing. Remote surgeries, health examinations, surgical robotics etc. are examples of how technology has enhanced the health sector. smart shoe insole system is a new monitoring technology that is developed to monitor a person’s walking pattern and assess whether the amount of pressure that is applied on the foot while walking is normal or abnormal in real-time observation allowing users with abnormal feet conditions to be diagnosed in early stages. Such technology is especially beneficial for people with diabetes in which constant surveillance of the foot can help in positive prevention. Also, people with flat feet, a condition in which the applied pressure of the foot is not distributed evenly resulting in severe pain while walking, will benefit from having monitoring insoles. This project will discuss the design of a wearable shoe insole that can measure the pressure applied by the foot during walking. The design will be utilizing pressure sensors, circuit configurations and consideration for creating a small workable electronic device also using a low-level communication protocol to send pressure data wirelessly to a centralized device storage. It will be sent to the cloud for further processing so that it can be seen by the user on their mobile application. This project will assist in constructing an affordable and portable foot monitoring system for patients, by using Artificial Intelligence and deep learning will help in producing graphical maps that will indicate whether the pressure that is applied on the feet is normal or abnormal.
The Implementation of Blockchain on Face recognition and detection system for vehicle security and driving safety enhancement
Project ID = SDP222375
Supervisor: Dr. Devrim Unal
Alanoud Afifa, Reem AlKathiri, Alanoud Al-Hemaidi
Recently, motor vehicle theft and its attempts and the driving of unauthorized drivers have significantly increased worldwide. Accordingly, vehicle security systems should include additional precautions for vehicles. Reducing the number of vehicle theft crimes, prohibiting unlicensed and unauthorized drivers, and maintaining a safe driving environment is the purpose of our senior project. We developed an RFID tag reader lock system to limit vehicle access and a computerized programmable camera with face recognition and drowsiness detection capabilities to instantly identify and capture the driver when entering the vehicle monitor them while driving for any drowsiness behavior. The project primarily targets reducing the rate of unauthorized drivers and vehicle thefts and addressing numerous issues that most vehicle businesses and companies that own vehicles for their services or even on persistently identify and capture the driver when entering the vehicle. The proposed system allows the vehicle owner to assign authorized drivers to utilize the vehicle. In addition, we will provide a driver drowsiness detection solution to track driver behavior and evaluate these drivers accordingly. The cameras built into the vehicles will monitor the driver. Each driver's face recognition and drowsiness detection logs will be saved in a secure private Blockchain. We decided to use private Blockchain to safely store and retrieve the face recognition and drowsiness detection logs, ensuring data integrity and offering a transparent and tamper-proof record for assessing driver behavior. The admin and other authorized members are able to access the logs using a graphical user interface we have built for the user’s convenience. The web application will show each driver’s behavior to be evaluated. Moreover, the built cameras will also ensure the driver’s health and safety.
Garagat Qatar
Project ID = SDP222376
Supervisor: Dr. Mahmoud Barhamgi
Hassan Al-Ali, Ali Al-Enazi, Marawan Mohamed, Salem Rashid
Car owners in Qatar often face difficulties in accessing and requesting services from local garages due to the absence of a professional and convenient application that connects all garages in the area. In response to this issue, we propose the development of an application that allows users to access garage store pages, request services, and order spare parts with the option for home delivery for a small fee. This application will only allow government-verified stores to register, ensuring that users can trust the sellers on the application. The alternative applications currently available are either expensive or do not have verified sellers, making our application a valuable resource for car owners in Qatar. By providing an easy-to-use and trustworthy application for accessing local garages, we aim to improve the experience of car owners in Qatar when it comes to accessing and requesting services from garages. A specialized application like ours has not been introduced before in Qatar, and there are few similar applications in the region that can be used by Qatar residents, and this is what makes our application unique and sets it apart from other alternatives.
Design and Implementation of an Electro-Optical Imaging System for CubeSat with Onboard Image Processing
Project ID = SDP222378
Supervisor: Dr. Khalid Abualsaud
Hagar Elsayed, Moza Al-Kubaisi, Malha Al-Ahbabi
A CubeSat is a small satellite composed of several mandatory and payload subsystems. The purpose and goal of a CubeSat mission are determined by its payload, which is often one or two scientific instruments. Cameras can also be used as a payload, and in these cases, CubeSats often use tiny, low-resolution CCD or CMOS imaging sensors and camera modules. This project, part of Qatar University's nano satellite project (QUbeSat), aims to design and implement an electro-optical imaging system for a CubeSat with onboard image processing capabilities. The system will be used to capture images of Qatar. The system will consist of optics, an imaging sensor, a power supply, data storage, control electronics, and communication electronics. The system will be developed and tested using various tools and technologies, and the final product will be demonstrated to meet the objectives and success criteria established for the project. The proof-of-concept for the system was successfully implemented and verified, with testing results indicating compliance with a significant portion of the design constraints. This successful implementation and verification provide a strong foundation for further developing and integrating the Electro-Optical Imaging System for CubeSat with Onboard Image Processing. In addition, the project is expected to significantly contribute to the capabilities of the QUbeSat platform and positively impact future developments.
Integrated Accident Detection and Evaluation System Based on Vehicular Networks and Artificial Intelligence (IADES)
Project ID = SDP222380
Supervisor: Dr. Devrim Unal
Maryam Al-Meraikhi, Dareen Douglas, AlDanah AlAnazi
Vehicle accidents are a global concern that inflates annually, resulting in massive losses in human lives, resources, and finances. Although some accidents might be minor, others can be fatal or cause long-term disabilities. Hence, in this project, we present a hybrid system that detects, estimates, and reports vehicle accidents as quickly as possible. The project's primary objectives are saving people's lives by reducing the reporting time, increasing the response of appropriate authorities and companies, and clearing road blockage that emerged from damaged vehicles. Consequently, the system is designed to achieve the above objectives with multiple components and new emerging technologies such as Artificial intelligence. In detail, the hybrid system consists of two devices, an AI accident detection model and a vehicle device represented in a collection of sensors, and microcontrollers. Designing a hybrid system eliminates any failure occurrence to the two devices rather than using each individually. For instance, severe accidents could damage the vehicle device and increase the likelihood of uncertain and false reported information or total data loss at worst. Moreover, previous works failed to address this, alongside estimating the accident severity from the collected data the hybrid system produces. Consequently, this project will benefit future studies and innovations by developing it into an avoidance system that aligns with the Smart Cities technology concept besides reducing physical, social, and financial costs of vehicle accidents.