الجامعة التكنولوجية

Bipedal robots typically have heavy bodies and a simple gait. Still, they require precise design and expensive components, making it difficult for students to obtain a walking robot of suitable size on a limited budget. This project focuses on designing and manufacturing a 13 Degrees of Freedom bipedal robot with a smooth gait. The robot was designed in SolidWorks, and all parts were manufactured on an FDM printer using PLA to reduce weight and cost while maintaining quality. The robot was programmed in the C++ language using a finite-state machine model. We have also implemented an AI trained on a dataset of obstacles using image processing software to recognize and avoid them effectively. The results confirmed the proposed robot gait model, but some limitations exist due to the unavailability of tools, sensors, and motors.

The project builds an autonomous SCARA robotic arm chess coach that uses OpenCV vision and Stockfish AI to guide beginners on a physical board in real time. A dual-controller setup (Raspberry Pi + Arduino) drives NEMA 17 motors and a 12V electromagnet, while a spring‑loaded end-effector and magnetic board passively auto-center pieces for accurate, safe operation.

Iraq Jobs Portal is a real-time platform that collects job vacancies scattered across public messaging channels, converts them into clean structured records using artificial intelligence, and presents them through a single searchable website with a live labour-market analytics dashboard. In Iraq, a large and growing share of hiring happens on public Telegram channels rather than on traditional job boards. Vacancies are posted as free-form text, written in Iraqi Arabic dialect mixed with English, with no consistent structure for title, salary, location, or contact details. The same advertisement is frequently reposted across many channels. A job seeker who wants full coverage must follow dozens of channels and read every message by hand. Iraq Jobs Portal solves this by continuously monitoring more than one hundred channels, extracting structured job data from each post automatically, removing duplicates, standardizing salaries and locations, and exposing everything through fast fuzzy search and rich filters. The result is a single, trustworthy, searchable view of the Iraqi job market, backed by analytics that reveal hiring trends by sector, occupation, governorate, and salary band.

This project addresses a significant problem in Farming, where water waste is at all times high, especially in Iraq. The proposed solution is based on a hardware system that consists of a temperature sensor, humidity sensor, waterflow sensor, and rain sensor. As well as a smart software system and application that gets direct live information from the soil activity via the sensors, and decides when to water the crops and how much water to spend, with the aim of lowering water waste. Additionally, the application has a smart AI assistant that is trained on Iraqi climate. The expected outcomes include, simplifying the farming process for farmers, especially amateurs. On the other hand, it will in high hopes help reduce water waste by up to 70% when it comes to the farming industry.

This project addresses the lack of affordable, advanced interactive robot platforms inside university laboratories for engineering education. The proposed solution is based on an integrated laboratory humanoid robot head with audio and visual capabilities, fabricated through 3D printing technology. The system operates on a distributed architecture that links a main computer for artificial intelligence processing and microcontrollers for sending motor control and sensor signals. This practical framework was developed to establish a reliable testbed for evaluating and testing various artificial intelligence models within university laboratories for scientific research purposes and enhancing students' skills, with the potential for future enhancement and wider applications. The results achieved within our utilized software environment include real-time face and object tracking, emotion recognition, face saving, and interactive dialogue management, while maintaining a stable and optimized system response latency during dialogue coordination. يعالج هذا المشروع نقص منصات الروبوتات التفاعلية المتقدمة وميسورة التكلفة داخل المختبرات الجامعية للتعليم الهندسي. ويستند الحل المقترح إلى رأس روبوت بشري مختبري متكامل ذي قدرات سمعية وبصرية، مصنع عبر تقنية الطباعة ثلاثية الأبعاد. يعمل النظام بناءً على بنية نظام موزعة تربط بين كمبيوتر رئيسي لمعالجة الذكاء الاصطناعي ومتحكمات لإرسال إشارات تحكم بالمحركات والحساسات. تم تطوير هذا الإطار العملي لتأسيس بيئة اختبار موثوقة لتقييم واختبار مختلف نماذج الذكاء الاصطناعي داخل المختبرات الجامعية لأغراض البحث العلمي وتطوير مهارات الطلبة، مع إمكانية تطبيقه مستقبلاً لمجالات أوسع. وتشمل النتائج المحققة في برنامجنا المستخدم تتبع الوجوه والأجسام في الوقت الفعلي، وإدراك العواطف، وحفظ الوجه، وإدارة الحوار التفاعلي، مع الحفاظ على زمن استجابة مستقر ومحسن للنظام أثناء تنسيق الحوار.

The Magical Math World is a fun and interactive way to teach children math. It's a computer program designed for children aged 6 to 12. The problem is that children often get bored with math, and this program aims to solve that. It makes learning math more like a game, with different difficulty levels that increase as their skills improve. They can even earn rewards and track their progress in real time. The program also has a special mode that shows them how to solve math problems in a fun and interactive way. Developed using the Python programming language, it has a special database that records each user's progress. This means that multiple children can use the program, and it will remember each child's last point. The program also provides a safe way to perform calculations, and it can play sounds on different types of computers.

This project addresses critical challenges in modern healthcare by overcoming the fragmentation of medical services and patient data. The system features an intelligent blood donation management platform that rapidly identifies compatible blood donors, replacing traditional and time-consuming donor search methods during emergencies. It also integrates an AI-powered virtual doctor that conducts an initial assessment by asking patients symptom-based questions to determine the severity of their condition. Based on this evaluation, the system either schedules a remote consultation with a healthcare professional for non-critical cases or directs patients requiring urgent care to the nearest emergency department. This AI-assisted clinical triage process optimizes healthcare resource utilization, reduces unnecessary hospital visits, and accelerates access to appropriate medical care. The proposed system resulte provide an efficient, integrated, and patient-centered healthcare system that improves service coordination, enhances emergency response, reduces mortality, and ultimately contributes to better public health outcomes.

Manual date palm inspection is costly, slow, and physically dangerous. This paper presents PALMY, a UAV-based system leveraging a fine-tuned vision-language model (Qwen3-VL-2B-Instruct) for automated aerial disease detection. The key innovation is a self-correcting annotation pipeline that enables low-cost dataset generation, coupled with a VLM architecture that replaces black-box CNN labels with structured natural-language diagnostic reports. Using LoRA (r = 8) on a 4-bit quantized base model, PALMY was fine-tuned for 30 steps (~5 epochs) on free-tier cloud hardware. Training loss converged to 0.761 from an initial 4.64, an 83.6% reduction, across 11 target classes spanning diseases, pests, nutrient deficiencies, and healthy status. The system outputs Excel reports with severity, urgency, and treatment recommendations. Validation with government officials and farmers confirms PALMY's practical agricultural impact. As a proof-of-concept, PALMY Phase 1 demonstrates pipeline feasibility rather than production readiness, with full-scale validation scoped to future work.

Voltage instability can damage electrical equipment and reduce power system reliability. This paper presents SafetyX IoT, an AI-assisted Internet of Things (IoT) system for smart electrical voltage monitoring and protection. The system uses an ESP32 microcontroller and a ZMPT101B voltage sensor to monitor AC voltage and automatically disconnect the load during abnormal conditions using a relay. Voltage data are synchronized with Firebase Realtime Database through the REST API and monitored via an Android application. The application integrates a Grok-powered AI assistant that analyzes system data, explains abnormal events, answers user questions, and provides troubleshooting guidance. Experimental results demonstrated reliable monitoring, automated protection, and stable cloud synchronization.

حقول الحنطة الذكية والمستدامة في العراق بأستخدام نظام الروبوت والطائرة المسيرة الذكي (AgriGuard AI) يتناول هذا المشروع مشكلةً جوهريةً في مجال الزراعة الدقيقة والاستدامة البيئية. ويستند الحل المقترح إلى نظام روبوتي هجين متكامل )طائرة مسيرة وروبوت أرضي( يعتمد على حوسبة الحافة، ودمج مستشعرات متطورة تنغرس فيزيائيا للفحص المباشر لعمق التربة، والخرائط الجوية الذكية باستخدام YOLOv8-nano ، المربوطة بتطبيق أندرويد منخفض زمن الاستجابة. يهدف هذا المشروع بشكل رئيسي إلى تأسيس منظومة تحكم ذكية مغلقة تقوم بتحليل بيانات الرطوبة والملوحة الناتجة عن غرس الحساسات لتحديد وإضافة المقدار الدقيق الذي يحتاجه النبات من مياه أو أسمدة أو معالجات كيميائية مستهدفة. وتشمل النتائج المتوقعة خفضا كبيراً في هدر الموارد وتقليل استخدام المواد الكيمياوية مما يقلل التأثيرات البيئية، واستخراج قراءات مباشرة وعالية الدقة لشبكة الجذور الكيميائية عبر ناقل Modbus RS485 بنسبة خطأ أقل من 2%، وتحقيق مرونة تشغيلية عالية للأنظمة تحت درجات حرارة ميدانية تتجاوز 50 درجة مئوية. اثبتت النتائج المستحصلة امكانية التطبيق الصناعي في العراق لتحقيق الأمن الغذائي المستدام بتكنولوجيا الذكاء الأصطناعي الصديق للبيئة وبأقل التكاليف .

Smart Park is an AI-based smart parking management system that automates vehicle access using Automatic Number Plate Recognition (ANPR), Optical Character Recognition (OCR), and ESP32 controllers. The system enables users to reserve parking spaces in advance, verifies vehicle authorization automatically, and controls the entrance gate and smart ground barrier without human intervention. In addition, a solar-powered energy system supports sustainable operation.

في هذا المشروع، تم تصميم نظام ري ذكي يعمل بالطاقة الشمسية لمعالجة المشكلات الأساسية المتعلقة بري النباتات ومراقبة نموها، وذلك بدمج العديد من الأدوات التكنولوجية مثل الطاقة المتجددة والتعلم الآلي وغيرها لتحسين كفاءة الري وتقليل هدر المياه. يستخدم النظام المقترح مستشعرات LDR لتتبع ضوء الشمس وتحديد الاتجاه الدقيق للألواح الشمسية تلقائيًا عبر محرك مؤازر لزيادة الاستفادة من الطاقة الشمسية إلى أقصى حد. ولضمان إمداد طاقة مستقر، تم استخدام وحدة إدارة طاقة تعتمد على منظم LM2596 ووحدة شحن TP4056. تُعد المراقبة المستمرة للتربة من أهم العوامل في التحكم بتدفق المياه، مما يضمن ضخ المياه فقط عند حاجة النبات إليها. في الوقت نفسه، تُرسل وحدة ESP32 بيانات المستشعرات في الوقت الفعلي إلى تطبيق الهاتف المحمول، بما في ذلك حالة البطارية ومستوى المياه ورطوبة التربة. تُحلل المستشعرات بيانات التغذية الراجعة للتنبؤ بالوقت الأمثل لعملية الري التالية باستخدام نموذج التعلم الآلي، وبالتالي إدارة المياه بطريقة ذكية ومتكيفة. تُظهر النتائج التجريبية أن النظام المقترح يوفر حلاً اقتصاديًا للطاقة بالإضافة إلى الاستقلالية والاستدامة، مما يجعله مناسبًا للزراعة في المناطق النائية والتطبيقات الزراعية.