Finished 11th out of 59 teams at the Ignition 1.0 Hackathon, conducted by Team VEGAVATH, PES University EC Campus and Powered by ATHER ENERGY
📅 7th & 8th November 2025
This project is a mobile-based driver telemetry and rider-state detection system that collects real-time sensor data from a smartphone and classifies rider movement into walking, running, scooter, or bike riding. The phone is mounted securely onto the rider’s chest using a normal belt, enabling accurate motion and orientation capture without needing additional sensors or hardware modules.
The system visualizes live telemetry, GPS routes, speed, and motion data within a mobile app and stores all readings locally with timestamps.
- Participants must build a wearable telemetry system that attaches to a rider’s helmet, jacket, and/or pants and captures real-time motion and location data.
- The system must display live information on a mobile app and store all readings with timestamps.
- The app should also detect whether the rider is on a scooter, a motorcycle, or not riding, based on posture and motion.
- All prototypes must be fully demonstrable on the test track during the hackathon.
The mounted position captures torso orientation changes and vibration/tilt patterns:
- High-frequency oscillation → running
- Low vibration + minimal lean angle → scooter riding
- Sharp gyroscopic variation during leaning → bike riding
- Vertical body motion periodicity → walking
- Live GPS route mapping & speed calculation
- Real-time IMU visual telemetry
- Activity classification: Walking / Running / Scooter / Bike
- Timestamped local logging
- Low-cost wearable prototype + battery efficient
- Minimal weight mount with no stains or damage to gear
| Component | Technology |
|---|---|
| Website | Flask |
| App | Flutter |
| Sensors | IMU (Accelerometer + Gyroscope) & GPS |
| Data Storage | Local database |
| Visualization | Charts, Maps, Graphs |
| Hardware | Smartphone + normal belt |