Machine learning enabled IOT based fire accident detection system.

The proposed system is to atomize the detection of fire or smoke at an early stage and can help in saving lives at home or at work place. The system is in such a way that it is versatile enough to all types of environments. IOT based Fire Accident Detection System uses the Sensors, namely, Temperature, Smoke and the Digital Humidity sensor. The micro-controller is programmed to turn on the alert, when any one of the temperature, smoke and humidity reach a threshold value in the air. We are trying to implement Machine learning enabled IoT technology to detect the Fire Accidents. In this system we go for detection and Monitoring of fires through several sensors and send to IoT cloud. Machine learning provides ability to learn and improve from experiences automatically thus provide accurate results. So it can avoid false alarming for the Indian daily events like smoke from incense sticks. It does not decide only on one factor, there are various factors like humidity, temperature, carbon monoxide (CO), carbon dioxide (CO2), Nitric Oxide(NO), Ammonia(NH3). Depending upon the sensor values in the cloud if it is greater than the preset values it will turn on the alert. Continuous monitoring and uploading values to Thing speak cloud can be achieved. It notifies us through SMS whenever there is a sudden spike in the gases, temperature or humidity around us or whenever there are high levels of such chemicals. [ABSTRACT FROM AUTHOR]