3. Senior Projects 2021
ICONTROL : A new way to protect your data
Project ID = S2122 01
Supervisor: Dr. Armstrong Nhlabatsi
Nasser Abdulwahab Alzouabi, Mohammed Seoud, Abdullah Alamodi
Nowadays, photos and files sent are still way too easily transferred to unwanted and malicious parties despite all such advancements. It is too familiar to hear about people's images reaching the public or unintended recipients. The challenge is that once a photo is shared, it is currently impossible for its owner to have technological control over how the image is further shared or used. To address this problem, we propose IControl. With IControl, we aim to create an application such that your files can ONLY be accessed by the people you, and only you, want and cannot reach the hands of unwanted or even malicious characters that have been and always will be there. IControl gives the owner of digital content control of those files even if he has already shared them with other parties. With IControl, the user will upload their file to our platform, choose specifications, stating the lifespan of the file, screen shielding, and recipients' emails, and can then take comfort in knowing that the file will not reach unintended recipients. We do this by using tools to encapsulate your file with our tailored-to-you code and return it to you such that you can send it to those you specified. After which, the aforementioned code will communicate with our database to ensure everything is in order and knows when to destroy the file should any of the specified rules be violated. For example, suppose the file is screenshotted without the owner's knowledge and permission. In that case, the system will block the screenshot, and the owner will be immediately notified by our system so that they can take action and possibly revoke that recipient's access.
Bayan: Towards an Effective Arabic Fatwa Search Engine
Project ID = S2122 02
Supervisor: Dr. Tamer Elsayed
Abdulrahman Al-Raimi, Faisal Abughazaleh, Saad Anis
A Fatwa (فتوى) is an answer to a religious question from a knowledgeable scholar. Back in the day, a person seeking a fatwa would go to a scholar (mufti) to request one. The mufti would then offer the fatwa if and only if he is knowledgeable and therefore eligible to provide a fatwa in that subject. Fatwas constitute a critical part of Islam because they direct the actions of the seeker according to religious texts, which are Quran and Sunnah in our case. Nowadays, with advancements in search engine technologies, people find it more effortless to seek fatwas online. Unfortunately, this raises a few important concerns. Firstly, for the Arabic language, the search engine sometimes fails to provide relevant information that fulfills the user’s query request which leads to inefficiency in finding a relevant fatwa. Additionally, general-purpose search engines do not account for certain user features specific to seeking fatwas, like checking the authenticity of a Hadith (حديث). Finally, search engines do not differentiate between authentic Islamic websites like islamweb.com and other possibly inauthentic sources like news and aggregator websites. We are addressing these problems by providing a user-friendly web application that extends Google Search’s capabilities. Our system, Bayan, uses the Google Custom Search JSON API to search for an Islamic query on a list of specific authentic websites, which could be customized by the user. After getting the results, they are re-ranked based on a fine-tuned AraBERT model. Finally, these results are then displayed to the user through a friendly web app, with the help of unique features such as Quran and Hadith annotation, which help guarantee the authenticity and the correctness of the results. We evaluated our re-ranking model using two datasets: an existing test set, SemEval, which exclusively contained fatwas, and our in-house test set, which we built to be a more suitable test for our problem domain. We were able to achieve a Macro F1 score of 85% on the SemEval test set and an NDCG@10 score of 93.90% on the Bayan in-house test set.
Sports community
Project ID = S2122 03
Supervisor: Dr. Mohammad Saleh
Elbaraa Elhawary, Mahmoud Gazalh, Mohamed Khattab
The motivation for us to create the Sports community application and plan for it is to help people keep their health and increase awareness of the importance of practicing sports. Also, we aim to generate revenue through the application for us and the stakeholder. In our project, we aim to make finding the closest training partner or teammate easier for anyone seeking to practice any sport and find the most immediate appropriate sports organizations and facilities to practice a particular sport. This app targets a vast sector of the society as we are gathering many sports services providers in one app to present and propose their services and make it easier for any person who is passionate about any sport to find a teammate who is interested in the same sport. Our app is an entrepreneurship idea that enables us to make a profit by collaborating with business owners who may find it helpful for them to subscribe to our service. It benefits us by having a commission on every reservation a user reserves with the facility owner. Our app will be developed using the most recent technologies, and we are going to provide the user with a friendly user interface that gives the best user experience. However, we may face some problems at the beginning of distributing that app among the athletes and facilities providers; we will use all the advertisement tools available to make it reach the highest number of users in the shortest time possible. The application also enhances the concept of competition by making users able to rank each other depending on their performance and how recommended is it to have a person in a team; this gives a chance to every passionate person to present their skills and has an evaluation from other users about their athletic performance, it also makes it easier for commercial clubs to find great athletes who other athletes recommend. We may also include some tutorials and advice for users about a particular sport and how to improve their performance and schedule time to practice. Our app is a great idea to increase society's awareness of the importance of sports, the role of sport in social gatherings, and the importance of technology to facilitate people’s lives.
Microlearning-Based Social Network
Project ID = S2122 04
Supervisor: Dr. Saleh Al-Hazbi
Ali Mohammadian, Hasan Alsamra, Abdulla Khedr
Ever since the pandemic of COVID-19, e-learning has been immensely growing and has become widely used by a variety of worldwide teaching institutions. When talking about e-learning in effort and time-wise approaches, it can be described in two terms, macrolearning and microlearning. Macrolearning teaches the subject in complete detail. On the other hand, microlearning teaches small-sized and information-packed lessons, which are identified as micro-lessons. The significance of microlearning lies in minimizing the educational content and focusing on the subject at hand while preserving the core concepts of the topic. In our project, we will design a social network platform that is based on microlearning educational strategies. This platform combines both the social aspects of social networks and the pedagogical aspects of microlearning. Moreover, we aim to provide like-minded users with a platform to connect with each other. Additionally, we want to maximize the number of potential users; therefore, our platform will primarily target mobile devices to achieve that goal.
PSAR: Predicting students at risk
Project ID = S2122 05
Supervisor: Prof. Khaled Shaban
Redwan Chowdhury, Mahdi Alhaddad, Yousef Qumatah
We built a system in collaboration with Machine Learning professionals at Qatar University to predict students at risk. The problem is that universities cannot know if a student will dropout or not. Therefore, we developed a system that will predict students who will be at risk of failing. We used machine learning techniques like random forest and decision trees to predict at-risk students. Both techniques provide high accuracy, stable analyzing and can solve classification as well as regression problems. We used an agile methodology to support communication in the team. We were adaptable in our plans to new changes, and testing was done while developing the system. Our developed model, random forest, gave us an accuracy of 95.4%, and decision tree accuracy was 87.3%. Moreover, we made a user-friendly website, which will be used to facilitate the functionalities of our model. Our project aim is to minimize students who will be at risk of failing, and that will increase the awareness of the university about their students.
Oral Cancer Detection Web Application using Machine Learning techniques
Project ID = S2122 06
Supervisor: professionals. Khaled Shaban
Ahmed Terchoun, Mohamed Ahmed, Md Zihan Alam
Oral cancer is a serious illness and a deadly disease that is usually accompanied with a late diagnosis and painful treatment. Oral cancer detection techniques have had noticeable progress in the last few years. In this project we introduce a web application that facilitates uploading photographic images of patients and utilizing machine learning models to diagnose oral cancer. The application is used by three types of users namely doctors, administrators, and machine learning engineers. Doctors will be able to perform the uploading of images, requesting diagnosis, and correcting this diagnosis, if needed. Administrators will have access all over the system and be able to view and edit information. Machine learning engineer’s role is to view information related to the engine model. This report describes the development of the web application in terms of related research and development work, design, implementation, and testing for oral health professionals. This web application can will be able to improve oral cancer detection by utilizing an ML model that captures an image of the patient’s mouth. A constantly retrained engine model presents the doctor with a suitable diagnosis depending on the data collected. This report aims to provide related research in this field, and an idea of the functionality of this proposed solution. An overview of the proposed solution is that when a doctor takes an image of the patients mouth, the doctor will be able to send it to the ML model and retrieve an annotated version of the image with the diagnosis.
Harassment Prevention Helping Tool Using Heat Map
Project ID = S2122 07
Supervisor: Dr. Mohammad Saleh
Hesham Zaky, Mohanad Mohamed, Yousseif Elshahawy
Harassment has been a toxic phenomenon that proved hard to drastically countermeasure due to its random and unexpected nature. Additionally, this phenomenon helped draw a faulty image of societies where many harassment events occur, regardless of the movements that are publicly against it. Creating a tool that puts the power of opposing this phenomenon in the hands of everyone, all while being effective and responsive, is what inspired us to adopt this as our senior project. Accordingly, we targeted the prevention prospect of fighting against harassment by implementing a heatmap that reflects the density of harassment in an area and additional functionalities to aid people in the case of incidents occurring. One of the aiding functionalities is the immediate help functionality, where the victim will press a button to call emergency forces like the police and ambulance to help the victim. Moreover, we provided a “view near facilities” functionality, where the user can view facilities on the map, such as hospitals and police stations. A program like ours with the same characteristics has not been made before and has not been used in the region before, and this is what makes it a unique program with an easy, simple, and robust design.
Import Management System (IMS)
Project ID = S2122 08
Supervisor: Dr. Abdelkarim Erradi
Saad Iftikhar Zubair, Bassam Saleh Nasser, Sandrik Concepcion Das
In today’s developing trade industry, software in this market area seems to be divided and appears to specialize in only one task or functionality. This forces companies to utilize multiple applications to complete its goal, which makes the overall process unnecessarily complex and expensive. This project aims to address this division in products and design an affordable solution that contains the relevant features needed for the import and export process and combines them into one product. Our solution streamlines the process by providing a user-friendly interface to create and send quote requests, receive and compare priced quotes, and manage the order of the shipment throughout the process from the perspective of an importer. By splitting our high-level architecture into user interface, app services, and external services layers and implementing them through the controller-service-repository design pattern, we created the foundation for a Flutter application that utilizes Express middleware to connect to a MongoDB database and other essential services.
iPark
Project ID = S2122 09
Supervisor: Dr. Noora Fetais
Ibrahim Buhindi, Mohammed Al-Kaabi, Saad Al-Rewaily
Traffic problems are unavoidable as the number of motor vehicles on the world's roads increases. This is mainly due to the current mechanisms that have been set in place for parking are incapable of dealing with the upsurge of cars on these highways, roads, schools, and stores. The proposed smart parking system is being introduced to address these mentioned issues. Users will have the ability to readily find and secure an empty slot at any parking structure regarded suitable to them thanks to the design and development of the smart parking system. The integration of a convenient parking system also makes vehicle entrance and exit more comfortable [1]. With a plethora of vehicle sensing devices on the industry, the decisions taken may vary because of the many requirements as well as the advantages and disadvantages. Following that, the different sensors in use in developing the smart parking systems, as well as recent study and enterprise systems on the industry, are analyzed, as well as vehicle detection being critical in the parking system. The aim of this project is to design a smart parking system with mobile application which can show the status of the parking slot and give the notification if someone else parks the car in someone else’s allocated parking slot. First solution system uses NodeMCU controller board, ultrasonic sensor and RFID transmitter and receiver for hardware. The ultrasonic sensor detects the availability of the parking spot and RFID read the unique code of the car. The data is then sent to firebase database and mobile application will display the status of the parking slot and compare the RFID number with the original RFID number which is inserted in the system while signing up for the mobile application. The final solution system uses NodeMCU controller board, ultrasonic sensor and Webcam module, Raspberry pi for local host. The ultrasonic sensor is connected to NodeMCU which detects the availability of the parking spot. If parking lot is not available, NodeMCU will send a message to NodeRED using MQTT protocol which activates the Webcam on local host pc which is connected with raspberry pi. The camera will take the picture and send it to firebase and mobile application will display the status of the parking slot and compare the vehicle plate number with the original plate number which was inserted in the mobile system while signing up for the mobile application.
Sound denoising using deep learning
Project ID = S2122 10
Supervisor: Dr. Mohamed Al-Meer
Hamza Hamad, Yazan Qawas, Abdulrahman El-Nagar
This project aims to remove any noise that might affect speech signals, using a deep-learning approach. As is known in the real world, there are various noises coming from nature that can corrupt speech signals, which significantly downgrades their quality and performance. That is where de-noising assists in generating a clean speech signal, free from any type of noise. The current speech de-noising techniques can be split into two groups: (1) conventional methods – which revolve around estimating the noise to achieve de-noising; and (2) Deep Learning-based methods – these are more recent; they use the non-linear relationship between noisy and clean signals through deep Neural networks (DNN). In our project, we used TensorFlow libraries, alongside Librosa, and some others to achieve signal de-noising through Python coding language. Later, we implemented this code on a Raspberry Pi microcomputer, with a graphical user interface to record sound mixed with noise and reproduce a clean speech signal.
System for Monitoring and Managing Electric Vehicles Charging Using IoT
Project ID = S2122 12
Supervisor: Dr. Loay Ismail
Noureldin Elshiekh, Osama Mohammed, Ahmed AL Salahi
Many countries worldwide are taking steps to reduce air pollution caused by internal combustion engine (ICE) vehicles; leading the popularity of electric vehicles (EVs) to increase. As EV popularity has increased over the last few years, more demands are expected to be placed on the charging station infrastructure to adapt to this increase. This project aims to provide a system for monitoring and managing EV charging using a few different modules. At the core of the project is the Internet of Things (IoT) technology to help connect the various parts of the project, and provide a seamless experience for the users. The project consists of different systems each with its own objective, including a way to measure the battery charge directly from an EV, sending the battery level data to a mobile application to provide user notifications, and communicating with the server at the most suitable charging station to reserve a charging time slot to charge the EV. Additionally, the charging station includes systems for safety and management to handle both the reservation requests, and the safety of the chargers at the station. The proposed design for monitoring and managing EV charging using IoT is designed to benefit EV users, and charging station owners. The system thoroughly estimates the state of charge (SoC) of the EV’s battery and notifies the user when the SoC approaches a critical value. An assistive reservation is also provided to find the most suitable charging station for the user and guide him to that station with one single click. The design is constructed using a current, voltage, and temperature sensors with a machine learning algorithm for battery estimation. Moreover, a USB camera is used for EV detection at the charging station using you only look once (YOLO) algorithm, a thermal sensor to detect any increase in the chargers' temperature using the red intensity of the images from the sensor, and a raspberry pi camera to detect the QR code of the reservation tickets using OpenCV. Finally, a mobile application is provided to assist the user in various tasks from checking his EV’s battery level to reserving a charging time slot at any available charging station to charge his EV.
AirEye: Intelligent Mobile Target Visitation of a UAV using DRL
Project ID = S2122 13
Supervisor: Prof. Amr Mahmoud Salem Mohamed
Abdelrahman Soliman, Mohamad Mohamad Ali Bahri, Mohamed Daniel Bin Mohamed Izham
From traffic monitoring to livestock tracking, and military reconnaissance to marine discovery, the unmanned aerial vehicle (UAV) is indispensable. However, its dependence on a battery for its power supply means that it has a limited flight time to visit the required locations. Consequently, the visitation needs to be completed as soon as possible to minimise the mechanical energy used by the UAV. The goal of this project is to develop a system that can perform the target visitation task in the shortest possible time. The objectives are to integrate hardware to make an autonomous drone, use machine learning (ML) to detect targets, and implement reinforcement learning (RL) to teach the drone how to visit all targets in a minimum amount of time. The significance of this project is that by combining object detection and RL, UAVs will be able to autonomously capture details of fixed targets with unknown locations, or mobile targets with an arbitrary mobility pattern, while minimising mechanical energy and time. The hardware part of the proposed solution consists of a Raspberry Pi acting as the onboard computer attached to a Parrot ANAFI drone. The onboard computer also receives high-level commands from the command and control station. On the software side, deep reinforcement learning (DRL) algorithm called Proximal Policy Optimization (PPO) is implemented to train a model in the Sphinx 3D cyber-physical environment. At the same time, the Olympe program is utilized to send commands to the simulated and real ANAFI drone and receive sensor data from them. The RL has been proven to be superior in terms of time and energy spent to execute both fixed-targets and mobile-targets visitation missions compared to random and zig-zag agents. Moreover, the work in the visual simulation has been validated in the real world in the integration testing, thus confirming that it can act as the digital twin of the physical version. The framework that has been proposed in this project is flexible enough to be extended to applications beyond target visitation. The impact of this project on the global scale is through proving that RL is a viable and effective method to train a UAV to execute a visitation mission either with fixed or mobile targets. Once the framework developed in this project is in place, companies with little knowledge of RL can easily retrain the UAV digital twin in the framework for their new missions. The simplicity will help spread the use and benefits of UAVs more widely, such as in marine discovery, wildlife preservation and homeland security. In addition, this project can lead to the creation of new jobs in target visitation and area tracking using UAVs.
QU Evergreen
Project ID = S2122 14
Supervisor: Prof. Qutaibah Malluhi
Mahmoud Abdelaziz, Omar Omar, Abdolrahman Aboulebda
Many new trends in farming have emerged because of the growing need for water and food, which has led to the development of complicated agricultural production systems. Plants can be cultivated in soilless environments like hydroponics and aeroponics. Mineral nutrient solutions are used to feed plants in hydroponic systems grown in water or a soilless media. Several research investigations have indicated that hydroponics and aeroponics may positively impact the long-term food supply. Utilizing less water, fertilizer, and space while boosting yields per unit area may provide an environmentally friendly alternative to traditional farming practices. These contemporary farming techniques have a substantial advantage over their predecessors since they conserve water and require little or no agrichemicals. This project aims to create a controlled environment for a hydroponics system that produces plants with shallow plant roots and flowing hydroponic nutrient layers to guarantee that they receive adequate water and handle temperature, humidity, pH, and light. Plants thrive in water that contains nutritious solutions, which are constantly pumped by a pump. These measurements will be uploaded to the firebase firestore and stored there, where we will create an application for the user to see the status of plants and measures at any time.
Cyber Carrier-Pigeon
Project ID = S2122 15
Supervisor: Dr. Noora Fetais
Assad Saadoun, Jamil Mohammed Al-Jaberi, Mohamad Alnass, Yousif Yousif
Despite the advances in process automation introduced by the digital age, the process of mail delivery of non-electronic information is still largely dependent on human intervention. The main objective of this project is to make mail delivery more systematic and swifter. Our plan to facilitate this is to use Unmanned Aerial Vehicles (UAVs) to deliver letters between stations. These drones will run autonomously and deliver mail. The goal is to enable users to request a drone to a specific station via a mobile application, after which the drone will arrive and the user will load the items on a box attached to the drone, and send it off to a target location, where another user will receive it. The system is designed for the secure transmission of letters, which is achieved through biometric authentication, using fingerprints.
Mahally: An Online Shopping Application to Gather Home Businesses under One Platform in Qatar
Project ID = S2122 20
Supervisor: Dr. Moutaz Saleh
Amna Aljumaily, Asmaa Khattab, Haya Al-Kuwari
With the world's accelerated growth and innovation, the home businesses market is expanding rapidly in Qatar, and therefore, it is becoming an important sector of the market in Qatar because of its ability to increase economic development and provide job opportunities in different fields. Besides, home businesses contribute greatly to the preservation of Qatari culture. However, one of the major difficulties that harmfully affect the home business market is that no platform gathers all home businesses in one place. Therefore, having a mobile application that connects the clients to all home businesses in Qatar and provides them with the essential services will facilitate the process of buying and selling and advance the home businesses market significantly. Mahally allows the owners of home businesses to add their items and offer them to the users directly through the application. Furthermore, the users of this app navigate and search over the home businesses, their items, order items to be delivered, and rate and review the home businesses. And since most of the home businesses in Qatar do not have an assigned driver to fulfill orders to clients, a feature of the application is that it will provide a delivery service across the country without overwhelming the owners and users to search for it. The drivers will use Mahally for the sole purpose of delivering the orders and updating their status for the user to track. The novel feature that distinguishes Mahally the most from other applications is that it hosts the three types of users in the same app: owners, customers, and drivers. Moreover, customers can post a question to the shop owners. The owners can answer the customers' questions, and both the questions and answers will be seen by all the users.
Saakin: A Qatari Real Estate Mobile Application
Project ID = S2122 21
Supervisor: Dr. Sayed El-Sayed
Maryam Al-Malki Maryam Arab, Dana Hassan
Real estate market in Qatar is currently bustling with a lot of activity, especially because of the upcoming World Cup 2022. Due to expensive prices, a lot of budget-conscious people spend a significant amount of time picking a house to rent. Also, there are a large number of people looking to invest in properties due to rapidly increasing demand. Many people in Qatar find it difficult and time-consuming when searching for real estate in the country, and they don't know which real estates are credible and which are unreliable, as well as people who want to visit Qatar and want to stay for a long time. So, we decided to create aneasy-to-use app for anyone who wants to rent, buy, or sell real estate. This application aims to help people inside and outside Qatar to search for suitable real estate for them, especially foreigners including students and employees, and people who are going to visit Qatar in 2022 for World Cup and want to stay for a long time. Also, to provide a greater chance of looking at more than one real estate or communicate with a real estate agent directly to help them with what they are looking for. In addition to having many features that are not found in other real estate applications. There are indeed, many applications for real estate, but not all of them are comprehensive and easy to use. Each app has a specific feature, but they have a lot of gaps. Features that are expected by creating this app, will help citizens, residents, and people who would like to visit Qatar.
Tahseen: Vaccination-Related Services Website
Project ID = S2122 22
Supervisor: Dr. Khaled Khan
Abeer Ali, Ahlam Abonada, Fatema Al‐Mansoori
The online system of private and government hospitals in Qatar has always been complicated in making appointments for vaccination, knowing important pandemic-related announcements, and getting the most up-to-date information about the patients’ vaccination records. Appointments are usually booked either by calling or directly to the hospital. Since the Covid crisis started, the pressure on the appointment system has been tremendous, and still, it is. Considering this situation, we believe that developing a one-stop-service website for booking vaccination appointments and other related services will significantly help the citizens and residents. In this project, we developed a web-based system that provides the general public w easy access to the online booking system and other vaccination-related services. These services focus on simplifying the way vaccination appointments are made. For instance, one of the significant features is managing an individual appointment and their children. Another essential feature is that individuals can download certificates of any vaccination they took simply from the website and view all vaccinations they took in their lifetime. The system also offers a self-assessment service where users can ask questions and receive answers from doctors regarding vaccinations. To understand the usefulness of this project, we conducted a survey to know to what extent the Qatari community needs a website that could provide all necessary functions for the vaccinations that individuals take throughout their lives. Most of the participants agreed that our community needs such a website to fulfill their needs in managing their vaccination-related information. After implementing the website, we also tested our website with friends and relatives, and we got good reactions regarding the performance and design. A single website only for vaccination-related services, called Tahseen website, will enhance the healthcare providers such as hospitals to make more one-stop-services for other health-related issues, not only vaccination. We hope that Tahseen will inspire others to develop a similar one-stop service to cater to their healthcare matters.
QSB: Qatar Small Businesses
Project ID = S2122 23
Supervisor: Dr. Sayed El-Sayed
Shahad Abougahl, Sharefa Saqer Al-Rumaihi, Noura Hussain AlGhadeed
The project aims at developing an application platform that will allow business people and owners to advertise their businesses and the services they offer in one place. The application will enable companies to promote their products, hence offering them an opportunity to reach a great multitude of customers. As digital marketing has taken the central role in modern advertising, the idea will enable businesses to target many people, thus increasing their Return on Investments (ROI). Further, the project will ease finding the service a customer needs by strategically classifying the business’s services based on their industry. For instance, services will be classified as teaching, hair, and beauty, depending on the company that will adopt the idea. The ease of navigation through the system due to the incorporation of the search option and the strategic grouping of the services will enable the users to save time and find what they want. Digital marketing that sells and buys goods of known trademark businesses in the country will be implemented to develop this business idea. Digital marketing is essential for commercial purposes; its relevance is based on its use in commercial products. A digital marketing system will allow obtaining an enhanced quality service and safer. Allow the business service providers to rapidly and readily manage an online order which clients can browse and use to place orders with just a little button press click at any place. Also, it will allow to update and handle the details of Business Category, Product, Order, and Shopping Cart, Delivery Address. It will keep track of all information pertaining to the Delivery Address, Order, and Shopping Cart. The project's objective is to develop an application program that will reduce the amount of manual work required to manage Business categories, Products, Orders, Shopping carts, as well as Delivery Addresses. The system works as an online ordering system that can take care of the order placed by the client and will be delivered by shipping addresses with the purchased product at any point in time. After placing orders, the client will respond to the service provider to know the status of the order on-time delivery time that the client deal with the associated service provider. The application will provide a convenient order option where the client will order a product with the service provider of interest. The order option will help reduce the time that when the customer tries to reach the service provider through phone calls, it happens to get busy with the customer problem, shopper, and long queue. Our system will promote products for clients instead of the usage of the traditional papers such as magazines, newspaper whose been decreased latest years. The major hindrance to using these traditional means of advertisement is the additional cost associated with them, limiting their usage like purchasing a newspaper, limited time to listen to the radio, and least time to watch ads made on televisions. The application is considered more effective since it is free of cost and accessible to everybody. Moreover, the app is an easy-to-use, efficient selling medium for business and for easy access and purchase by customers. Our system will make small business/home businesses ready to meet the needs of most customers, with a simple design that is better and more attractive to customers.
QUguide: A Complete Platform to Support Engineering Students Learning at Qatar University
Project ID = S2122 24
Supervisor: Dr. Moutaz Saleh
May Qaddourah, Sheikha AlGuwaizi, Tahani Bakalaf
Every semester, students in the college of engineering (CENG) at Qatar University face a dilemma regarding choosing their courses and professors. When students prepare their list of courses for the next semester, they seek more information about the courses they intend to register for. However, the description of the courses provided in the banner system does not satisfy a student’s curiosity. Students tend to inquire about each course's level of easiness, intensiveness, and usefulness before registering for any courses. Moreover, students want to know other student’s experience in the courses they completed to learn from their experiences and avoid their mistakes. Another problem that students are concerned about is determining the suitable professors for the course, because no matter what the course is about, the assigned professor can make it interesting and easy. Therefore, students always ask their colleagues for suitable professors in specific courses. Presently,there are no portals that gather CENG students in which students can exchange their experiences, opinions, and useful resources. Hence, creating a portal that gathers all CENG students will help students in their university journey, allowing them to exchange their knowledge and experiences in their major and courses. Moreover, the portal will allow students to upload useful materials related to any course they took, so other students can download such materials and use them to better enhance their knowledge towards remarkable success. Additionally, the portal will have other useful services that students can use which will benefit them in their university life.
ShopAt: Supporting small local businesses in Qatar
Project ID = S2122 26
Supervisor: Dr. Tamer Elsayed
Mai Saed, Ranim Ibrahim, Fatma Mohamed
Due to the COVID-19 pandemic, there has been a general increase in home businesses in Qatar. Many home businesses upon starting do not study the market sufficiently to differentiate themselves from their competitors. Thus, many small business owners currently face serious difficulties some of which are: communication with customers, creating a recognizable brand image in the community, and promoting their products. Similarly, clients also face issues such as differentiating between small businesses, ambiguous and hidden prices, as well as long response times. Customers searching on social media platforms for a specific product tend to go through a lengthy process to complete an order, which in turn wastes their time and the business owners' time and efforts. Most customers in Qatar browse Instagram-based businesses and use Instagram direct message or WhatsApp to contact the businesses and place their orders. This method of placing and accepting orders is ineffective and majorly flawed. Some of these flaws include prioritizing orders of the most recent messages due to the arrangement of messages on the Instagram direct message platform. This complicates the system of processing orders by business owners, particularly when the business is faced with an unexpectedly high demand for a product and has received many queries and order requests. Additionally, due to the lack of a foolproof ordering process, customers will doubt whether their message has been received and so whether their order has been placed, this can give rise to many inconveniences if the customer requires the product within a certain timeframe, and in effect, the business loses potential customers. Customers will also be discouraged from ordering if the business response time is too long to their inquiries about the product of interest, such as stock availability and delivery times. Therefore, our team has decided to develop an application to tackle these challenges, aiming to help customers and business owners equally. We have named the application in question ""ShopAt"", which means ""shop at any time at our application"". We aim to provide business owners and customers with several functionalities and services to streamline the social media business experience. Some of these include a filter for the customer's items of interest, a favorite section for items and stores, and a smoother and more reliable ordering process. Through these services, we hope to provide an easier shopping experience for the client and business in addition to giving other businesses exposure and finally providing customers a wider range of choices.
Share App
Project ID = S2122 27
Supervisor: Dr. Khaled Khan
Fatma Abdulla Al-Khulaifi, Muneera Nasser Al-Naimi, Shaymaa Mohammed Al-Mohssen, Fatma Abdulrahman Al-Mansouri
With the spread of the pandemic COVID-19, most individuals became infected and suffered economic damage. For example, some people have lost their job or business, and others have had their income reduced, but most of these people have families who rely on them. On the other hand, some people have a lot of unwanted items such as clothes, furniture, or other household items that they want to dispose or replace with new items for their home. We have thought that instead of disposing of unwanted items which are still usable, they could donate them to others. Based on this idea, we have proposed the concept of donating items to needy people using an online system. We call it “Share”. What is the actual meaning of Share? Share is a charity application with various features that can assist both donors and beneficiaries. The beneficiary may easily browse for their needs, and if they want certain specific goods that are not available in the donated items, they can add them to their wish list. If they want monthly items like food supplies, they can sign up for a subscription for regular supply of foods. Furthermore, people can also borrow objects for a limited time if they do not want to keep them permanently. Donors, on the other hand, will be able to add items to the application, either permanently or temporarily, and fulfil the beneficiary's wish list, as well as accept the subscription to provide regular food stuff to the beneficiary. This application caters to both parties, donors and beneficiaries as a one-step-charity-service. It is expected that this application would be particularly useful to the society because at present there is no such service available in Qatar. We will offer them the help they need for an easy-to-use system with their basic level of computer literacy. Beneficiaries would feel more comfortable interacting with the application rather than physically visiting a charity office and asking for help. The beneficiary people would find themselves more dignified using this application. We have used the model of clientservice relationship in the interaction between beneficiaries and donors on this application. They are not required to interact directly, but their purposes are well served by this application.
Mudrek: A Learning Mobile Application for Autistic Children
Project ID = S2122 28
Supervisor: Dr. Saleh Mohammed AlHazbi
Maryam Salem Al-Marri, Dana Mohammed AlYafei, AlMaha Ebraheem AlKhelaifi
With the advancement of technology, a lot of technological tools are used and developed to facilitate the process of teaching children with autism spectrum disorder (ASD). Although users with ASD are different from one another, they have good capabilities in using computer technologies. Therefore, using a proper customizable tool with respect to the different user’s abilities will result in improving the children’s learning process and their relationships with family and friends. ASD children are independent learners, and they tend to favor learning visually rather than interpersonally. In this project, our objective is to design and implement a mobile application that is always accessible and aims to improve autistic children's ability to identify, categorize, differentiate, and label familiar items in their daily life, which ultimately improve their communication, social, and cognitive skills. The application provides help within reach for parents to support early intervention at home and to reduce the cost for the families.
EEG Real-time Monitoring during Immersion in Relaxing Virtual Reality Environment
Project ID = S2122 30
Supervisor: Dr. Elias Yaacoub
Shada Al-Mohannadi, Maryam Al-Meraizeeq, Fatima Awad
According to the Global Organization for Stress, 80% of people are stressed at work and according to the American Institute of Stress, stress causes 48 percent to have difficulty sleeping. Relaxation reduces stress, depression, and anxiety. There are several methods for relaxation, such as meditation. Electroencephalography (EEG) is used by scientists to analyze brainwave signals that explore the emotions and the cognitive processes of the brain. In recent years, Virtual Reality (VR) technology has drawn lots of attention. Thus, the use of VR, as a technique of relaxation, is a novel idea for assisting students and workers in achieving relaxation to help them focus on their studies and work. This project aims to acquire the EEG signals to analyze the characteristic frequency brainwave bands related to relaxation after the subject is exposed to a VR environment. The result of the experiments show that a relaxed VR environment has an impact on the human brainwave. Some EEG features, such power spectral density (PSD) ratios of brain waves like alpha/beta, theta/beta, alpha/ (beta + gamma), and theta/ (beta +gamma), were found to have a significant variance among different participants while watching relaxing scenes. These features will be used in the future to optimize the relaxation prediction model and relaxation interaction system research based on EEG.
Real-Time Stress Monitoring Through ECG Signal Measurement and Analysis Using IOT Wearable Sensors
Project ID = S2122 31
Supervisor: Dr. Elias Yaacoub
Sammar Suleiman, Dana Al Kuwari, Reem Bassam Tluli
Cardiovascular disease is a term for all types of diseases that affect the heart or blood vessels, including heart attacks, coronary heart disease, which is when the arteries are clogged, stroke, congenital heart defects and peripheral artery disease. One of the many causes of cardiovascular diseases is the stress level of an individual. Stress is often labeled as the silent or proxy killer. In fact, chronic stress is a major underlying origin of the top leading causes of death, globally. The significant contribution of stress to the development of disease is undeniable. The growth and availability of digital technologies involving wearable devices and mobile phone apps can afford the opportunity to dramatically improve measurement of the biological stress response in real time. In this project we will be using electrocardiography (ECG), which will record the electrical activity of the heart which will then help us detect the stress response by studying the stress features of human beings and characterize them in real-time while being exposed to multimedia content. Through this experiment we will see how technological devices can affect the human body and how we can help people monitor their stress levels through an application.
Child-monitoring fever and location via smart watch
Project ID = S2122 32
Supervisor: Dr. Khalid Abualsaud, Co-supervisor: Dr. Junaid Qadir
Fatma Hani Al-Khuzaei, Fajer Khalid Al-Emadi, Al-Anoud Abdulrahman Al-Emadi
Smartwatches are an emerging technology that combines smartphones and wearable accessories. Tasks such as tracking people's location, counting footsteps, and weather forecasting that were initially executed by smartphones can be carried out now by smart watches. Consumers of this product consider several factors to determine what type of smartwatch accommodates their needs. However, despite the increasing interest in smartwatches, there are still a few tasks that a smartwatch cannot perform efficiently. The purpose of this study is to embed a child-monitoring system within the smartwatch. The monitoring system will include temperature detection – so that the healthcare information of the child may be relayed to the parents in real-time, heart detection sensors – to collect information on the physical activity of the child and GPS for tracking – so that the caregivers may be informed of the whereabouts of the child in real-time. To achieve this, we will be using an ESP microprocessor along with sensors to monitor the parameters. An analog temperature sensor will be used to monitor changes in temperature. 18b20 module has been employed since this is a prebuilt PCB with the IC, and resistors will be attached.
Light-Based Therapeutic Glasses
Project ID = S2122 33
Supervisor: Dr. Abdulla Khalid Al-Ali
Fatima Al-Naimi, Aisha Al-Ishaq, Fatima Al-Kuwari
The combination of health care and recent technology is the leading factor of patient empowerment. The aim of this project is to develop a system that regulates a person’s circadian rhythm to enhance his/her mental health. The project introduces a system to treat jet lag in a short period of time by the direct exposure to blue light. It benefits people who are exposed to jet lag involving frequently traveling individuals, in addition to people exposed to Seasonal Affective Disorder comprising persons who are living in extreme Northern and Southern Hemispheres. The introduced system schedules blue light-based treatment sessions to achieve a speedy recovery from jet lag using healthy wavelength of blue light, which was showed to regulate circadian rhythm. This is accomplished through a wearable glass which emits a therapeutic wavelength of blue light at scheduled times. In addition to a wearable wristband which comprises of a sensing system that constantly senses the user heart rates and sends them to the mobile application to predict the user’s mental status by applying machine learning techniques on collected data. The proposed solution uses BluetoothLE as network medium to generate the communication between the two devices and the mobile application. The project strength point is centered around the fusion of machine learning techniques such as SVM model in addition to jet lag reducer system which lead to a unique project that minimizes jet lag symptoms and provides performance feedback based on predicted user’s statues. The impact of the solution concentrates on enhancing mental health by scheduling light sessions which regulates the user’s circadian rhythm and thus improves the overall mental health.
Smart Electronic Gate for Crowd Management
Project ID = S2122 34
Supervisor: Dr. Noor Al-Maadeed
Jomana Al-Jilani, Reem Al-Shamari, Nourah Al-Qahtani
All authorities responsible for regulating and controlling crowds in public spaces, whether they would be municipal police agencies or event and festival organizers, face a difficult challenge. The majority of the time, even with several entries and exit points, the crowd swells to a very vast physical area that is tough to monitor with staff on the ground. The controlling part is even more difficult due to the crowd's haphazard movement. Because a single mistake in crowd management can result in stampedes and significant loss of lives, the most important requirement is to act quickly in the event of any potential emergency. The present work explores the possibility of a smart electronic gate for crowd management to be used for the FIFA World Cup in 2022. The smart video sensors for surveillance and security applications are IOT-based and utilize the internet for different functions. These applications include crowd surveillance and sophisticated decision support systems that operate and transfer data through the internet. The study of crowd and pedestrian behavior is critical for smart IoT cameras and video processing. Simulation and tracking techniques have been studied in the literature to create relevant behavioral models. In both situations, ground truth is required to train deep models, and offer meaningful quantitative evaluation. We offer a system for crowd management and gate control. This will include counting people from camera feeds and a gate that will not be open if the capacity is full, sending alarms, and logging the number of people entering from that gates-to-gates administrator. The goal of this electronic gate is to allow fans to enjoy the FIFA World Cup 2022 in a safe environment. In other words, our system is a combination of hardware (smart network cameras, electronic sensors, and extra hardware components for our purpose), and software components written in any suitable programming language (MATLAB, Python) to analyze the gathered information from the hardware used devices to make decisions and depend on these decisions. Some commands will be sent to special sensors in smart electronic gates to do some actions to limit the number of people using those gates by closing them or any suitable action, and alarms will be sent to the gate administrators to take the proposed actions. The expected results are that the proposed system should be efficient in estimating the density of the crowd and sending alarms about the situation.
Smart Moves
Project ID = S2122 35
Supervisor: Dr. Abdulaziz Al-Ali
Maisam Elkhalaf, Bayan Khalouf, Rama Nawwas
Athletes of all sports expend enormous physical efforts on a daily basis to uphold the required level of skills. Therefore, they become more vulnerable to muscle and bone injuries during intensive, improperly performed exercises. Foot injuries result in significant complications that can cause pain and deviation even while walking. Athletes may fail to discover such issues at the right time before a severe and unrepairable injury occurs. Gait analysis is a critical therapeutic and diagnostic procedure that has been adopted to diagnose foot injuries for a long time. Nevertheless, the conventional methods used for gait analysis have limitations. It requires equipped laboratories operated by professionals, which are out of reach for a vast portion of the population due to the high cost and appointment capacity. This work is attributed to tackling this issue by designing and prototyping a portable and wearable device called Smart Moves, which performs gait analysis while performing a particular activity. Smart Moves aims to provide accurate diagnosis via machine learning techniques and ground contact time (GCT) measurements. The data is collected wirelessly from an array of sensors placed right above the ankles. Smart Moves is designed to detect gait abnormalities and the potential occurrence of an injury. The produced prototype collects accelerometer data to measure in real-time the asymmetry between the two legs via identifying the type of activity the user is performing and the ground contact time of each foot. Smart Moves displays the results on a mobile application in real-time. In this work, the achieved accuracy values of the activity recognizer, right-foot ground contact recognizer, and left-foot ground contact recognizer are 98.5%, 97.8%, and 98.7%, respectively. The achieved accuracies showcase the potential of Smart Moves to be adopted by the sports industry as a user-friendly and accurate wearable for the early diagnosis of foot injuries.
Outdoor Air Quality Monitor
Project ID = S2122 37
Supervisor: Prof. Amr Mohamed
Hanan Al-Shammari, Maryam Al-Naemi, Haya Al-Malhiya
Air pollution is one of the most serious scourges of our day, due to its impact on climate change as well as its impact on public and individual health through increasing sickness and deaths. Many pollutants play a crucial role in human diseases. Particulate Matter (PM) is a form of a particle with a varied but extremely small size that reaches the respiratory system through inhalation and causes cancer, cardiovascular and respiratory problems, reproductive and central nervous system malfunction. Although ozone in the stratosphere protects against ultraviolet irradiation, high levels of ozone at ground level are harmful, causing respiratory and cardiovascular problems. Furthermore, nitrogen oxide, sulfur dioxide, VOCs (Volatile Organic Compounds), dioxins, and polycyclic aromatic hydrocarbons (PAHs) are all classified as air pollutants that are dangerous to humans. Carbon monoxide can cause acute toxicity when inhaled in large amounts. Moreover, depending on the level of exposure, heavy metals such as lead can induce either rapid poisoning or persistent intoxication in humans. Among the ailments produced by these substances are respiratory disorders such as Chronic Obstructive Pulmonary Disease (COPD), asthma, bronchiolitis, lung cancer, cardiovascular events, central nervous system dysfunctions, dermatological diseases, and pneumonia. Last but not least, environmental pollution-induced climate change, as well as natural disasters, influence the geographical distribution of many infectious diseases. This project's purpose is to create an air quality monitoring system capable of detecting, and monitoring harmful gases, severe temperatures, and humidity, among other things. It also helps detect harmful chemicals before they cause additional harm to individuals and the environment. Developing a system that can deal with climate changes without being damaged is another purpose of this project and we are expecting to get accurate and scalable results when measuring the Air Quality Index (AQI), which can give indications to stakeholders about the severity and risk of work in some environment conditions.
Automatic Electronic Gate System Using BLE Beacons of EHTERAZ
Project ID = S2122 38
Supervisor: Dr. Qutaibah Malluhi
Aya El Sayed, Myesha Hoque, Sofia Basha
The Covid-19 pandemic has created a halt to our socio-economic lifestyle. One such example is the traffic congestion at the entrance of institutions for checking a user’s EHTERAZ health status and body temperature. EHTERAZ is Qatar’s COVID-19 contact tracing application used to monitor and prevent the spread of infection. This application displays a colored QR code indicating the health status of the user; green for healthy, yellow for quarantined, gray for suspected and red for infected. While some facilities may include a thermal scanner to automate the temperature check process, there is no technology that enables automatic detection of EHTERAZ status. This has resulted in using specified gates that undergo physical inspection for EHTERAZ app status, which in turn, increases the time to access a building, may lead to long queues or gatherings during peak times and requires the additional cost of hiring security personnel at these gates for inspection. Our project aims to eliminate the need of any personnel to physically check for EHTERAZ status. This helps prevent undesired human interaction between the users and security personnel at entrance and thus provides smooth entrance to a facility. This project develops an electromagnetic lock system, which searches for users’ EHTERAZ status by scanning the advertised Bluetooth Beacon information by the app. The users are granted entry permission only if their health status is green. Otherwise, the gate remains locked. For this purpose, this project takes into consideration two deployment scenarios. In the first scenario, the lock is independent and can make its own lock or unlock decisions. In the second scenario, all the gates of an institution are centrally linked to a database for logging lock use information while the decision-making authority is still maintained by the individual locks. This electromagnetic lock system is bundled into a package that comes with a webpage that includes a user view interface for logging information of user entrance history. In addition, is the system offers an optional feature of QR Code scanning where the lock opens if the scanned QR Code of EHTERAZ user is Green.
Speech Recognition using deep learning
Project ID = S2122 39
Supervisor: Dr. Mohamed Al-Meer
Reem Aldelayel, Ghada Aldosari, Sheikha Almannai
Due to the application of machine learning technology, advancements in natural speech processing lead substantially more sophisticated speech processing systems. The voice control of a small robot was designed to implement human-robot interaction. The fundamental contribution of this project is the design and implementation of a machine learning program that uses Raspberry-pi for voice processing, and then identifies instructions to move the robot. The requirements for evaluating commands on robot control were established. In addition, the robot's control architecture was developed and built. The model can classify a one-second audio clip as "down", "go", "left", "no", "right", "stop", "up" and "yes" depending on the actual command pronounced. This was implemented using deep learning which is a subfield of machine learning and AI and is inspired by the human brain structure. Deep learning has different types of algorithms, and to implement a speech recognition system, the CNN algorithm was utilized. After the audio files were converted into spectrograms the data were fed into a convolutional neural network (CNN) that takes an input image, processes it, and recognize it. There were also some additional preprocessing layers for this model which included the conversion of the waveform into a spectrogram. This model is installed into a small computer board the Raspberry Pi controls the robot using speech recognition. The results of the system gave an accuracy of 95%.
Detecting Atrial Fibrillation using Artificial Intelligence
Project ID = S2122 40
Supervisor: Dr. Junaid Qadir
Hissa Almeadhadi, Maryam Alhumaidi, Wadha Al-Shafi
Atrial Fibrillation (AF) is a severe heart condition that can lead to multiple life-threatening complications such as heart attacks, blood clots, or heart failure. It can be described as an irregular heartbeat in which fast electrical signals cause the upper chambers of the heart (atria) to contract rapidly and unsystematically. Atrial Fibrillation is the most common arrhythmia diagnosed in clinical practice, with an estimated number of people with AF being 0.5% worldwide. In 2019, AF was the cause of 183,321 deaths in the United States [37]. Studies have also shown that people of European descent are more likely to have AF as well as women are more likely to experience AF since women live longer than men and AF chances increase with age. Our project aims to detect Atrial Fibrillation using Artificial Intelligence which is Support Vector Machine algorithm (SVM) and K- Nearest Neighbor (KNN) that is easily portable and at a meager cost to be accessible to everyone, especially in underdeveloped countries where Electrocardiography (ECG) that Read ECG Signals from the patient. will tests are either overly expensive or not even available.
WAMDH: 1U CubeSat Training System
Project ID = S2122 41
Supervisor: Dr. Uvais Ahmed Qidwai
Asmaa Almarri, Ameena Alsheeb, Maha Fekri
As technology advances, the field of space exploration has introduced a new kind of nanosatellite, called CubeSat. CubeSats are commonly known as an inexpensive research spacecraft compared to other types of satellites. The CubeSat standard size is a cube of 10x10x10 cm3 dimensions and its mass ranges between 1 and 1.33 kg. CubeSats can be used in several applications such as weather monitoring, earth observation images, earthquake detection, and many more scientific and commercial investigations. As a result, CubeSats became extremely popular among universities, governments, space agencies, and researchers. This project aims to develop a CubeSat training system suitable for engineering students or CubeSat developer groups. This training system will provide the users a platform to experiment with different modules in the satellite, to gain hands-on training experience with various functionalities of a satellite, and possible troubleshooting in various functionalities. This training system has similar functionalities and components as those of a real CubeSat. The main difference is that it will operate in the lab instead of space. The CubeSat training system comprises of five sub-systems: attitude control, imaging payload, communication system, telemetry system, and on-board power system. Any issue in one of these subsystems would be easier to fix when the CubeSat is on the ground. Hence, engineers would be able to validate or monitor the CubeSat application that they designed before launching the actual CubeSat and sending it to space. The development of a low-cost CubeSat training system has increased recently, since there are no training systems of low cost available in the market. The solution proposed has achieved this important aspect of the design. In addition, the five sub-systems of the CubeSat have been implemented in this proposed solution.
A Tiny-ML Enabled Intelligent Plant Monitoring System
Project ID = S2122 43
Supervisor: Dr. Junaid Qadir
Haya Ali Al-Faihani, Shaikha Alaseri, Amna Hassan Baker
People nowadays have a very hectic lifestyle. This lifestyle leads to many overstressed individuals; having a hobby can reduce stress and help people feel more energized to do their work. There are different types of hobbies. This project focuses on plant caretaking, many people have a hobby of plant caretaking, but their busy schedule does not allow them to do it well; We propose to develop an intelligent plant monitoring system that can independently take care of the plant relieving the human users. Our system uses sensors to measure humidity, moisture, and actuators to control several parameters, such as a water pump system that will supply the plant with water. The plant’s health may be monitored, and its maintenance is ensured. Compared to existing embedded plant monitoring systems, we go the extra step by incorporating intelligent value-added functionality (such as keyword spotting and gesture recognition) by using Tiny-ML, a machine learning system for embedded tiny devices. Furthermore, we also propose to build a mobile-friendly web dashboard that can be used to monitor and supervise the home plants and an intelligent plant monitoring system. This project is non-trivial and leverages the state-of-the-art Tiny-ML library. Our resulting intelligent plant monitoring system can cost-effectively relieve the stress of overworked individuals using commodity devices and open-source systems.
"QUGM” QATAR UNIVERSITY CONTINUOUS GLUCOSE MONITORING
Project ID = S2122 44
Supervisor: Dr. Khalid Ahmed Abualsaud
Noora Al Bordeni, Fatima Al-Kaabi, Sara Al-Mohannadi, Mazun Alshahwani
Most people struggle to remember measuring their blood sugar from time to time, which may cause the blood sugar level to increase without the patient noticing. It may cause the patient to pass out without the knowledge of family members. Thus, if people have a device that measures blood sugar continuously, they do not need to check whether it exceeds the blood sugar risk level; it will automatically alert them and alert the people in the emergency contacts. Patients do have blood sugar monitoring devices; however, they are invasive and do not continuously read blood sugar levels. It can be considered wasteful in terms of time. If they were at risk, they manually tell the related people to help them if they can reach them. The solution to this problem is developing a system consisting of hardware and software parts with more advanced options. Advanced technologies and modern engineering have helped improve every aspect of people's lifestyles and continue to provide never-ending and innovative solutions that fulfill people's needs. One of the new technologies that have not been used widely yet is the PPG wave which can diagnose the patient without the need to put a needle or take a sample of blood, which is non-invasive, unlike what is available in the markets and hospitals these days. In this project, a bracelet that continuously measures blood sugar was designed and implemented, and it is a small, light, weight design that makes it portable. QU-CGM device consists of a Pulse sensor, ESP32 microcontroller, battery, and sliding switch to turn it on and off. In addition, the bracelet is connected to the QU-CGM application, which is designed to display the patient's glucose results. If the glucose results are higher or lower than the normal level, the application sends alerts to the user's emergency contacts. Since this solution is non-invasive, it is painless. It will provide comfort to the patient, as he will no longer have to measure his glucose with a needle from one time to another. If his glucose reaches unsafe levels, the application will take the necessary work and send alerts to the concerned people.
Indoor Air Quality Prediction System using Machine Learning
Project ID = S2122 45
Supervisor: Dr. Cagatay Catal
Aldana Alsulaiti, Manel Riahi, Nada Ben Hassen
Indoor air pollution has become worrying in recent years. The world is progressing, and the environment is paying the price. In countries where the weather is unbearable most of the year, people spend more than 80% of their time indoors. As such, they are constantly breathing indoor air which accumulates harmful toxins and results in many dangerous short-term and long-term health issues, and some specific problems such as lower academic performance and less focus. This calls for finding a way to optimize air quality indoors, but to do so, different ways need to be found to assess it and determine where the problem is (e.g., low oxygen level, high humidity). An inexpensive and easy-to-use monitoring device is necessary, which will detect harmful gases. Previous solutions are either expensive, hard to use, or do not detect most harmful gases, and it is usually complicated to read and understand the results of the readings. This project aims to design an indoor air quality monitoring system to detect harmful gases and levels of oxygen and show the results in a simple readable way with actionable tips to improve the air quality conditions. In this project, the sensors chosen are as follows: MQ2 (LPG sensor), MQ7 (Carbon monoxide sensor), MQ8 (Hydrogen concentration sensor), MQ135 (Carbon dioxide sensor) and DHT11 (humidity and temperature sensor). Choosing these sensors was based on the harmful cases that are important to identify, the availability, and the price, since the MQ series of sensors is cheap yet pretty accurate. The device will have its own mobile application that connects with it through Bluetooth. The mobile application will allow the user to trigger the measuring of the device and then read the results clearly and concisely. This end-to-end monitoring system utilizes Raspberry pi devices, a touch screen display, several sensors, and aims to measure and assess the indoor air quality of a space. This system is easy to set up and to use, has 80-95% accurate results and shows actionable tips depending on the situation or the danger.
The Implementation of Blockchains on IoT Devices for FIFA World Cup 2022
Project ID = S2122 46
Supervisor: Dr. Devrim Unal
Anjoud Al-Rumaihi, Fatima Al-Janahi, Muneera Al-Naemi
In recent years there has been an exponential growth in technology, and with that comes significant demand for better, faster, and more efficient technologies. There have been some revolutionizing technologies that have been introduced in recent years, such as the decentralized computing technology of blockchain. Blockchain has been a widely known technology that has been adopted and continues to be adopted in finance and the public and private sectors. This technology has introduced a new concept of security, reusability, and integrity of information and has proved to be an innovative yet efficient way of dealing with information. We are presenting the use of blockchain technology that will be implemented in all future aspects of ticketing applications and data processing. In this project, we implement our idea onreal-lifee information, which the FIFA 2022 committee organization could use to ease the access of information, enhance the security of the data, and decrease fraud and illegal reselling of the tickets through this technology. Using the blockchain alongside IoT devices also provides a more eco-friendly solution than regular databases.
Assistive Telexistence System Using Machine Learning Based Motion Generation
Project ID = S2122 47
Supervisor: Dr. Osama Halabi, Co-supervisor: Dr. Mohammed Al-Sada
Hoda Helmy, Somaya Eltanbouly, Muraam Abdel-Ghani
Recent technological advances and changes in work environments and global situations have increased the demand for working remotely. The need to interact with objects in the work environment makes current remote working solutions insufficient, and the use of telexistence systems becomes elevated. The major problem related to telexistence systems is enhancing the immersion experience of the end-user so that they feel as if they were physically in a remote environment. The telexistence system includes using a robotic arm that closely maps the motion of the user’s arm. It also enhances the vision system to feel visually immersed. It enables the user to attain a higher level of connection with the remote environment by feeling the objects they touch with the robotic arm. It gives them the sensation of touching it themselves. This project focuses on developing an assistive telexistence system that enhances the end user’s telexistence experience by using a five-finger robotic arm on the remote side that better maps the motion of the user’s hand than a regular robotic gripper would. The user can feel that they are interacting with the object by integrating a haptic feedback system with the five-finger robotic hand. It promotes the visual system to a stereoscopic stream of the remote environment with the ability to view it from different angles by moving the head, supporting the end-user’s immersion in the remote environment. Moreover, a new enhancement to the teleoperation motion controller is proposed by providing a level of autonomy that assists the user in reaching the objects they want to interact with. All these features will promote the telexistence experience of users and allow them to feel much more immersed in the remote environment, which will enable a smooth remote working experience in a broader range of fields. Evaluation of the system’s performance with the enhancements showed that 70% of the participants preferred to use the system with haptic feedback and assistance activated. Participants in the evaluation also filled in a questionnaire about the sense of body agency they felt while using the system, which consisted of three main components: acceptance of the system, control of the system, and change from the system. On running the repeated measures ANOVA test on the responses, a significant difference was found in the mean results for the control component of the system between trials with no haptic and no assistance and trials with no haptic but assistance activated. The result reflects that the assistance module improved users’ sense of control of the robotic arm. Additionally, it highlights that the activation of haptic feedback gives users a sense of assurance in completing the task that they overlook the assistance provided to them. Both analysis results support that introducing haptic feedback and assistance help enhance the telexistence experience of the system users.
Automating the process of harvesting mature fruits
Project ID = S2122 48
Supervisor: Dr. Cagatay Catal
Noor Husam Mohammad Abusirriya, Khadija Ahmad M A Mojadam, Muntaha Abdelkarim M Abdoon
Manual harvesting is traditional intensive labor, time-consuming and expensive method. It has been the preferred method for attaining high-quality control and minimizing the losses (e.g., damaging the fruits.) [1]. It is a commonly practiced method in various regions of the world. With the digitalization revolution, there has been an efficient alternative for many time-consuming tasks. Digitalization has been adapted in the farming field too. Digital farming has been widely researched and improved over the years, and it is faster and more efficient than manual labor. In our project, we explore the possibility of using a digital mechanism to harvest mature fruits. The mechanism is applied by using Yahboom Transbot Robot ROS AI with Jetson Nano 4GB. The robot includes a robotic arm, LiDAR, and depth camera suitable for the project. The robot creates an internal world-map of the surrounding environment and then uses the depth camera to detect mature fruits (e.g., tomatoes). If the fruit’s maturity level is suitable, the robotic arm plucks it. This autonomous mature fruit detection system improves the efficiency within the farm and decreases the number of farmers needed within the farm. This project is a step toward taking digital farming to the next level in the near future.