AN INTELLIGENT MODEL FOR PREDICTING FIRE RISK IN RESIDENTIAL HOUSEHOLDS BASED ON ARTIFICIAL INTELLIGENCE

Residential fires remain a major threat to human life, property, and public safety. Most conventional fire safety systems are designed to detect fire after ignition, limiting their preventive capabilities. This study proposes an intelligent model for predicting fire risk in residential households based on artificial intelligence. The model integrates data from temperature, smoke, gas, humidity, and electrical sensors to assess fire hazards before ignition occurs. By analyzing multiple risk indicators simultaneously, the proposed approach enables early warning, supports preventive measures, and contributes to reducing fire-related losses. The study highlights the practical potential of artificial intelligence in strengthening residential fire safety and emergency management.