Project Title: Smart Speed Camera Based on Automatic Number Plate Recognition: Phase II.
Abstract:
Road traffic accidents are a significant cause of accidental deaths in Qatar, with residential compounds and institutions being particularly vulnerable due to the absence of government-issued speed radars. Current speed monitoring solutions are inadequate for large-scale deployment and lack real-time notifications, making it necessary to develop an Automatic Number Plate Recognition (ANPR)-based, fully automated speed camera system to monitor speed limit violations in residential compounds and institutions and notify relevant authorities in real-time. To address this problem, this project aims to design and implement a smart speed camera system based on ANPR. The system will use a high-resolution camera connected to an ANPR subsystem with a multi-core edge device, such as a Raspberry Pi, Odroid, or Nvidia Jetson, for processing and will analyze retrieved number plate (NP) data locally before transferring with a secure-IoT cloud architecture. Multiple units will be installed at strategic locations within the country to ensure maximum coverage and improve road traffic safety in Qatar, with the system also providing real-time notifications to authorities and concerned management parties.
Students Names: Noora A. Ali, Fatima H. Ali, Muneera A. Ali
Supervisor: Dr. Faycal Bensaali
Project Title: Deep Learning-based Biosensor for Early Detection of Ventilator-Associated Pneumonia: Design and Clinical Validation.
Abstract:
Ventilator-associated pneumonia (VAP) is a serious and potentially fatal complication affecting patients who require mechanical ventilation (MV). Up to 28% of patients undergoing MV in the intensive care unit (ICU) are at risk for VAP, the most common healthcare-associated infection and the most common nosocomial infection [1]. Pneumonia makes up over a third of all nosocomial infections in ICUs, with 83% linked to MV [2]. The development of VAP is associated with increased morbidity, mortality, length of hospital stay, and healthcare costs. Pyocyanin (PYC), a volatile organic compound (VOC), is produced by Pseudomonas aeruginosa, a common VAP-associated pathogen, and can be detected in the breathprint of infected patients, indicating a potential biomarker for early VAP detection. The proposed project aims to develop a non-invasive, point-of-care diagnostic tool for the early detection of VAP in intubated patients using a novel in-house fabricated graphene-based biosensor. The biosensor will be functionalized with DNA aptamers specific to PYC and integrated with deep learning (DL) algorithms for accurate, reliable, and non-invasive VAP detection. With a sensitivity range of 1-100 ppb, the biosensor is highly selective and can provide a reliable and accurate diagnosis, which will significantly advance the critical care medicine field by improving patient outcomes and reducing complications associated with VAP.
Students Names: Rabab M. Attaalla, Hend M. ElDakhakhni, Eman G. Ismail
Supervisor: Dr. Faycal Bensaali
Project Title: eMindReader: A machine learning-based decoding system for recognizing inner speech in complete Locked-in syndrome patients.
Abstract:
There are millions of people suffering from complete paralysis, Locked-in syndrome, Multiple Sclerosis, Arthritis, Muscular dystrophy, Parkinson’s, and Spinal cord injury. These diseases can lead to partial or complete locked-in syndrome and pose severe restriction on the ability to engage in communication with family and society. Several invasive and non-invasive brain-computer interfaces (BCIs) have been developed as communication tools for individuals in LIS. These rely on either the remaining control of eye-movement, (facial) muscles or neural signals. However, if the patient loses control of facial muscles or cannot open their eyes voluntarily, present assistive technology can no longer provide communication for completely locked-in state (CLIS) patients. Thus, once all voluntary movement is lost, neural mechanisms to produce communication fail.
Students Names: Raghad M. Aljindi, Malek Chabbouh, Diala I. Bushnaq
Supervisor: Dr. Muhammad Enamul Hoque Chowdhury / Dr. Muhammad Salman Khan
Project Title: Development of Next Generation Perovskite Solar Energy Technology at Qatar University.
Abstract:
Perovskite solar cells (PSCs) have attracted a lot of attention recently due to several advantages when compared to silicon-based cells such as low cost, high efficiency, and simple manufacturing process. PSCs have emerged as one of the most exciting fields of research of our time – the World Economic Forum in 2016 recognized them as one of the top 10 technologies 2016 onward. Qatar Foundation and then Qatar University have classified PSCs as main technology for energy efficiency. PSCs poised to revolutionize how power is produced, stored and consumed that would lead the near future “paradigm shift” in the energy sector. Despite these unique characteristics, PSCs suffer few challenges that are yet to be solved such as lack of long-time stability and the toxic materials used in the perovskite compound. The stability issue stems from the exposure to weather conditions such as atmospheric moisture as well as ion migration that becomes an issue under illumination. Fresh undergraduate students will be involved to in this green energy theme to address these issues. They will be trained in such a high-profile field in an exciting learning environment, fostering capacity building. This project aligns with the road map of both QNRF and research at Qatar University (Energy, Environment & Resource Sustainability) by addressing Solar PV (emerging technologies and performance improvement). It will be a very plus to Qatar University by enhancing research and technical skills in the emerging field of perovskite PV technology, and will prepare fresh engineers for such a Qatar’s national priority.
Students Names: Abrar M. Al-Kuwari, Shahd F. Alkaid, Aisha M. Al-Shahwani
Supervisor: Dr. Farid Touati
Project Title: Overcurrent protection of microgrids with renewable energy sources.
Abstract:
Overcurrent protection is a critical component of microgrid operation, as it ensures the safety and reliability of the system by detecting and isolating faults in a timely manner. However, microgrids include multiple distributed energy resources and various types of loads, which presents challenges for designing effective overcurrent protection schemes. In particular, the coordination of protection relays is crucial to prevent unwanted tripping and minimize disruption to the system. Moreover, the integration of renewable energy sources such as solar and wind power, which can exhibit variable and intermittent behavior, adds further complexity to the overcurrent protection problem. Therefore, there is a need for developing an overcurrent protection scheme research that can address the unique challenges of microgrid operation and ensure the reliable and safe operation of the microgrid.
Students Names: Haya J. Al-Kubaisi, Fatima A. Ashkenani, Maryam A. Abdulwahab
Supervisor: Dr. Maher Azzouz
Project Title: Design of a Solar PV based EV Charger for the Parking Area of Qatar University Campus.
Abstract:
To reduce the carbon foot print in Qatar, the penetration of electric vehicles is increasing in the market. The penetration of electric vehicles in Qatar may lead to extra burden on the existing grid and even may lead to various issues like dip in frequency and dip in bus voltages of the system. In worst case, it may require modification in the existing infrastructure to supply the extra demand created by electric vehicles. The electric vehicles available in the parking area of academic institutes and commercial areas required to be charged from the supply provided by the main grid. This leads to creation of huge charging load demand on the grid.
Students Names: Noura S. Al-Kuwari, Alanood H. Aldosari, Shayma H. Al-Basti
Supervisor: Dr. Atif Iqbal
Project Title: Design and implementation of networked dc microgrid using Controller Area Network (CAN) based communication.
Abstract:
Microgrid is proved to be a potential solution to supply increasing global energy demand. A dc microgrid includes various renewable energy sources like micro turbines, fuel cells, solar PV, wind power and energy storage units. To enhance the reliability of supply, and improve stability of system during imbalance in generation and load demand, battery sources are provided in dc microgrid. As the battery has to be charged after every discharge period, battery based sources are controlled by droop controllers for proportional sharing of load power among sources. However, in dc microgrid, proportional sharing of load current among sources deteriorates due to unequal values of interconnecting cable impedances.
Students Names: Maryam A. Al-Boenain, Lara R. Bsharat, Aliaa A. Sinoussy
Supervisor: Dr. Atif Iqbal