Project Title: Valvular heart disease detection using signal analysis of phonocardiogram signals.
Abstract:
The heart is a critical organ that beats to pump blood all around the body, and valves function in a way that prevents the reverse flow of blood during this process. So, it cannot come as a surprise that Valvular heart diseases (VHDs) impact heart function. VHDs are structural defects in the heart valves, contributing significantly to global morbidity and mortality rates. While echocardiograms remain the gold standard for diagnosis, their reliance on specialized equipment and expertise limits accessibility, especially in primary care settings. In this project, we develop machine learning and deep-learning-based models that will classify normal and abnormal heart sounds. This is achieved by training the models using publicly available phonocardiogram (PCG) datasets such as the Physionet 2016 database. Next, the machine learning and deep learning models models are employed to classify and detect abnormal heart sounds, possibly indicative of VHDs. By optimizing filter design, developing visualization tools for heart sound analysis, and implementing advanced classification algorithms, the project aims to provide an efficient and accessible alternative for detecting VHDs, ultimately improving patient outcomes. The model performance is measured in terms of accuracy, precision, F1 score, and recall.
Students Names: Abdullah Saif, Salman Binyamin
Supervisor: Dr. Muhammad Salman Khan
Project Title: Smart Home Energy Management System.
Abstract:
The increasing demand for energy and the need for sustainable practices have led to a rising interest in home energy management. Current residential energy systems lack intelligent control, resulting in inefficient energy consumption. The main problem addressed by this project is the lack of a comprehensive Smart Home Energy Management System that utilizes IoT and machine learning to optimize energy usage, reduce costs,
and promote sustainability.
Students Names: Ahmed M. Alashqar, Hareth N. Omar, Mohammed T. Aboushakrah
Supervisor: Dr. Ridha Hamila
Project Title: Integrated Additive Manufacturing and CNC Machine.
Abstract:
This project presents the development of an innovative embedded system that integrates a 3D printer and a Computer Numerical Control (CNC) milling machine into a single device. The system utilizes shared motors for movement across three axes, enabling both additive and subtractive manufacturing capabilities in a compact and cost-efficient design. The motivation for this project stems from the need for versatile fabrication tools that minimize workspace requirements and reduce costs for makers and small businesses. Existing solutions either too expensive or limited in functionality. Previous works have explored dual-purpose machines; however, these systems are usually expensive and very advanced to control. Such limitations make these machines less practical for professional or multi-functional use. To address these issues, this project proposes the use of Marlin firmware for 3D printing and Garble(GRBL) firmware for CNC operations, leveraging a robust embedded control system that ensures compatibility and efficient motor utilization. This solution was selected for its reliability, ease of implementation, and ability to meet the project’s objectives. The methodology involves designing the embedded system architecture, programming the firmware for smooth operation, and integrating the hardware, including spindle motors, power supplies, and switches, to support both printing and milling tasks. Preliminary results demonstrate high precision in both 3D printing and CNC machining modes, with significant improvements in system efficiency and cost-effectiveness compared to standalone machines.
Students Names: Azzam A. Al-Tairi, Ibrahim E. Elsayed, Munir A. Issa
Supervisor: Dr. Mohamed Sultan Mohamed Ali
Project Title: Design of a Low-Voltage DC Microgrid for Camping Purposes.
Abstract:
This project presents the design, modelling, and simulation of a low-voltage DC microgrid aimed at enhancing energy efficiency and integrating renewable energy sources. The system comprises three key subsystems: a photovoltaic (PV) panel with a maximum power output of 400 W, integrated with a cascaded boost converter that steps up the voltage from 24 V to 120 V, employing Maximum Power Point Tracking (MPPT) for optimal energy harvesting. The bidirectional converter ensures efficient energy storage and management, with the system supporting a battery capacity of up to 500 Wh. Ahierarchical control strategy is implemented to maintain stability and enable power sharing among distributed generation units. The system operates within the constraints of ensuring a stable DC bus voltage of 120 V and is designed to meet IEC 61850 standards for communication and control within microgrids. MATLAB/Simulink was utilized for system simulation and validating subsystem performance under various operational scenarios including dynamic load and varying irradiance conditions. The proposed microgrid demonstrates a scalable and efficient solution for renewable energy integration, addressing challenges such as power flow management, voltage regulation, and dynamic load demands, and ensuring compliance with key standards like IEC 60068 for environmental performance.
Students Names: Ali K. Miqdad, Mahmoud M. Shanaa, Musaab O. Ali
Supervisor: Dr. Maher Azzouz
Project Title: A virtual inertia Control Schemes for DC Microgrids.
Abstract:
DC microgrids (DC-MGs) have experienced rapid growth, driven by the integration of distributed generations (DGs), energy storage, and local DC loads. Bidirectional grid-connected converters (BGCs) serve as the crucial link between DC-MGs and the utility grid, managing energy exchange, maintaining DC bus voltage stability, and enhancing system efficiency. However, DC-MGs, being low-inertia grids dominated by power electronic converters, face challenges such as voltage fluctuations due to frequent load switching and intermittent DGs like PV and wind sources. To address this, integrating virtual inertia control into BGCs shows promise in increasing DC-MG inertia, reducing voltage fluctuations, and enhancing stability. This project will design a control strategy for DC microgrids (DC-MG) using bidirectional grid-connected converters (BGCs), inspired by virtual synchronous machines (VSM). The goal is to increase DC-MG inertia and reduce voltage fluctuations. A mathematical model will be established for the BGC system and analyzes how fluctuations in power affect the DC bus voltage. A method to minimize disturbances caused by the BGC’s output current will be developed, aiming to stabilize the DC bus voltage. Simulations and experiments, will be carried out to validate the effectiveness of the proposed strategy.
Students Names: Abdalla H. Abdelhamed, Fahad M. Alkhater, Moemen Y. Eldukany
Supervisor: Dr. Lazhar Ben-Brahim
Project Title: GSM-based power quality analyser for smart distribution systems.
Abstract:
This project presents the development and software implementation of a GSM-based Power Quality Analyser (PQA) for smart distribution systems, designed to address critical challenges in monitoring and managing electrical power quality. In the long run, the project focuses on implementing a cost-effective solution with real-time capabilities to detect, measure, and analyse various power quality disturbances, including voltage sags, swells, interruptions, harmonics, and frequency variations. The system involves the simulation of an 11kV/0.415kV power distribution network that generates voltage and current waveforms with embedded power quality disturbances. Signal-processing algorithms are implemented to calculate key power quality indices based on international standards, and the analysed data is transmitted via GSM to a cloud platform for visualization. ThingSpeak is used for real-time monitoring and fault notification, providing an intuitive graphical user interface for operators to assess system health effectively. The system achieves compliance with industry standards for accuracy, efficiency, and reliability while addressing the limitations of high-cost commercial analysers. It enables proactive maintenance and rapid fault response, particularly in remote areas with limited connectivity. This project contributes to advancing smart grid technology by improving accessibility to power quality monitoring tools for diverse applications.
Students Names: Bilal Hussain, Md Iftekhar Ahamed Nafis, Saad M. Ejaz
Supervisor: Dr. Maher Azzouz
Project Title: Investigation of PV-Integrated Dynamic Overhangs in Qatar.
Abstract:
A dynamic overhang is an adjustable shading device designed to optimize sunlight and reduce heat gain in buildings, improving energy efficiency by lowering cooling demands. This project focuses on the design and development of photovoltaic (PV)-integrated dynamic overhangs aimed at enhancing energy efficiency in buildings in Qatar’s hot climate. The work involves designing a solar PV system integrated with a dynamic overhang, developing a sun-tracking mechanism, and creating an IoT-based sensor system for real-time monitoring and performance evaluation. The team will select appropriate PV panels, sensors, and a battery storage system, ensuring the system could monitor both energy generation and environmental parameters such as temperature and humidity. A sun-tracking system will be designed to adjust the overhang’s position based on the sun’s trajectory, optimizing solar energy capture throughout the day. Additionally, an IoT-based platform will be developed to collect and process real-time data, enabling the continuous monitoring of energy performance and environmental conditions. The integration of these subsystems is aimed at reducing cooling loads, improving indoor comfort, and contributing to more sustainable energy solutions in Qatar’s extreme climate.
Students Names: Ahmed M. Altairei, Aiman N. Alhamoodi, Hasan D. Alhaddad
Supervisor: Dr. Farid Touati
Project Title: Design and Development of a research grade hydroponic station.
Abstract:
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. In addition, the optimal contents of the nutrients as well as the ambiance parameters such as lighting, temperature, and moisture/humidity can significantly affect the outcome of the crops. Various combinations of these parameters exist to grow specific plants but it is still a continuous process. However, the limited functionalities in the existing hydroponic farming infrastructure. These problems can be overcome by developing a customizable hydroponic bed where various parameters can be controlled remotely and plant growth could be monitored using AI tools. The proposed project intends to build a multi-level hydroponic bed system with controllable nutrients’ level, temperature, humidity, and lighting control in terms of intensity as well as color. The work will be conducted in supervision of QU Agriculture Research Station.
Students Names: Abdullah A. Almusri, Mohammed A. Ghadamsi, Naeem H. Abdul kadir
Supervisor: Dr. Nader Meskin
Project Title: Design and Development of an Autonomous Underwater Vehicle for RoboSub.
Abstract:
More than 73% of the earth’s surface is covered by water, and ocean exploration is one of the next challenges in the scientific research and development in this century. Various analyses and development about the ocean such as marine environment, ocean life and ocean resources research require the collection of ocean data by survey and observation in the actual underwater environment. In this project, the first prototype of autonomous unmanned underwater (AUV) vehicle will be developed to fulfill the requirement of RobotSub competition.
Students Names: Saad M. Aden, Ali Moharram, Mohammad B. Hamad, Suhib A. Alsfarini
Supervisor: Dr. Nader Meskin