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Recent Submissions

Smart Walker
(Aladdin Masri, 2026-06-11) Lama Enad Hag; Omar Alaa Jarbou
Smart Walker is an intelligent mobility assistance system developed to support visually impaired and elderly individuals during daily navigation. The project aims to enhance user safety, independence, and environmental awareness through the integration of sensing, embedded systems, and artificial intelligence technologies. The system combines an OAK-D camera for object detection and recognition with a LiDAR sensor for obstacle detection and distance measurement. Sensor data are processed by a Raspberry Pi to determine safe navigation paths, while an Arduino Mega manages steering assistance, braking control, authentication, and monitoring functions. Real-time voice guidance is provided to inform users about surrounding obstacles and detected objects. Additional features include RFID-based authorization, banknote recognition, battery monitoring, guardian monitoring, and automatic lighting control. Experimental testing demonstrated the system's ability to reliably detect obstacles, recognize objects, provide navigation assistance, and perform integrated safety functions. The developed prototype offers a practical and cost-effective assistive solution that improves mobility, safety, and quality of life for visually impaired and elderly users.
Aromatic Light
(Dr. Emad Natsheh, 2025-09-20) Reem Abd Al Raheem Hasan; Farah Faisal Ahmad; Dr. Emad Natsheh
This project involves an automated unit for producing customized scented candles with the aim of simplifying and speeding up traditional craftsmanship methods. In addition to the increasing demand for decorative and calming candles, the proposed machine provides a practical solution for creating personalized handcrafted candles in an easy and efficient way. The system enables the user to select the number of molds (up to three at a time), the type of wax (two available options), colors (two color dyes), and scents (two fragrance options). The process begins by melting and blending the chosen wax with the selected color dye until the mixture is smooth and consistent. Afterward, the selected scent is added and mixed again to achieve the desired fragrance intensity. The final mixture is then poured into the molds. To accelerate the cooling and solidification process, a ventilation system is integrated to provide effective airflow around the molds. Unlike commercial machines designed for large-scale production, this project is tailored for individual users and small-scale businesses. Its customizable automation features allow users to experiment with various combinations of wax, colors, and scents while ensuring consistency and quality. The project provides a modern and flexible solution that supports both hobbyists and entrepreneurs interested in candle-making.
Bright path to learning
(Dr. Shareef Yaseen, 2026-01-27) Reem Abd Al Raheem Hasan; Farah Faisal Ahmad
This project aims to develop an intelligent mobile and web application that helps students organize their studies in an interactive and efficient way by integrating artificial intelligence with a modern and user-friendly interface. The application analyzes each student’s learning style to personalize their educational experience, whether visual, auditory, or kinesthetic. The system allows users to upload their study materials such as books, PDFs, or images, and automatically generates summaries, quizzes, and flashcards to enhance understanding and retention. It also provides an adaptive study plan that adjusts based on the student’s performance and available time, along with motivational quotes and Islamic reminders to maintain focus and positivity throughout the learning journey. The mobile version of the application will be built using React Native and Expo to ensure a smooth, responsive, and cross-platform user experience, while the web version will be developed using React.js for an intuitive browser-based interface. The Back-End will be developed using Node.js and Express.js, with MySQL as the main database for efficient and structured data management. The system will also be integrated with the OpenAI API to enable intelligent features such as automatic summarization, question generation, and personalized study planning. Additionally, the project includes an Administrator Dashboard for monitoring user activity, analyzing learning performance, and managing educational content effectively. This project combines artificial intelligence, smart organization, and motivational design to deliver a complete digital learning experience that empowers students to achieve their academic goals with confidence and efficiency.
HR Vision
(Dr. Abdalla Rashed, 2026-01-28) Aya Sawalha; Raheeq Qassrawi
HR vision system was designed and implemented to address the growing need for efficient and intelligent employee management at An-Najah National University, as it still depends on manual or semi-automated HR processes, which often lead to inefficiencies, errors and delays. The proposed system aims to automate and organize core employee management processes through an integrated web and mobile platforms supported by artificial intelligence features. The key components of the proposed system include a centralized human resource management platform that manages employee records, attendance, leave requests, exit permissions, and workload allocation. In addition, artificial intelligence techniques were employed to ensure fair and efficient distribution of workloads among teaching assistants. The system also incorporates an intelligent recommendation engine to support Heads of Departments (HODs) in assigning teaching assistants to laboratory sessions and course sections. Furthermore, a user-friendly interface provided to allow teaching assistants to easily submit and track their leave and exit requests. The system was developed using a multi-layered architecture. A web application was implemented using React.js, while a cross-platform mobile application was developed using React Native to support both Android and iOS devices. The backend was built using Node.js, with MySQL employed as the primary database management system. The system supports role-based access for Human Resources (HR), Heads of Departments (HODs), and Teaching Assistants (TAs). Core functionalities include attendance management, leave and exit requests, employee registration approval, department management, workload and section distribution, schedule creation, announcements, and meetings management. Additionally, intelligent features such as a chatbot, notification system, and real-time chat were integrated to enhance usability and communication. An artificial intelligence module based on a pre- trained Ollama model was incorporated to support system assistance, suggestions, and analytical operations. Although various HR management systems are available, many focus primarily on basic administrative tasks and lack effective integration between academic workload management and communication tools. This project distinguishes itself by providing a unified platform that combines HR operations, academic scheduling, intelligent assistance, and real-time communication, offering a more cohesive and practical solution tailored to the university environment.
BLOOM
(Dr. Sufyan Samara, 2026-01-27) Basmala Samaneh; Loaa Awayes
Bloom is a smart agriculture platform designed to help farmers manage their crops and access agricultural services in a simple and organized way. The project combines several important features in one system, including crop management, expert communication, AI- based assistance, and an online marketplace. Bloom is available as both a web application and a mobile application, which allows users to access the system anytime and from different devices. Through Bloom, farmers can create crop cases, upload images, receive guidance, and communicate with agricultural experts using a real-time messaging system. The platform also provides a marketplace where users can buy, sell, or rent agricultural products and tools. In addition, Bloom includes AI-supported features that help generate tasks and recommendations based on crop information and environmental conditions. The main goal of this project is to reduce the need for farmers to rely on multiple separate platforms and instead provide one integrated solution that supports daily farming activities. Bloom aims to improve access to reliable information, enhance communication between farmers and experts, and support better decision-making in agriculture using modern web and mobile technologies