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.