Delivering the Future 🚀
SU Robo is a full-stack autonomous campus delivery robot system developed at Elsewedy University of Technology (SUT) as a graduation project. The system enables contactless, AI-secured delivery of meals and parcels across university campuses using a 4WD robot platform with biometric face recognition for cargo release.
🏆 ARIIF 2025 Competition — Final List (Project Code: 25SUTDP005)
- 📱 React Native mobile app — food ordering, staff delivery requests, real-time robot tracking
- 🤖 Autonomous navigation — IR line tracking + ultrasonic obstacle detection
- 🔐 Biometric cargo unlock — ArcFace face recognition (≥95% accuracy, cosine similarity ≥0.60)
- ⚡ Real-time updates — Socket.IO with <2s latency
- 🖥️ Multi-role admin dashboard — super_admin, restaurant_owner, student, staff
- 🍽️ Restaurant management — kitchen queue, menu management, order lifecycle
Mobile App (React Native) ←→ Node.js Backend ←→ MySQL Database ↕ Admin Dashboard (Vanilla JS) Socket.IO (real-time) ↕ Python Flask (ArcFace) ↕ ESP32 Robot (Wi-Fi) IR · Ultrasonic · Camera
| Layer | Technology |
|---|---|
| Mobile App | React Native, Expo SDK 54, React Navigation v6 |
| Backend | Node.js, Express.js, Socket.IO, JWT Auth |
| Database | MySQL (8 core tables) |
| Face Recognition | Python Flask, InsightFace, ArcFace |
| Admin Dashboard | Vanilla JavaScript, Socket.IO client |
| Hardware | ESP32 WROVER, ESP32-CAM, L298N, HC-SR04, IR sensors, IMU MPU-6050 |
| Firmware | Arduino C++ (FreeRTOS dual-core) |
| Component | Quantity | Cost (EGP) |
|---|---|---|
| ESP32 WROVER | 2 | 1,000 |
| ESP32-CAM + Board | 1 | 380 |
| 3D Printed Chassis | 1 | 12,000 |
| L298N Motor Driver | 2 | 150 |
| 25GA370 DC Motor 12V | 4 | 1,260 |
| HC-SR04 Ultrasonic | 4 | 200 |
| IR Line Tracking | 3 | 105 |
| IMU MPU-6050 | 1 | 175 |
| Robot Tires + Couplers | 4 | 1,600 |
| SG90 Servo Motor | 1 | 80 |
| Buck Converter | 1 | 80 |
| 18650 Battery + Holder | 1 | 400 |
| Misc (wires, switch) | — | 170 |
| Total | EGP 17,600 |
cd backend
npm install
cp .env.example .env
npm run devcd mobile
npm install
npx expo startcd face-service
pip install -r requirements.txt
python app.pyOpen esp32-firmware/ in Arduino IDE Install ESP32 board package Flash to ESP32 WROVER
| Metric | Target | Achieved |
|---|---|---|
| Face Recognition Accuracy | ≥95% | ✅ 95% |
| Real-time Update Latency | <2s | ✅ 1.4s avg |
| Delivery Success Rate | ≥90% | ✅ 92% |
| Hardware Unit Cost | <EGP 20,000 | ✅ EGP 17,600 |
| Name | ID | Role |
|---|---|---|
| Youssef Mohamed | 240102997 | Team Lead — Mobile, Backend, Architecture |
| Mohanad Mohamed | 240100006 | Hardware — ESP32, Motors, Chassis |
| Abdelrahman Essam | 240103308 | Hardware — Sensors, Wiring, Camera |
| Bassel Osama | 230103139 | Hardware — Servo, Power System |
| Jana Mohamed | 240102837 | Documentation — Technical Report |
| Mariam Ahmed | 240102470 | AI — Face Recognition, Dashboard |
| Judy Khaled | 240102849 | AI — Dashboard, Backend API |
| Sam Malak | 240102939 | Cybersecurity, Hardware |
| Hamza Khaled | 240103406 | AI — Python Flask, ArcFace |
Supervisor: Prof. Dr. Amany Sarhan — Elsewedy University of Technology
MIT License — see LICENSE for details.
Made with ❤️ at Elsewedy University of Technology · Spring 2025