Multisensor Information Fusion for Condition Based Environment Monitoring

Abstract

Destructive wildfires are becoming an annual event, similar to climate change, resulting in catastrophes that wreak havoc on both humans and the environment. The result, however, is disastrous, causing irreversible damage to the ecosystem. The location of the incident and the hotspot can sometimes have an impact on early fire detection systems. With the advancement of intelligent sensor-based control technologies, the multi-sensor data fusion technique integrates data from multiple sensor nodes. The primary objective to avoid wildfire is to identify the exact location of wildfire occurrence, allowing fire units to respond as soon as possible. Thus to predict the occurrence of fire in forests, a fast and effective intelligent control system is proposed. The proposed algorithm with decision tree classification determines whether fire detection parameters are in the acceptable range and further utilizes a fuzzy-based optimization to optimize the complex environment. The experimental results of the proposed model have a detection rate of 98.3. Thus, providing real-time monitoring of certain environmental variables for continuous situational awareness and instant responsiveness.