AI and IoT-Enabled Smart Helmets for Accident Detection, Health Monitoring, and Automatic Emergency Alert Systems

Motorcycle accidents remain a leading cause of death on the roads, particularly in developing countries where two-wheelers are the primary means of transportation. The delayed emergency medical response and lack of information about the victim's health status increases the risk of death during the crucial first hour following the incident. WHO estimates that Powered two-wheelers (PTWs) account for nearly 25% of global road deaths, with some Asian countries witnessing even higher rates due to intense traffic and insufficient protective infrastructure. Researchers have proposed various Internet of Things (IoT) and sensor enabled smart helmets to address these issues. Previous works use a combination of motion sensor and communication modules coupled with micro-controllers to identify accidents and relay user location information. However, a deeper inspection of the recent literature suggests pertinent limitations with the proposed solutions. While most works demonstrate successful crash identification using accelerometers and force sensors, there was an apparent lack of integration of biometric monitoring (heart rate and SpOn), intelligent AI driven severity assessment tool, cloud assisted medical record retrieval and robust false alarm mitigation mechanisms. This paper presents a detailed analysis of five IEEE research papers published in 2023-2025 that explore smart helmet design. The papers examined various existing works related to smart helmet based accident detection systems, user health monitoring and emergency alert relaying mechanisms. The review highlights potential research opportunities based on the gaps identified in the surveyed works. Leveraging the lessons learned from the review and the opportunities highlighted, this work also proposes an original AI driven smart helmet system design. The proposed model uses a combination of sensors for accident detection, biometric health monitoring and alcohol content estimation. The model also implements an AI based impact assessment algorithm and intelligent dual mode emergency message relaying system. The observations made in this review can form a robust foundation for the development of next generation smart helmet systems that canreduce post-crash mortality rates due to timely emergency response