NEUROHELMET: AN IOT-ENABLED SMART HELMET FOR TWO-WHEELER RIDER SAFETY AND EMERGENCY RESPONSE

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Abstract

The Smart Helmet System is a technology-driven safety solution developed to improve protection and emergency response for two-wheeler riders.Motorcycle accidents frequently lead to serious injuries due to improper helmet usage, riding under the influence of alcohol, and delays in receiving medical assistance.To overcome these issues, the proposed system integrates preventive safety mechanisms and automated emergency communication within a single intelligent helmet framework.The system incorporates helmet-wear detection to ensure proper usage before ignition, along with an alcohol sensing module that restricts vehicle operation if intoxication is detected.An accelerometer-based crash detection mechanism continuously monitors sudden impacts or abnormal motion patterns.In the event of an accident, the helmet automatically acquires real-time GPS coordinates and transmits an emergency alert message to pre-registered contacts using GSM communication, thereby reducing rescue response time.In addition to safety enforcement, the system supports voice-assisted navigation to provide hands-free route guidance, minimizing rider distraction.Live location tracking further enables family members to monitor travel progress, enhancing personal security during long journeys.The entire system is implemented using embedded microcontroller technology, wireless communication modules, and sensor integration to ensure reliable and real-time performance.By combining accident prevention, monitoring, navigation support, and automated emergency alerts, the Smart Helmet System presents a practical and scalable solution aimed at reducing road fatalities and encouraging responsible riding behavior in modern transportation environments.

Fields of Study & Subjects

IoT and GPS-based Vehicle Safety Systems Traffic and Road Safety Automotive and Human Injury Biomechanics

Publication details

Journal / source
International Research Journal of Modernization in Engineering Technology and Science
Publication date
26 February 2026
Language
EN