Motorcyclists are about 29 times more likely than passenger vehicle occupants to die in a motor vehicle crash and are 4 times more likely to be injured. Safe motorcycling takes balance, co-ordination, and good judgement. As per NHTSA, per 100,000 registered vehicles motorcycle fatality and injury rate stand at 58.33 and 975 and that of passenger vehicles stand at 9.42 and 1152. With such rates of fatality and injury of motorcyclists, there is strong need for motorcycle solutions that help to minimize traffic fatalities and improve road safety scenarios. Helmets are estimated to be 37% effective in preventing fatal injuries to motorcycle riders and 41% for motorcycle passengers but there is little to no post-crash assistance available on board the motorcycles. Post-crash emergency response is time sensitive and can be broken down into a subset of activities beginning with discovery of crash, notification, and activation of emergency medical service (EMS), response time, on-scene time, occupant retrieval, pre-hospital medical care, transport and arrival at hospital. An advanced system is required that can accurately determine the motorcycle crash severity that considers the occupant post crash health parameters and effectively convey the information to an eCall system. This research presents an optimized solution for motorcycles that detects a collision and triggers the e-call system based on the estimated severity.