Objectives
1. To develop a mobile app using Flutter for real-time fall alerts. 2. To connect and monitor an IP camera using a YOLOv8 model running on a local laptop. 3. To integrate a wearable device (ESP8266 + MPU6050) for motion-based fall detection. 4. To send instant alerts to the caretaker’s phone in case of a fall. 5. To ensure continuous fall monitoring whether the person is in or out of camera view.
Socio-Economic Benefit
1. Improves elderly care by providing timely fall alerts, reducing risk of serious injury. 2. Supports low-income families with a low-cost, non-cloud-dependent safety solution. 3. Reduces hospital burden by enabling quicker response and possibly preventing long-term damage. 4. Encourages local innovation by showing how affordable tech can solve real-life problems.
Methodologies
1. Requirement Analysis – Identify system needs, components, and user roles (caretaker and patient). 2. Hardware Integration – Set up IP camera and wearable device (ESP8266 + MPU6050). 3. Model Training – Train YOLOv8 model on fall detection dataset using local machine (RTX 4060). 4. Backend Development – Use Python with OpenCV and Flask to process video and send alerts. 5. App Development – Build a Flutter app to receive alerts and display fall notifications. 6. Testing & Validation – Test camera and wearable detection accuracy in real-world scenarios. 7. Deployment – Run the system on a local laptop and connect with the Flutter app over Wi-Fi.
Outcome
1. A working Flutter app that receives real-time fall alerts. 2. Successful integration of IP camera with YOLOv8 model for visual fall detection. 3. Functional wearable device (currently a prototype) for fall detection when camera view is unavailable. 4. Reliable alert system that notifies caretakers instantly through the app.
Project Team Members
| Registration# | Name |
|---|---|
| CU-2008-2021 | Hashir Ahmad Khan |
| CU-1982-2021 | Muhammad Faiq |
| CU-2253-2021. | Umer Bin Muslim. |
PROJECT GALLERY
Real-Time Fall Detection for Parkinson’s Patients Using YOLO and IoT-Enabled Smart Monitoring Systems
22 Jun, 2025 06:28 pm
