Design and Implementation of an AI and IoT-Enabled Smart Safety Helmet for Real-Time Environmental and Health Monitoring

This research paper is introducing the concept of AI and IoT-enabled Smart Safety Helmet for Real-Time Environmental and Health Monitoring, which is a breakthrough attempt focusing on providing safety solutions for workers in dangerous areas. Employing the AI-IoT synergy to solve the problem of monitoring the surrounding environment and the mental state of the user, our helmet significantly decreases a risk of an accident and exposure to dangerous conditions. The primary part of the study is to mount various sensors on the helmet so as to observe the realtime changes in the environmental parameters that include CO2 levels, temperature, humidity, and physical responses of the wearer as well. This sensor data is then fed into a microcontroller unit that is connected with IoT that uses this process and analyze the data to identify risks and assess risk levels. Through the IoT technology, a perfect channel for a real-time data transfer to the end-users end the centralized monitoring systems is availed, enabling an action to be taken immediately. We ran many different types of MATLAB simulations and real-world testing scenarios. Then our evaluation determined the sensors' accuracy, the efficiency of the AI model, the consumption of the power, the data transmission capabilities, and the overall usability of the helmet. This outcome not only confirms the safety and economical nature of the helmet but as well its user-centricity design which ensures its effectiveness in creating a safe working environment.