An IoT-Belief Rule Base Smart System to Predict Earthquake

Abstract

An Internet-of-Things (IoT) - Belief Rule Base (BRB) based mixture system is introduced to evaluate Earthquake prediction (EP). This intelligent method can automatically accumulate signs of animal behavior along with environmental and chemical changes in the nature of various earthquakes in real-time and predict their intensity levels. The BRB subsystem incorporates knowledge demonstration parameters such as attribute weight, rule weight, and degree of belief. The IoT-BRB system predicts the probable occurrence of the earthquake in a region based on the sign and symptoms collected by the persistent sensing nodes. The categorization results obtained from the projected IoT-BRB smart method is compared with expert and fuzzy-based system. The projected method outperformed the up to date expert system and fuzzy system.