An IoT based Real-Time Stress Detection System for Fire-Fighters

Stress is an acute condition of a person experienced under high pressure. This can to conditions like depression and cardiac arrest. One of the top most stressful jobs across the globe is that of firefighters. They, not only have to rescue the people who are in danger also needs to keep themselves and their co-workers safe during the rescue mission. This paper deals with the design and implementation of a real-time stress monitoring system for firemen who have been assigned a fire rescue mission. This work focusses on the development of a wireless sensor node prototype embedded on the gloves of firemen which embeds Galvanic Skin Response (GSR) sensor and heart rate sensor to detect the stress level, a microcontroller to process data, a communication module using ZigBee to send data and a rechargeable long-lasting power supply. The system uses Message Queuing Telemetry Transport (MQTT), as the IoT message protocol and Adafruit IO as the MQTT broker and analytics platform to store and analyze data based on which the alerts are displayed to the fire engine via User Interface (UI). Also, advanced Machine Learning techniques can be incorporated in the future to study the anomaly and predict the stress among firemen beforehand.