Smart Safety Helmet for Workers

Abstract

Industrial workers are frequently exposed to hazardous conditions such as falls, smoke, and harmful gases, which can lead to severe injuries or fatalities if not detected promptly. This project presents the design and implementation of a Smart Safety Helmet System aimed at enhancing worker safety through real-time monitoring and automatic response mechanisms. The proposed system is built around two ESP32 microcontrollers communicating via the ESP-NOW protocol. The helmet unit integrates an MQ2 gas sensor for smoke and gas detection and an MPU6050 sensor for motion, fall detection, and temperature monitoring. Real-time data is displayed on an OLED screen, while detected hazards trigger automatic responses such as activating a ventilation fan or issuing an audible alert using a buzzer. Experimental results demonstrate that the system accurately detects falls and hazardous gas conditions with low latency and reliable wireless communication. The proposed helmet proved to be portable, power-efficient, and suitable for industrial environments. Future enhancements may include cloud connectivity, additional environmental sensors, and improved power optimization techniques.