The highly anticipated senior projects’ presentations took place on May 6th at the state-of-the-art new engineering building H07. These remarkable projects, the culmination of tireless efforts by talented students, were subjected to rigorous evaluation by industry examiners. After careful deliberation, outstanding projects from each program, Computer Science (CS) and Computer Engineering (CE), emerged victorious. Exceptional teams of these winners will be chosen to proudly represent our department in the upcoming college contest. We eagerly anticipate the success that awaits our representatives as they compete at the college level, confident in their abilities, to make our department proud once again. 

Winning Projects in CSE-SDP23 Contests Day  

CE Rank 1

Project title: Q-SAR: Drone Swarm for Disaster Management

Students: Ali Elmancy, Abdalla Ahmed, Assem Alnajjar

Supervisor: Dr. Amr Mohamed

Abstract:

• SAR operations face difficult environments.​
• Drones offer faster and more effective SAR missions.​
• Design a drone system to enhance SAR missions.​
• Radar sensors are used for under-rubble survivor detection.​
• Leverage autonomous smart drones.​
• Drone assembly and sensor integration.​
• Design a wireless charging stations for drones.​
• Develop a backend for ground control and monitoring.

CE Rank 1 (equally-ranked)

Project title: Marathon Monitoring System

Students: Aly Okasha,  Mohammad Rayyan,  Ibrahim koubeisi 

Supervisor: Dr. Noora Fetais

Abstract:

The challenges in marathon organization, in particular participant safety and data collection. We’ve evolved a product to track participant positions, detect cheating, identify fainting, and easily transmit data to event administrators.

CE Rank 2

Project title: NABATEQ: Plant Health Monitoring System
Deep Learning Classification Approach 

Students: Amro Moursi , Mohamed Tahar, Malek Hamad, Hamad Alansi

Supervisor: Dr. Uvais Qidwai

Abstract:

This project focuses on the development and implementation of an advanced plant health monitoring system. Our approach involves addressing the critical environmental factors essential for preserving plants’ well-being, including temperature, soil moisture, water levels, humidity, as well as the presence of essential nutrients like Nitrogen, Phosphorus, and Potassium. 

Central to our methodology is the utilization of computer vision technology with Artificial Intelligence to provide health ranks for the plants under monitoring. By leveraging this data-driven approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

CE Rank 3

Students: Abeer Madyar , Kawther Ahmed,  Leen Alinsari,  Razan Abdelgalil​

Supervisor: Dr. Mohammed AlSada

CS Rank 1

Project title: Vaultexe/OSS Zero-knowledge Self-hosting Password Manager 

Students: Ahmed Ashraf, Husam Snober, Mohammed Saqallah, Walid Ben Ali​​

Supervisor: Dr. Moutaz Saleh 

Abstract:

In this digital age, we rely on passwords to protect our online presence on the web. With so many passwords to memorize, we experience password fatigue and easily fall into the trap of reusing weak passwords across different sites. This is a serious security risk, as a single compromised password can give attackers access to many other accounts. To address this issue, we introduce Vaultexe, an open-source self-hosted zero-knowledge password manager.​

CS Rank 2

Project title: PassGuard

Students: Youssef Aly,  Essa Ahmed Kamel Abou Jabal, Mohamed-Dhia Abdaoui,  Khalifa Yousuf

Supervisor: Dr. Mohammad Saleh

Abstract:

The importance of a password in today’s world cannot be overstated. Unfortunately, a large number of people falls victim to data breaches because of their reliance on weak passwords, default passwords, reused passwords. It can be explained by a simple reason: it is more convenient for the general public to use predictable passwords and reuse them.

Here comes PassGuard, an offline password manager application, whose sole purpose is to provide password security and user convenience.

CS Rank 3

Project title: ReWisely: a ChatGPT-based comprehensive revision platform for generating user-personalized study materials

Students: Amani  Mamiche, Asma Bahabarah,  Khadija Khedr,  Taqwa  Ellabad

Supervisor:Dr. Moutaz Saleh

Abstract:

Our project aims to modernize the creation of revision material by integrating AI into a comprehensive, interactive, customized, and user-friendly web application. It focuses on developing a platform capable of handling vast amounts of data and offering assistance through text summarization, flashcards, question extraction, the Feynman technique, and mind-mapping functionalities.​