An Intelligent Wearable Safety Jacket for Motorcycles Using Lean Angle Detection and Automatic Airbag Deployment

Motorcycle accidents remain one of the leading causes of road fatalities, with two-wheeler riders accounting for nearly 44% of all road accident deaths in India. Conventional protective equipment, such as helmets, provides limited protection to the rider's torso, spine, and shoulders, while existing tether-based airbag jackets suffer from delayed deployment due to their dependence on rider separation from the motorcycle. This paper presents an intelligent wearable safety jacket that employs lean angle detection and real-time crash identification for rapid airbag deployment. The proposed system utilizes an MPU-6050 inertial measurement unit (IMU) and an Arduino Uno microcontroller to continuously monitor lean angle, acceleration, and angular velocity at a sampling rate of 100 Hz. A complementary filter is implemented for accurate lean angle estimation, while a dual-threshold crash detection algorithm combines G-force (1.8 g prototype threshold) and tilt rate (30°/s) to minimize false alarms. Crash confirmation is achieved using two consecutive sensor readings, enabling deployment within approximately 10–20 ms, which is significantly faster than the average human reaction time of 150–200 ms. The proposed airbag jacket incorporates a 17 L multi-zone inflatable bladder designed to protect the spine, chest, shoulders, neck, and collarbone. Experimental evaluation of the prototype demonstrated reliable detection of hazardous riding conditions while effectively distinguishing normal riding events such as braking, potholes, and cornering from actual crash scenarios. The proposed system offers a low-cost, intelligent, and rapid-response rider protection solution, making it suitable for improving motorcycle safety, particularly for urban commuters and delivery riders.