A Deep Learning-Based Autonomous Fire Detection and Suppression Robot

Abstract

Fire poses a significant threat not only to human life but also to property, necessitating prompt and effective identification and control. Traditional systems are labor intensive, which is often slow and ineffective. This study utilizes cutting edge technologies in robotics and artificial intelligence to develop a robot which can detect and put out fire without human intervention. The system engaged multiple sensors such as thermal cameras for heat sensing, gas detectors and smoke sensors. The robotic system has been trained of different terrains with the use of convolutional neural network navigation algorithms to navigate through various terrains. The fire suppression system is intended to use water foam, dry chemicals and wet chemicals to suppress different classes of fire effectively. Several tests under simulated conditions as well as real life conditions have also confirmed that the robot works effectively and can be used to improve fire hazards safety. Overall, the developed robot represents a very important progress in the field of fire management due to its more trustful and efficient performance in comparison with conventional systems.