Applications of Artificial Intelligence in Fire Safety of Agricultural Structures

Artificial intelligence applications in fire safety of agricultural structures have practical economic and technological benefits on commercial agriculture. The FAO estimates that wildfires result at least USD 1 billion agriculture-related losses due to the destruction livestock pasture, buildings, premature death farm animals, general disruption activities. Even though artificial neural networks (ANNs), genetic algorithms (GAs), probabilistic (PNNs), adaptive neurofuzzy inference systems (ANFISs), among others, proven useful prevention, their application is limited real environments. Most farms rely traditional/non-technology-based methods prevention. case for AI prevention grounded accuracy reliability computer simulations smoke movement analysis, risk assessment, postfire analysis. In addition, such technologies can be coupled with next-generation fire-retardant materials as intumescent coatings a polymer binder, blowing agent, carbon donor, acid donor. Future prospects agriculture transcend basic encompass Society 5.0, energy smart cities, UAV monitoring, Agriculture 4.0, decentralized energy. However, critical challenges must overcome, including health aspects, cost, reliability. brief, offers unlimited potential hazards farms, but existing body knowledge inadequate.