What is it?
An in-car IoT safety system that prevents drunk driving, monitors speed, and identifies the driver. Built for a national competition in 3 months.
What needed solving?
Drink-driving remains a leading cause of road fatalities in Malaysia. Existing solutions are expensive, cloud-dependent, or easy to bypass. None address sobriety, identity verification, and speed monitoring in a single unified system.
No single device addressed drunk driving, identity, and speed at once.
How it was built
How we solved it
Designed a pre-ignition gate: the car won't start until the driver passes a MQ-3 breath alcohol test. HuskyLens handles facial identification so only registered drivers can operate the vehicle. A GPS module triggers configurable audio speed alerts in real time. The entire system runs on a Raspberry Pi Pico.
Build & demo
Why these technologies?
| Technology | Why we chose it | Role in system |
|---|---|---|
| Raspberry Pi Pico | Dual-core ARM microcontroller with ultra-low power draw, suitable for always-on installation in a car without draining the battery. | Sobriety gate + sensor fusion |
| HuskyLens | Dedicated AI camera module for face recognition that runs entirely on-device with no server, no API, no internet required. | Facial ID gate |
| MQ-3 Sensor | Industry-standard electrochemical alcohol sensor with calibrated sensitivity in the breath-test range (0.05–0.5 mg/L). | Alcohol detection |
| GPS Module | Standalone NMEA-output GPS provides speed data without cellular dependency and works in any location. | Speed monitoring |
Key metrics
What we achieved
Pre-ignition alcohol gate blocks drunk drivers before the car starts
HuskyLens facial ID ensures only authorized drivers can operate the vehicle
Real-time GPS speed alerts with configurable thresholds
Competed nationally in Shell Selamat Sampai Varsity Challenge 2024
Full system assembled and demonstrated within a 3-month timeline