Сучасні інформаційні системи інформування та прогнозування надзвичайних ситуацій

Abstract

The increasing frequency and scale of emergencies require the improvement of information systems for forecasting and alerting. This paper analyzes modern methods for predicting emergencies, including time series models (ARIMA, GARCH), artificial neural networks, machine learning algorithms, and big data. Special attention is given to the use of Geographic Information Systems (GIS) and the Internet of Things (IoT) for real-time automated threat monitoring. The effectiveness of national and international alert systems (WEA, NINA, J-ALERT) is examined, with key evaluation criteria identified: message transmission speed, population coverage, adaptability, and information reliability. A concept for an integrated alert system that combines various technological solutions to enhance emergency response efficiency is proposed.