Exploitation of Deep Learning Algorithm and Internet of Things in Connected Home for Fire Risk Estimating

This research attempts to implement fire safety measures and ensure the safety of individuals with the preservation of property in institutions, health, and lives of citizens. Fire prevention procedures must be developed and implemented in order to assess, remove, and prevent probable causes of fires. Fire risk measures include creating ideal conditions for saving property and evacuating citizens. Preventive work with residents guarantees that the source of the ignition is identified and that emergency services are alerted as soon as possible in the event of a fire. An Unsupervised Deep Learning algorithm using the Internet of Things (IoT) concept was used to develop a fire risk estimation system. The suggested algorithm determines whether or not the scenario is safe. An alert signal is transmitted to three peripheral devices: the monitoring camera, the fire sensor due to high temperatures, and a sensor due to the increasing CO levels in the atmosphere. The proposed system considers the data collected by various distributed sensors and later it is processed by using a deep learning algorithm to estimate the risk level at that point, release an alarm fire risk as a signal at a usual time for safety and preserve public property.