Promising Projects

Project Title: Enhanced Morphological Grasping for Fruit Harvesting: Integrating Directional Nano-Adhesion with Logarithmic Spiral Soft Robots

Description:
This project addresses a significant problem in the field of soft robotics and automated manipulation for Fruit Harvesting, which is the unstable grasping of smooth or low-friction objects. The proposed solution is based on a cable-driven logarithmic spiral soft robot (SpiRob) integrated with 3D-printed flexible contact membranes and reusable directional nano-adhesion tape, with the aim of maximizing payload stability without requiring excessive mechanical clamping force. The expected outcomes include a substantial increase in grasping reliability for 3-arm robotic arrays, allowing the system to securely hold smooth geometries by combining morphological wrapping with physical van der Waals adhesion.

Uploaded At: 2026-07-05 18:56:07

Project Title: Adaptive Smart Shading and Irrigation System

Description:
يقدم هذا المشروع نظامًا ذكيًا وآليًا للتظليل والري، صُمم بهدف تحسين ظروف التظليل والري لأنواع مختلفة من النباتات. يعتمد النظام على Arduino Mega لجمع بيانات المستشعرات في الوقت الحقيقي (رطوبة التربة، ودرجة حرارة البيئة، والرطوبة، والإشعاع الشمسي)، وRaspberry Pi لتنفيذ مهام الحوسبة عالية المستوى. ولتحقيق إدارة دقيقة للموارد، تم تطبيق تقنيات الرؤية الحاسوبية، حيث يتم توصيل كاميرا USB بجهاز Raspberry Pi للتعرف على نوع النبات وحالته، مما يسمح للنظام بتكييف عملياته وفقًا لمتطلبات كل فئة من النباتات. يعالج متحكم المنطق الضبابي (Fuzzy Logic Controller - FLC) البيانات الواردة من المستشعرات لاتخاذ قرارات ذكية ومناسبة بشأن عمليتي التظليل والري. ويتم ضبط التظليل بشكل ديناميكي باستخدام محرك (Servo Motor) يقوم بتدوير طبقة مستقطبة للتحكم في شدة الضوء، بينما يُستخدم نظام تحكم ذي حلقة مغلقة (Closed-Loop Control System) في نظام الري للتحكم في مضخة المياه. علاوةً على ذلك، يتيح النظام إمكانية المراقبة عن بُعد عبر واجهة ويب، مما يسهل متابعة حالته. ومن خلال دمج الرؤية الحاسوبية المعتمدة على الشبكات العصبية الالتفافية (Convolutional Neural Network - CNN) مع التحكم بالمنطق الضبابي والتغذية الراجعة ذات الحلقة المغلقة، يضمن النظام المقترح توفير الظروف المثلى لنمو النباتات، وتقليل هدر المياه، ومنع إجهاد الضوء، مما يوفر حلاً قويًا وقابلًا للتوسع في مجال الزراعة الذكية.

Uploaded At: 2026-07-04 19:00:14

Project Title: Multi-Task Learning via Hybrid Quantum-Classical Neural Networks: A Novel Approach for Advanced Agricultural Decision Support

Description:
Two essential ways that our proposed frame work differs from previous studies This research, first, introduces a custom-built Variational Quantum Circuit (VQC) to encode multi-dimensional tabular field data (7 different environmental features), as opposed to pixel data like the majority of quantum deep learning literature. In contrast to prior works which are limited to single-objective classification (e.g., crop type), our multi-task hybrid topology enables simultaneous prediction of both categorical (crop type) and continuous (harvest days and yield) variables. Queuing into a logical framework We observed that classical models plateaued with regards to maximisation of the prediction performance: Accuracy approaches 90% and remains unchanged afterwards, whereas our proposed quantum-enhanced model broke through this barrier by establishing a Coefficient of Determination (R2) of 0.995 thus representing a whole new frontier in precision agriculture

Uploaded At: 2026-07-05 05:42:44

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Project Title: VARICOSE VEIN DIAGNOSIS SYSTEM AND THERAPY

Description:
The proposed system is based on a closed-loop
architecture that integrates real-time physiological sensing with automated therapeutic response in a wearable
device. Infrared and temperature sensing techniques are employed to detect blood pooling and localized
inflammation associated with venous insufficiency.

Uploaded At: 2026-07-05 03:05:57

Project Title: From Soil to Sky — An AI-Powered Fusion System for Smart Irrigation and Crop Protection

Description:
Our system is an AI-assisted precision irrigation drone system addressing inefficient water usage and delayed crop stress detection in agriculture. Before each mission, Sentinel-2 satellite imagery is processed to generate NDVI-based heatmaps classifying field zones as dry, medium, or healthy. During flight, a drone equipped with a live camera stream feeds video to a ground-based AI model that detects crop health status, identifies plant diseases at close range, and flags fire or smoke hazards, triggering an automatic alert call and mission abort if detected. A human operator then manually activates a relay-controlled pump to irrigate only flagged zones. Expected outcomes include reduced water waste, earlier crop stress and disease detection, and an integrated fire safety mechanism.

Uploaded At: 2026-07-05 04:03:05

Project Title: Specter

Description:
يتناول هذا المشروع قيوداً حرجة في مجال الزراعة الدقيقة الحالية، وتحديداً غياب الحلول الأرضية القادرة على تصوير الأسطح السفلية لأوراق النباتات (abaxial surfaces) والحاجة الماسة لمنع انضغاط التربة. ونقترح في هذا العمل نظام Specter، وهو روبوت سداسي الأرجل (hexapod) ذاتي القيادة صُمم خصيصاً للكشف البصري عن أمراض النباتات ورسم خرائط ثلاثية الأبعاد لرطوبة التربة. يجمع نهجنا بين آلية الحركة المحاكاة حيوياً (biomimetic locomotion) لضمان الملاحة المستقرة والتنقل الآمن، والتشخيص الفوري (Real-time) المبني على الذكاء الاصطناعي. وتظهر النتائج التجريبية دقة تشخيصية عالية جداً (mAP50 تبلغ 0.995) ودقة فائقة في الخرائط المكانية، مما يقدم بديلاً متفوقاً وموفراً للطاقة مقارنة بالمنصات الجوية (الدرون) والأنظمة القائمة على العجلات في البيئات الزراعية الكثيفة وغير المنظمة.

Uploaded At: 2026-07-02 15:21:45

Project Title: An Image Processing Application for Merged Stains Separation on Water Sensitive Papers

Description:
This project addresses a significant problem in agriculture, particularly in pesticide application process. The proposed solution is based on developing an application of image processing technology with the aim of separation of merged stains that occurs in water sensitive papers (WSP). The expected outcomes include that the application will successfully address this problem and will report correct results of the pesticide application parameters that measured using WSP.

Uploaded At: 2026-06-26 15:42:29

Project Title: Tracking and Counting Weeds and Estimating the Vehicle Speed using YOLO Algorithm

Description:
This application is created for real-time weed, and the main crop tracking and counting to control weed precisely and to optimize herbicide application by sparying only the unfavorable weeds. Moreover, tracking the main crop was used to estimate the vehicle speed when the interplant spaces are fixed and known. This application is based on artificial intelligence especially YOLO algorithm, computer vision, and spot spraying. This application has an easy-to-use graphical user interface (GUI) through which some necessary information can be entered, as well as some buttons to perform specific tasks, in addition to real-time display of calculated variables and a display of the camera stream. additionally, this application can record real-time information and save them in an Excel file that can be used for documenting or further analysis.

Uploaded At: 2026-06-21 12:24:39

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