THEUSEOFARTIFICIALINTELLIGENCEINEMERGENCYMONITORINGAND PREVENTION SYSTEMS

This article explores the relevance and effectiveness of applying artificial intelligence (AI) technologies in emergencymonitoring and prevention systems. AIalgorithms enable theprocessing of real-time data to detect anomalies early and predict the likelihood of hazardous situations. The paper examines the use of machine learning, deep learning, and anomaly detection methods in emergency response applications. Case studies from Kazakhstan are presented, including the ―Darmen‖ mobile alertsystem, earlyforestfiredetection technologies, and drone-based monitoring systems. Inaddition, the advantages and limitations of AI implementation are discussed, along with the legal and technicalchallenges related to its integration. The research highlights that AI can significantly contribute to effective decision-making and the reduction of human and material losses during emergencies. This article is intended for researchers, practitioners, and government agencies involved in disaster risk reduction and emergency management