With the fast-growing economy in which the majority of the workforce uses two-wheelers, the occurrence of accidents has increased by 35 percent over a 35-year period, with fatalities totaling around 58,000 last year. The main cause of accidents is that the rider does not follow safety protocols or their accident is not reported on time. We proposed a smart helmet that detects accidents and detects if the rider is intoxicated by alcohol when worn by the rider. The prototype uses the following sensors to detect this (IR Sensor, Accelerometer, Breath-analyzer). The accelerometer measures the rider’s sudden change in tilt and sends data to a programmed interface. The breathalyser will detect the amount of alcohol in the rider’s breath and report if the reading exceeds the legal limit. The server gathers the information from the IR sensor to train Support Vector Machine (SVM) [1] which will be useful to optimize accident detection in the future when sufficient data is gathered.