SIGNAL ATTENUATION MODEL FOR EXTREME WEATHER CONDITIONS

Abstract

This project aims to assess the signal attenuation of various radio communication technologies in extreme weather conditions, particularly when buried in the snow. The primary objective is to evaluate signal strength and data reception success rates in different distances under such conditions. The outcome involves the development of a Machine Learning (ML) model utilizing Received Signal Strength Indicator (RSSI) data to identify snowy conditions. Potential applications include enhancing the reliability of IoT systems in environments like railway systems or smart cities, where the signal strength can indicate the extent to which a device is buried under snow.