ALGORITHMS FOR FAST FIRE RISK PREDICTION AND REAL-TIME DATA PROCESSING
Abstract
Ensuring fire safety in facilities with high fire risk is one of the pressing problems of modern society. Nowadays, there is a great need for accurate and effective prediction systems for fire prevention and rapid response. Since traditional methods do not provide the ability to quickly analyze and predict in real time, the development of algorithms and modern approaches using modern technologies is of great importance. This article analyzes fire risk prediction algorithms, their principles of operation and effectiveness, and considers methods for assessing and predicting fire risk using Artificial Intelligence (AI), Machine Learning (ML), and Big Data technologies. The article highlights the advantages and disadvantages of fire risk assessment algorithms, taking into account weather conditions, the ecological state of the area, human factors, and other important parameters. The research results can be used to create effective systems aimed at quickly detecting and preventing fire hazards. At the same time, it helps to speed up the response of emergency services, reduce economic losses, and improve environmental protection. This article aims to explore advanced technological approaches to improving fire safety and presents practical solutions.