المشاريع الواعدة

عنوان المشروع: Attend AI: Real-Time Face Recognition and Uniform Compliance Engine for Automated University Attendance Management

الوصف:
Attend AI is an intelligent university attendance management system that deploys three concurrent neural network models executing entirely within the web browser, achieving real-time student identity verification and uniform compliance detection without server-side GPU dependency. The system implements a TinyFaceDetector (SSD + MobileNet v1 backbone) for sub-100ms face localization, a 68-point facial landmark network for geometric alignment normalization, and a ResNet-based face recognition network generating 128-dimensional embedding vectors with Euclidean distance matching. A custom RGB color-space uniform compliance engine operates in parallel using face bounding box geometry — requiring zero additional neural network inference. Key innovations include: (1) client-side triple neural network inference eliminating cloud GPU costs, (2) dual-output single-pass detection combining identity and dress-code verification, (3) enrollment-aware attendance validation preventing cross-section fraud, and (4) a five-level RBAC architecture with 15 granular permissions. Evaluation results: face recognition accuracy 96.2% (F1=0.974), uniform compliance accuracy 91.8%, end-to-end latency under 200ms on standard consumer hardware. Built with Next.js 15, React 19, PostgreSQL (Neon), Prisma 6, and TensorFlow.js.

تاريخ رفع الملفات: 2026-06-26 06:44:43

عنوان المشروع: AI-Powered University Examination Timetabling

الوصف:
This project presents the design and implementation of an integrated university examination management system that automates exam scheduling, hall allocation, seating arrangement, and invigilator assignment within a unified framework. The scheduling problem is formulated as a constrained assignment problem and evaluated using a penalty-based objective function that distinguishes between mandatory hard constraints and quality-improving soft constraints. A Genetic Algorithm is employed for timetable generation, while a Greedy Algorithm is applied for hall allocation and seating distribution using an interleaving strategy to minimize adjacent seating of students from the same academic stage.

تاريخ رفع الملفات: 2026-07-05 10:54:32

عنوان المشروع: An Integrated Students Attendance System for Academic Institutions Powered by Artificial Intelligence Technologies

الوصف:
This project addresses a significant problem in the field of academic attendance management, where traditional methods are time-consuming, error-prone, and vulnerable to fraud. The proposed solution is based on a web-based intelligent attendance system that integrates real-time face recognition with comprehensive academic administration, aiming to automate the attendance process, enhance accuracy, and provide actionable insights for educators and administrators. The expected outcomes include a reduction in attendance processing time by over 80%, elimination of impersonation, generation of detailed absence reports with cumulative warnings, and a unified platform for managing students, courses, professors, and departments. The system supports multiple user roles (department heads, professors, registration staff, secretaries, and students) and offers bilingual interfaces, dark/light themes, and exportable analytics. By leveraging open-source technologies and modern web frameworks, this project delivers a scalable, cost-effective, and secure solution that can be readily deployed in universities and training institutions.

تاريخ رفع الملفات: 2026-07-05 20:13:15

عنوان المشروع: SETI Signal Analysis System: AI-Powered Extraterrestrial Signal Detection, Classification & Data Collection Platform

الوصف:
The SETI Signal Analysis System is the world's first Arabic-language AI-powered platform for radio frequency signal detection and classification, and the first structured scientific data collection tool purpose-built for SETI researchers in the Arab world. The system employs a Triple-CNN Ensemble (InceptionResNetV2 + ResNet50 + MobileNetV2, 85M+ parameters) trained on the Breakthrough Listen dataset, achieving 84.00% ± 1.13% mean classification accuracy across seven signal categories (95% CI: [83.00% — 85.57%]). Every signal analyzed is automatically archived in a structured SQLite database with full metadata — frequency, wavelength, confidence score, classification label, and ISO 8601 timestamp — enabling researchers to build longitudinal datasets for statistical analysis and peer-reviewed publication without writing a single line of code. A physics-based signal simulator enables dataset generation without radio telescope hardware, making structured SETI data collection accessible to any university with a laptop. Built with TensorFlow 2.x, FastAPI, Electron, React 18, and TypeScript. Supports SDG 4, SDG 9, SDG 10, and SDG 17.

تاريخ رفع الملفات: 2026-06-26 07:04:48

عنوان المشروع: SmartEdu: A Cloud-Based AI-Powered Educational Assistant for Interactive PDF Summarization

الوصف:
This project addresses a significant problem in the digital e-learning domain, specifically the passivity of traditional reading methods and the lack of real-time comprehension feedback for students. The proposed solution is based on a dual-platform system (Web and Flutter Mobile) integrated with advanced Large Language Models (LLMs) such as Gemini 2.5 Flash and Groq/Llama 3.3 70B , with the aim of transforming standard PDFs into interactive, responsive educational resources. The expected outcomes include a substantial improvement in student retention rate, automated personalized feedback, and streamlined lecture management for instructors.

تاريخ رفع الملفات: 2026-07-05 03:32:28

عنوان المشروع: CyberArena: A Hybrid Neuro-Symbolic AI Framework for Dynamic Cybersecurity Challenge Generation and Adaptive Training

الوصف:
وصف المشروع باللغه الانكليزيه
This paper is about CyberArena, a kind of training platform for cybersecurity that uses artificial intelligence. The problem is that most training platforms have the old challenges that do not change much so CyberArena tries to make things more realistic.Existing platforms like TryHackMe and HackTheBox have challenges that learners can solve once and then remember, which is not very helpful in the long run. CyberArena is different because it is a website that uses language models and Python to make new cybersecurity challenges whenever you need them. These challenges are in six areas: cryptography fixing code vulnerabilities looking at logs finding vulnerabilities, steganography and exploiting websites. The way it works is that the language models make the challenges and the Python modules handle the parts. This helps to avoid mistakes in the algorithm. CyberArena also has a mode where you can play against someone else in real time. It uses something called Server Sent Events. There is also a recommendation engine that suggests what you should do next a chatbot that helps you and a way to get a certificate that says you are good at cybersecurity. When we tested CyberArena it made 35 challenges in all six areas. Most of them were good to go from the start. It took 5 seconds to make each challenge. This is pretty fast. It means that CyberArena can make a lot of new challenges quickly. CyberArena is a CyberArena platform that can help people learn about cybersecurity in a realistic way with CyberArena being the key, to making it all work.

وصف المشروع باللغه العربية
تقدم هذه الورقة البحثية منصة CyberArena، وهي منصة تدريب هجينة للأمن السيبراني مدعومة بالذكاء الاصطناعي، تسعى لمعالجة ندرة التدريب الديناميكي، الذي غالبًا ما يكون غير متكرر، بحيث يمكنها محاكاة سيناريوهات الهجمات الواقعية. تعتمد الأدوات الحالية مثل TryHackMe وHackTheBox في الغالب على تحديات ثابتة مصممة يدويًا، حيث يحلها المتعلمون مرة واحدة ويحفظونها بشكل أساسي، مما يبطئ نمو مهاراتهم على المدى الطويل. تقوم فكرة CyberArena على منصة ويب متكاملة مدعومة بنماذج لغوية كبيرة (LLMs) ومحركات بايثون حتمية، تُنشئ تحديات جديدة للأمن السيبراني عند الطلب في ستة مجالات متخصصة: التشفير، وإصلاح ثغرات البرمجيات، وتحليل السجلات، واكتشاف الثغرات، وإخفاء المعلومات، واستغلال الويب. تم تقسيم البنية بطريقة هجينة، حيث يتم توليد المحتوى في جانب النماذج اللغوية الكبيرة، بينما يتم التعامل مع التنفيذ التقني بواسطة وحدات بايثون موثقة. يهدف هذا الفصل إلى تقليل مخاطر التشويش في الأجزاء الخوارزمية. يُقدّم CyberArena أيضًا وضعًا تنافسيًا فوريًا فرديًا، باستخدام أحداث الخادم المُرسلة (SSE)، بالإضافة إلى مُحرك توصيات ذكاء اصطناعي تكيفي، وروبوت دردشة مُرشد بالذكاء الاصطناعي، ونظام شهادات رقمية مُوثّقة. في تجربة توليد داخلية حيث تم إنتاج 35 تحديًا عبر المجالات الستة، حقق النظام نسبة تحقق من المحاولة الأولى بلغت 94.3%، ونسبة تكرار عناوين بلغت 2.9%، بمتوسط وقت توليد 5.17 ثانية لكل تحدٍ.

تاريخ رفع الملفات: 2026-07-05 09:54:30

عنوان المشروع: Design and Development of an AI-Powered Electronic System for Managing Faculty Promotions and Allowances Using ASP.NET Core and SQL Server

الوصف:
This project presents an integrated electronic system designed to automate and manage faculty promotions and annual allowances, developed utilizing ASP.NET Core and SQL Server. The core innovation lies in the deployment of a dual-layered artificial intelligence architecture. The first layer focuses on Intelligent Document Processing (IDP), where the system ingests uploaded letters of appreciation in PDF or image formats to verify document authenticity, extract the issuing authority, retrieve official metadata including document numbers and dates, and automatically identify the target employees. The second layer employs a rule-based inference engine that synthesizes these extracted inputs with institutional service records to proactively evaluate eligibility and predict promotion timelines with absolute precision. By enforcing strict programmatic constraints, the system eliminates administrative errors, prevents the duplication of appreciation rewards, and secures data privacy through a robust authorization matrix, offering a scalable framework for digital governance in higher education.

تاريخ رفع الملفات: 2026-07-03 12:06:23

عنوان المشروع: Smart Grader

الوصف:
This project presents "SmartGrader," an advanced software ecosystem designed to automate the grading of
handwritten student examinations using Generative Artificial Intelligence. The system integrates Optical
Character Recognition (OCR) with Large Language Models (LLMs) to semantically evaluate subjective answers
against established curricula and rubrics. Built using modern web technologies (React, Vite, Tailwind CSS) and
packaged as a standalone desktop application via the Electron framework, SmartGrader provides a seamless
"Human-in-the-Loop" interface. It drastically reduces the time educators spend on manual grading, mitigates
cognitive fatigue and implicit bias, and streamlines administrative workflows by automatically exporting
finalized results to Excel spreadsheets.

تاريخ رفع الملفات: 2026-07-05 22:33:19

عنوان المشروع: Enki.Ai) Community Platform)

الوصف:
Enki.ai is an AI-powered community and learning platform built specifically for engineering students in Iraq. It solves a real problem: students rely on scattered resources, informal chat groups, and foreign platforms that are not aligned with their curriculum, are often unavailable in their languages, and provide no access to personalized tutoring. Enki.ai brings tutoring, study tools, and community together into one coherent, localized system.
At its core is a curriculum-aware AI assistant that receives each student's university, college, year, and subjects, enabling it to deliver tailored, step-by-step explanations, answer engineering questions, and analyze uploaded images and documents. Surrounding it are eighteen integrated tools, including automatic exam and quiz generators, flashcards, a study planner, a GPA calculator based on the Iraqi grading system, a multi-language code lab supporting JavaScript, Python, C, C++, Java, MATLAB, and Arduino, a career roadmap generator, a CV builder, and a unique AI student-profile analyzer that produces a personalized learning profile and study strategy.
The platform also includes a full academic community: public and private study groups, discussion boards, a friend network, profile pages, and private direct messaging with file sharing. Enki.ai supports four languages — English, Arabic, Kurdish, and Turkish — is fully mobile-responsive, installable as a mobile app, and deployed live on a custom domain. It is built with React, Firebase, and a securely integrated large language model.

تاريخ رفع الملفات: 2026-06-26 11:47:15

عنوان المشروع: Design and Implementation of a Water Droplet Motion Illusion System Using the Stroboscopic Effect and Electronic Control Techniques

الوصف:
The B99 Water Drop Illusion is an innovative interdisciplinary project that transforms fundamental scientific principles into a compelling visual experience. By integrating fluid mechanics, optical physics, and embedded electronic control, the system creates the remarkable illusion of water droplets suspended in midair or moving upward against gravity. This effect is achieved by synchronizing a high-speed LED strobe with the periodic formation of water droplets produced by a precision micro-pump. The controlled interaction between pulsed illumination and droplet motion exploits the stroboscopic effect, altering the observer's perception of movement without changing the actual trajectory of the falling water. Beyond its aesthetic appeal, the project serves as a practical educational platform for demonstrating concepts such as motion perception, frequency synchronization, temporal sampling, and human visual persistence. Designed with simplicity, affordability, and portability in mind, the prototype is well suited for classrooms, engineering laboratories, science museums, and technology exhibitions. The B99 Water Drop Illusion demonstrates how the integration of engineering design and scientific visualization can transform abstract physical concepts into engaging, interactive learning experiences while inspiring innovation and creativity in science and engineering education.

تاريخ رفع الملفات: 2026-07-04 06:18:04

عنوان المشروع: AI-Integrated Interactive Virtual Chemistry Laboratory Using 3D Graphics Libraries

الوصف:
This project explores the development of an interactive virtual chemistry laboratory based on web-browser technologies using 3D graphics libraries (Three.js and GSAP) integrated with Artificial Intelligence to enhance simulation accuracy and educational guidance. The research aims to address traditional laboratory constraints such as high costs, safety risks, and geographic accessibility. Results indicate that the system achieves significant educational efficiency by enhancing conceptual understanding and reducing operational costs, while ensuring the highest standards of scientific integrity and originality in software design.

تاريخ رفع الملفات: 2026-07-05 19:44:44

عنوان المشروع: Design and Implementation of an AI-Powered Educational Support System

الوصف:
SmartEduAssistant is an AI-powered desktop application developed using C#, Windows Forms, and the OpenAI GPT API to support students in learning and self-study. It enables users to summarize lessons, generate questions, create personalized study plans, retrieve information from PDF documents, and assess their knowledge through AI-generated quizzes. By integrating multiple educational features into a single user-friendly platform, the system improves learning efficiency and simplifies the management of educational content.

تاريخ رفع الملفات: 2026-07-04 11:47:34