Predictive Modeling of Fire Hazard: Integrating Environmental Factors with Machine Learning

In today’s fast-paced world, where technology is advancing rapidly, the tragic loss of lives due to fire accidents is not only heart-wrenching but also poses a significant risk to public safety. Early prediction of such risks can play a crucial role in educating people about fire hazards, enabling them to be better prepared in case they find themselves in such unfortunate circumstances. Our study employed various machine learning (ML) techniques and evaluated their effectiveness by analyzing different factors. These factors are derived from the diverse living conditions in Bangladesh and were gathered through surveys. To refine and identify the critical features for classification, we utilized feature selection methods like ANOVA-f and the chi-square test. Our approaches have achieved a success rate of up to 97.98%.