ENHANCING FIRE SAFETY: ADVANCEMENTS IN AI POWERED FIRE DETECTION SYSTEMS

Abstract

Currently the majority of automatic fire alarm systems use a single passive sensor alarm system which has some unavoidable problems. In domestic fire alarm systems, some devices using photosensitive detectors are affected by sunlight and lighting. Smoke detectors can be affected by various gases. Due to which we often get false fire alarm. Thus, traditional fire detection systems are unable to meet the needs of real fire alarm. AI fire detectors can handle small and large fire targets as well as smoke. It can provide more visual information and spatial awareness than sensors. AI cameras can help to detect the fire and prevent the spread of wildfires. AI cameras can be installed in buildings to monitor the indoor environment fire. AI cameras can help improve the on-site incident command. The existing system of fire detection is based on detecting of fire using heat, flame, gas and smoke sensors. Limitations of existing system are high power consumption, maintenance costs and environmental interference. The proposed AI fire detection can detect fire and smoke in images or videos and also overcome limitations of existing system. Fire detection systems incorporating AI-enabled cameras have revolutionized early fire detection capabilities, offering a proactive approach to fire safety. These systems leverage advanced computer vision methods and deep learning algorithms to analyze real-time video streams from surveillance cameras, enabling the identification of fire and smoke patterns with remarkable accuracy and speed.