First Project: Decentralized Voting System on Ethereum Blockchain
Advisor: Dr. Ramzi Saifan
Students:
Voting is a fundamental democratic process, yet traditional voting systems suffer from security vulnerabilities, inefficiencies, and lack of transparency. In this project, we propose a blockchain-based decentralized voting system to ensure secure, transparent, and tamper-proof elections. By leveraging Ethereum smart contracts, we eliminate the risks associated with centralized voting systems, providing a trustless mechanism for vote casting and counting. The system is designed to enhance security, transparency, and accessibility by utilizing blockchain's immutable ledger and cryptographic principles. The voting process is automated using smart contracts, ensuring that votes are recorded accurately and cannot be altered. Our system features a user-friendly web interface that allows voters to securely authenticate and cast their votes, while the backend enforces authentication and vote validation through blockchain technology. To evaluate our system, we deployed it on an Ethereum test network and conducted simulations to measure its efficiency, security, and performance. The results demonstrate that blockchain-based voting significantly reduces the risk of fraud, enhances voter trust, and provides a verifiable election process. While challenges such as scalability and transaction costs remain, our approach offers a promising foundation for future improvements. We recommend further optimizations in gas fees, usability enhancements, and adoption of privacy-preserving techniques such as zero-knowledge proofs
Second Project: Intelligent Vehicle-to-Person Communication System
Traffic congestion and safety are critical problems in modern cities. Our project is the design of an intelligent communication system for enhanced real-time traffic management via the integration of Vehicular Ad Hoc Networks (VANET), Roadside Units (RSUs), and a centralized server, and a user mobile application. The local traffic department has announced that a small change in the departure time, a few minutes earlier than peak hours, can significantly reduce congestion. This project aims to manage the flow of individuals by providing advice on the optimal time to leave based on real-time traffic conditions. Previous solutions, such as Google Maps and Waze, provide traffic updates but do not actively manage movement. Existing research in intelligent transportation systems has focused on accident detection and route optimization. Our project builds on these efforts by offering dynamic, personalized travel recommendations that help users determine the best time to start their journey based on real-time and predicted traffic conditions
Third Project:
Design and implementation for object detection and tracking system using radio-frequency circuits.
Advisor: Dr. Raed Alzubi
The project focuses on designing a sensing and surveying system for objects using radio frequency (RF) technology and the ESP32 microcontroller. A 2.4 GHz signal is generated by an RF generator and split into two paths via a bidirectional splitter. The first path is transmitted through the RF-TX antenna, while the second path is directed to a phase shift measurement unit. The reflected signals from objects are received via the RF-RX antenna. The system calculates the time difference (Δt) between the transmitted and received signals to determine the object's distance, known as the Doppler effect. The phase shift is also analyzed to calculate the object's speed. The ESP32 processes all measurements and displays the results, such as distance and speed, on a 20x2 LCD screen via I2C connection. The system is characterized by simplicity and accuracy, with the low cost and small size making the design distinctive and important for many applications, including automation, robotics, and security systems. The project's architecture leaves room for future development or expansion of features as the ESP32 is used.
Fourth Project: Localization Problem in Wireless Sensor Network
Wireless Sensor Network (WSN) is defined as a group of sensors used to monitor, record and detect some type of inputs from both the physical or environmental condition such as heat, light, pressure, humidity. WSNs are widely used in many applications including search and rescue, disaster relief, target tracking, military and smart environments. Sensors in WSN collect information about the surrounding conditions and sent it to a control point. One of the important parts of this information is the physical location of the sensors. However, using Global Positioning System (GPS) on each sensor is not a good practical solution; high cost in a WSN that contains thousands of sensors, high power consumption for a limited battery-powered sensor, low accuracy. Therefore, different localization algorithms for WSNs have been proposed in the literature. In this project, we studied different localization techniques, then we exploited the good feathers of these techniques in order to propose a new efficient and accurate technique. Simulation results have verified the high estimation accuracy achieved by the proposed technique.
Fifth Project:
IoT-Based Smart Street Light System
Advisor: Dr. Talal Edwan
StreetSenseLight is an innovative smart street lighting system built in the University of Jordan area that integrates advanced simulation tools, including Veins, SUMO and OMNeT++, to optimize urban energy consumption.
The system dynamically controls streetlights, activating them only when vehicles or foreign objects are detected, significantly reducing unnecessary energy use while ensuring safety. Utilizing OpenStreetMap for real-world map integration and leveraging wireless sensor networks (WSNs), the project employs 868 streetlight nodes for both sensing and lighting functionalities.
By implementing state-of-the-art object detection and vehicle tracking technologies, StreetSenseLight enhances urban infrastructure sustainability and efficiency, presenting a scalable and adaptable solution for modern smart cities. StreetSenseLight integrates pathfinding by simulated traffic with real-world routes at the University of Jordan, activating only the essential streetlights for moving vehicles and pedestrians.