Paper Title
Iot Based Rider Health Monitoring System for Safety and Security

Abstract
The rise in road accidents due to negligent driving behaviors, such as riding without helmets or under the influence of alcohol, has highlighted the urgent need for intelligent safety systems. The Smart Helmet System is an innovative IoT-based solution designed to enhance rider safety, ensure compliance with road safety norms, and provide real-time emergency response. This system integrates two primary models: the Helmet Model and the Bike Model, both equipped with a variety of sensors and communication modules to monitor and control safety measures efficiently. The Helmet Model incorporates an MQ3 alcohol sensor to detect alcohol consumption, an IR sensor to verify helmet usage, and a blood pressure (BP) sensor to monitor the rider's health parameters. These sensor readings are displayed on an LCD screen for the rider’s awareness and simultaneously transmitted wirelessly to the Bike Model using a Zigbee module. The Bike Model, powered by an ESP32 microcontroller, is equipped with an RFID reader to authenticate the rider before enabling bike ignition. After authentication, the system checks helmet compliance and sobriety data received via Zigbee. If alcohol is detected, the system disables the ignition and immediately sends a Telegram alert to a predefined emergency contact. Furthermore, the inclusion of an ADXL accelerometer allows the system to detect accidents. In such events, the bike is automatically shut down and an emergency alert is dispatched. By leveraging IoT technology, wireless communication, and real-time monitoring, the Smart Helmet System ensures a layered approach to safety and security. It not only prevents unauthorized or unsafe bike operation but also facilitates rapid emergency response in case of accidents. This cost-effective and scalable solution addresses critical issues like drunk driving, non-compliance with helmet laws, and delayed medical response, thereby promoting responsible riding and reducing the risk of fatal road incidents. Keywords - RFID Authentication, Health Monitoring (BP), Alcohol Detection (MQ3 Sensor), Accident Detection, ESP32, Arduino UNO