Students

I had the privilege to work with and supervise the following talented students (annually updated):

Graduation Project Title (2021): Human Congestion Monitoring System.

Abstract: Detecting congestions quickly and efficiently is an important role in avoiding tragic events. Immediately detecting congestions gives a chance to control the area by closing the paths leading to it or by sending officials to organize the congestion. The aim of this project is to build a complete system that monitors public areas to automatically detect congestions in real time. This system can be utilized in numerous fields such as logistics and safety fields.  

To achieve the aim of the project, the proposed system will apply computer vision techniques to process a live camera feed (possibly multiple) of a specific area. Once a number has been specified for the maximum capacity of that area, an alert notification is sent when that maximum is reached. The alert contains information such as the degree of the congestion, alert time, and camera feed location. An objective is to build a simple GUI that displays all camera feeds along with all generated alert notifications. The GUI will also display an active counter for each camera feed.

Graduation Project Title (2022): Automatic Vehicles Monitoring System.

Abstract: The increasing number of vehicles in our world causes rapid growth of traffic in roads. This rapid traffic growth creates a need for monitoring systems of vehicles for safety and control purposes. Monitoring systems of vehicles provide means to detect roads and traffic status in real time.

In this project, the proposed system will automatically detect and monitor camera feeds to count oncoming/outgoing vehicles in certain areas to provide roads and traffic status. One of the main components in the proposed system is the object detection component. This component employs artificial intelligence algorithms and techniques such as TensorFlow API and ImageAI to detect vehicles. Further, the system will employ a duplicate detection component to avoid counting the same vehicle multiple times. Also, the system will utilize a DBMS to store roads information for future analysis tasks. The detection accuracy of the system will be evaluated based on ground-truth data.

Graduation Project Title (2023): Automatic System for Police Zones Allocation based on Constraints.

Abstract: This project focuses on the problem of assigning police zones to police officers to maximize the utilization of police workforces. Performing this assignment task manually by police chiefs requires a lot of manual and mental effort. Hence, this project aims to propose an automatic system to improve this zones allocation task to increase people’s safety and lower police response time. 

The main goals of this project are to design a complete system, which include a map view, and enables police chiefs to select and assign zones on the map directly. Moreover, the project aims to design and implement a process to optimize the assigned zone based on specific constraints. The project also requires a DBMS to store zones allocation information. 

Graduation Project Title (2024): Correl8: Detecting Correlated Data Series in Real-Time.

Abstract: Correl8 is a real-time system for detecting significant correlations in time series data across various fields, using the Pearson correlation coefficient. It allows users to set thresholds for alerts on relevant correlations, supports ongoing monitoring, and facilitates real-time data stream analysis.