Promising Projects

This page lists officially approved projects in the competition, available for companies, institutions, and incubators to explore for incubation, support, or partnership opportunities.

For incubation or partnership opportunities: contact the supervisor or team members using the contact details provided in each project.
Results: 603 — Page: 16/51
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Alpha team

University: جامعة نينوى — نينوى (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0815
Supervisor حسين محمد حسين
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: Non-Intrusive Machine Monitoring and Diagnostics Using a Triple-Branch 1D-CNN
Description:
PROsense is non-Intrusive machine monitoring and diagnostic system designed for industrial predictive maintenance, aiming to reduce costly and unexpected equipment downtime in manufacturing environments. Instead of relying on intrusive and expensive multi-sensor installations, it analyzes only electrical current signals captured through SCT-013 current transformers. A STM32 microcontroller converts the analog signal into 2500hz current streams and transmits them to a Raspberry Pi for further processing.

During the data collection phase, ESP32-based tags attached to sub-motors are used as automatic labeling agents. These tags capture real-time on/off transitions of individual machine components and are used exclusively to synchronize and label operational states for supervised learning. Once training is completed, the tagging system is removed, leaving only the core system inference active in deployment.

The intelligence layer is powered by a triple-branch 1D CNN that extracts time-domain waveforms, frequency-domain harmonics, and sequential behavior using sliding windows. This multi-representation learning significantly improves robustness against noise and load variations while achieving around ~94% accuracy in real industrial conditions. A stage-aware 3-sigma anomaly detection layer further monitors deviations within each operational state, enabling early fault detection and allowing the system to prevent failures before they happen. With a 1-second inference cycle, the system delivers reliable, real-time monitoring suitable for industrial deployment, reducing downtime, maintenance costs, and production losses.
Uploaded At: 2026-07-05 01:08:29
👥 Team Members (3)
عبدالسلام عبود شهاب
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
فراس عبدالله خليل
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
محمد عطيه خلف
✉️ [email protected]
🎯 Role: Programmer
🎓 Academic Level: Bachelor

Robotic team

University: جامعة نينوى — نينوى (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0824
Supervisor سحر لازم قدوري
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ No images uploaded.
📌 Project Details
Project Title: SmartVision Robotic Arm: Material and Color-Based Object Sorting Using Arduino Mega
Description:
This project aims to develop an intelligent robotic arm capable of sorting objects by color and material, overcoming the limitations of traditional systems that rely on a single sensor or slow manual sorting. The solution integrates mechanical, electronic, and software components into a unified system, in which sensor decisions are translated into precise movements via servo motors.
Uploaded At: 2026-07-03 15:22:55
👥 Team Members (3)
خليل بسام خليل
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
محمد حمزة فتخان
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
مصطفى ميسر عطية
✉️ [email protected]
🎯 Role: Electronics
🎓 Academic Level: Bachelor

Clover

University: جامعة تكنولوجيا المعلومات والاتصالات — بغداد (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0837
Supervisor أ.د.احمد صباح احمد
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: Predictive Maintenance System for Agricultural Machinery
Description:
This project proposes an intelligent predictive maintenance framework for industrial machinery and demonstrates its effectiveness through a case study based on agricultural equipment operating in demanding environmental conditions. The framework combines Internet of Things (IoT) sensing technologies with machine learning to enable condition-based maintenance and the early detection of equipment faults. An Arduino-based prototype equipped with temperature, vibration, and engine RPM sensors was developed to continuously monitor key operating parameters. The collected sensor data, together with an open-source dataset, were analyzed using a Random Forest classification model to identify potential faults before they progressed into critical failures. To improve system usability, the framework incorporates an intuitive diagnostic interface that converts complex analytical results into clear and practical maintenance recommendations, making the system accessible even to users with limited technical expertise.
Experimental evaluation demonstrated that the proposed framework achieved an overall fault detection accuracy of 92.11%. The results indicate that the system can effectively support predictive maintenance by reducing maintenance costs, minimizing unplanned downtime, extending equipment service life, and improving operational efficiency. Although the framework was validated using agricultural machinery as the primary case study, its architecture is sufficiently flexible to be adapted for a wide range of industrial machinery and predictive maintenance applications.
Uploaded At: 2026-07-04 05:47:22
👥 Team Members (3)
ايناس عامر كريم محيسن
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
حسين عقيل صبري
✉️ [email protected]
🎯 Role: Electronics
🎓 Academic Level: Bachelor
مصطفى ضياء عبد الامير
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor

Neuropolis

University: جامعة الكرخ للعلوم — بغداد (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0845
Supervisor د. احمد عدنان هادي
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ No images uploaded.
📌 Project Details
Project Title: Intelligent Monitoring System for Predictive Maintenance and Fault Detection in Network Systems
Description:
This project addresses an important problem in the field of (Networks Systems) The proposed solution is based on (the use of artificial intelligence techniques), specifically the use of machine learning models, with the aim of (predicting failures before they occur) The project aims to improve sudden network stops that negatively affect network systems by collecting and analysing data to detect abnormal patterns that precede the occurrence of failure. The expected results include early warning alerts are sent to operators minutes before a breakdown occurs, the probability of failure in real time for each monitoring network device, case severity classification: Normal / Degraded / Critical, record pre-fail patterns over time, allowing the model to continue, redirect data traffic or restart the service before the failure is complete.
Uploaded At: 2026-07-05 02:38:26
👥 Team Members (5)
حسن سامر يوسف
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
عبدالرحمن علاء الدين حسن علي
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
عبدالرحمن ماجد عبدالرحمن
✉️ [email protected]
🎯 Role: Electronics
🎓 Academic Level: Bachelor
محمد عبدالستار كامل
✉️ [email protected]
🎯 Role: Programmer
🎓 Academic Level: Bachelor
يوسف عباس غازي
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor

فريق القمة

University: الجامعة التقنية الشمالية — نينوى (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0869
Supervisor د.زكي مجيد عبدالله
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ No images uploaded.
📌 Project Details
Project Title: CNC Pin Plotter جهاز الرسم بالقلم
Description:
يعتبر جهاز التحكم الرقمي با استخدام الحاسوب ) CNC-Computer Numerical Control )
من اهم التقنيات الحديثة المستخدمة في مجالات الصناعة و الهندسة حيث يتيح التحكم بحركة
الادوات الميكانيكية
بدقة عالية بااستخدام اوامر رقمية يتم ارسالها من الحاسوب الى وحدة التحكم . تعتمد هذة
الاجهزة على تحويل التعليمات
البرمجية المعروفة باسم G-Code الى حر كات ميكانيكية دقيقة على محاور مختلفة ممايسمح
بتنفيذ عمليا ت مثل
الرسم ,الحفر ,القطع و الكتابة .
Uploaded At: 2026-07-05 10:16:21
👥 Team Members (5)
حسن عبدالستار حسن
✉️ [email protected]
🎯 Role: Programmer
🎓 Academic Level: Bachelor
روّاد الميكاترونيكس
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
عامر محمود خلف
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
غزوان محمد عبيد محيسن
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
مثنى صالح علاوي
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor

Zero cool

University: الجامعة التقنية الشمالية — نينوى (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0872
Supervisor د. ايناس فائق عزيز
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: ROBOSPLOIT STORM
Description:
The project aims to design and implement a secure simulation environment for studying cybersecurity in industrial robots and power plant systems, using Docker, ROS, and CuppeliaSim technologies. A virtual laboratory was created, incorporating several network services and a security assessment station within an isolated network, enabling the simulation of an industrial environment and the ethical and secure conduct of security studies.
Uploaded At: 2026-07-05 13:28:40
👥 Team Members (4)
أحمد أياد أحمد
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
احمد رياض احمد خلف عداي
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
راڤين مؤيد زوراو
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
مؤمن محمد عمر
✉️ [email protected]
🎯 Role: Programmer
🎓 Academic Level: Bachelor

مهندسو الاوتار

University: الجامعة التقنية الشمالية — نينوى (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0888
Supervisor مفاز يحيى ضمرة
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: GeoString An End-to-End Automated String Art Generation and Physical Fabrication Platform Based on Greedy Image Processing and Arduino-Microcontroller
Description:
This paper presents a design and implementation of Geostring, an end-to-end automated string-art platform that converts any digital photograph into a physical artwork composed of a single continuous thread wound around a circular nail frame. The system comprises three integrated components: an interactive web-based 2D generator employing a greedy chord-selection algorithm in polar coordinates, a live Three.js-based 3D mechanical simulator, and an AI-assisted parameter tuning assistant. The physical drawing machine is built around an Arduino UNO R3 running GRBL firmware, two NEMA 17 stepper motors driven by TMC2225 silent drivers, and a GT2 belt-driven linear arm operating over a 290 mm rotating disc. The greedy algorithm iteratively selects the nail-to-nail chord that maximally reduces the residual image darkness, producing sequences of up to 8,000 chords. Experimental evaluation confirms a disc positioning accuracy of 0.08° mean error, thread-shuttle repeatability of ±0.15 mm, and successful autonomous artwork production. The platform bridges computational art with physical mechatronic fabrication, providing an open, modular, and affordable system applicable to engineering education, creative technology, and intelligent automation research.project addresses a significant problem in (mention the field or domain). The proposed solution is based on (briefly describe the idea or technology) with the aim of (state the main objective). The expected outcomes include (summarize the anticipated results or impact).
Uploaded At: 2026-07-06 04:28:39
👥 Team Members (4)
ثابت حسان سالم
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
سالي احمد سعيد
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
عبد الله عمار علي
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
كوكب معن صالح
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor

فريق المعهد التقني النجف

University: جامعة الفرات الاوسط التقنية — النجف (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0908
Supervisor أ.م.د. احمد فاهم البغدادي
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: Smart Aiming
Description:
منظومة توجيه وتتبع ذكي ثنائية المحاور (Yaw/Pitch) مصممة بهيكل سداسي مطبوع ثلاثي الأبعاد لتقليل القصور الذاتي والاهتزاز. يعتمد النظام على معمارية معالجة متوازية تدمج بين خوارزميات الذكاء الاصطناعي (YOLOv8 & ByteTrack) لاكتشاف وتتبع الأشخاص لحظياً، متكاملاً مع حلقة تحكم مغلقة (P-Controller) وفلاتر رقمية متطورة لضمان استجابة فيزيائية فائقة النعومة ودون ارتعاش ميكانيكي.
Uploaded At: 2026-07-06 01:48:54
👥 Team Members (3)
مجتبى محمد علي عطية
✉️ [email protected]
🎯 Role: Electronics
🎓 Academic Level: Bachelor
مرتضى علي كاظم
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
ياسر ازهر جبار
✉️ [email protected]
🎯 Role: AI/Control
🎓 Academic Level: Bachelor

فريق قوة الاندماج

University: الجامعة التقنية الجنوبية — البصرة (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0914
Supervisor م.م. عبدالله عبدالعباس ناهي
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: Development of an Autonomous Gas Leak Detection System Using Reinforcement Learning with an Interactive Dashboard
Description:
1. Problem Statement
Manual industrial gas leak inspection exposes human operators to severe health risks in hazardous environments. Existing static sensor networks fail to pinpoint precise leak locations, while traditional robotic systems struggle with dynamic obstacles and high-latency telemetry.

2. Proposed Solution / Innovation
An autonomous AI-driven robotic system that localizes gas leaks in real-time. Our core innovation is a "headless" execution mode that disables visual rendering to accelerate reinforcement learning (Q-Learning) training speeds by over 10x, ensuring rapid environmental adaptation.

3. Method / Implementation
The agent processes sensory inputs through a persistent Q-table to determine optimal navigation paths. We utilize a decoupled architecture where an AI engine handles the logic, while a Flask-based backend asynchronously streams telemetry data to a live web dashboard.

4. Key Components: HW/SW/AIAI/SW: Python-based Q-Learning engine and Pygame physics simulation.
Sensory Framework: 2-sensor array calculating live concentration gradients (∇C).
Backend/UI: Flask micro-framework and HTML5/JS frontend for real-time visualization.
System Utilities: Automated background modules for crash-resilient data logging.

5. Expected Results / Impact
The system achieves precise gas source localization in complex layouts. It drastically minimizes human occupational exposure to toxic environments and provides a scalable, low-latency monitoring solution for industrial safety.


6. What the 60s video demonstrates
The video demonstrates the agent’s autonomous navigation in a complex environment, showing how it successfully reaches the gas source while bypassing obstacles. It highlights the real-time synchronization between the AI simulation and the web dashboard, where performance metrics and concentration gradients are streamed and updated instantly without any latency.
Uploaded At: 2026-06-30 17:16:56
👥 Team Members (4)
حسن عصام حسن
✉️ [email protected]
🎯 Role: Programmer
🎓 Academic Level: Bachelor
ذوالفقار إيثار يوسف
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
مريم عامر قدوري مهدي
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
هدى عبد الكريم نجم
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor

فريق Argyron

University: الجامعة التقنية الوسطى — بغداد (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0919
Supervisor د. امال غازي حمد
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: Smart Argyron Al Security System
Description:
This project aims to meet the increasingly demands of intelligent and automated visual surveillance to accurately identify people and obtain useful demographic information in real time. The proposed solution uses a high accuracy deep-learning face-recognition engine with a facial-landmark analysis module to detect faces, recognize known identities and estimate gender of the faces detected, which is achieved by a temporal voting mechanism to resist occasional misclassification. It continually streams its annotated video output to a lightweight Web interface, archives events into a cloud-hosted real-time database, records video on demand, and integrates the visual stream with a complementary radar-based motion display, providing a broader situational awareness than just behind the camera. The goal is to provide a consistent, low latency and scalable monitoring solution for access control and security applications. Experimental operation shows that the recognition is accurate, gender estimation is stable, the system works smoothly in real-time, and the three parts of the visual, cloud and radar can be integrated.
Uploaded At: 2026-07-03 11:42:17
👥 Team Members (3)
حوراء علاء لفته
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
طيبة بشار عبداللطيف
✉️ [email protected]
🎯 Role: Electronics
🎓 Academic Level: Bachelor
علي اسامه عبد الكريم
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor

فريق المخزن الذكي

University: الجامعة التقنية الوسطى — بغداد (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0924
Supervisor فائز موسى لهمود
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ 3 Images
📌 Project Details
Project Title: المخزن الذكي
Description:
يهدف هذا المشروع إلى تطوير أنظمة إدارة مخازن المواد الغذائية الجافة الحالية، والتي تعاني من عمليات فحص يدوية للمخزون، وتأخر اكتشاف ظروف التخزين غير المناسبة، وعدم دقة سجلات المخزون. يعتمد الحل المقترح على دمج تقنيات إنترنت الأشياء، والمراقبة القائمة على أجهزة الاستشعار، والتحكم الآلي في المرحلات، والتحليل التنبؤي باستخدام الشبكات العصبية الاصطناعية. يتميز النظام بقدرته على مراقبة ظروف التخزين وحالة المخزون من خلال استشعار البيئة والمسافة/المستوى. تتم معالجة البيانات المُجمعة بواسطة وحدة تحكم دقيقة تُشغّل مروحة تهوية عند تجاوز عتبات تحكم محددة مسبقًا. يحتوي النموذج الأولي على وحدة تحكم قائمة على أردوينو، ومستشعر فوق صوتي، ووحدة مرحل، ومروحة تيار مستمر، وبطارية قابلة للشحن، ومحول تيار مستمر قابل للتعديل للمراقبة الآنية والاستجابة التلقائية. يتمثل الهدف الرئيسي في زيادة وضوح العمليات، وتقليل جهود الفحص اليدوي، وإنشاء أساس قابل للتطوير لقياس المخزون والتنبؤ بالطلب المستقبلي. أثبتت نتائج التجربة نجاح تشغيل المرحل المُفعّل بواسطة المستشعر، والتشغيل التلقائي للمروحة، واستقرار مخرجات الجهد المنظم، والإشارة السريعة إلى سعة التخزين. تشمل التأثيرات المتوقعة تحسين موثوقية المراقبة، وتقليل وقت الاستجابة للتغيرات في ظروف التخزين، وخفض تكاليف التشغيل، والتوسع المستقبلي نحو الاتصال السحابي، والاستشعار البيئي، وتسجيل البيانات، والتنبؤ بالمخزون القائم على الشبكات العصبية الاصطناعية.
Uploaded At: 2026-06-30 18:32:07
👥 Team Members (3)
ايه اسامه محمد عجيل
✉️ [email protected]
🎯 Role: Other
🎓 Academic Level: Bachelor
سجاد ودود قاسم محمد
✉️ [email protected]
🎯 Role: Electronics
🎓 Academic Level: Bachelor
سيف كريم كاظم محمد
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor

فريق التطور

University: كلية الامام الكاظم للعلوم الاسلامية الجامعة - Imam Alkadhim University College — بغداد (حكومية)
Track: Industrial Robotics & Automation
✅ Approved
Team Code NURAI2026-0944
Supervisor م.م. حسن نعمان مسلم
✉️ [email protected]
Registered At 2026-04-22 11:16:54
📄 PDF 🎥 Video 🖼️ No images uploaded.
📌 Project Details
Project Title: Arduino-Based Ultrasonic Radar for Robotic Applications
Description:
This work presents the design and implementation of a low-cost Arduino-based ultrasonic radar prototype for short-range object detection and robotic defense applications, where the low-cost electronic components that used were: Arduino Uno, ultrasonic sensor, servo motor, buzzer, and laser module, are used in the system. The system emits ultrasonic waves through the sensor to measure the distance to objects, and the sensor is rotated by the servo motor to scan a specific area. When a target is detected within a range of 40 cm, the system activates warning signals, including a laser beam and an audible alert through the buzzer. The data is also displayed graphically using the Processing software, allowing users to easily track detected targets. The system is suitable for educational applications and as a prototype for smart defense technologies.
Uploaded At: 2026-06-29 19:16:24
👥 Team Members (3)
علي عبدالله فاضل طاهر ، محمود عدنان عبد حزيم
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
محمود عدنان عبد حزيم
✉️ [email protected]
🎯 Role: Programmer
🎓 Academic Level: Bachelor
مصطفى مؤيد حسين
✉️ [email protected]
🎯 Role: Leader
🎓 Academic Level: Bachelor
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