Intelligent Deep Learning Enabled Wild Forest Fire Detection System

The latest advancements in computer vision and deep learning (DL) techniques pave the way to design novel tools for detection monitoring of forest fires. In this view, paper presents an intelligent wild fire alarming system using (IWFFDA-DL) model. proposed IWFFDA-DL technique aims identify fires at earlier stages through integrated sensors. includes Integrated sensor (ISS) combining array sensors that acts as major input source helps forecast fire. Then, attention based convolution neural network with bidirectional long short term memory (ACNN-BLSTM) model is applied examine existence danger. For hyperparameter tuning ACNN-BLSTM model, bacterial foraging optimization (BFO) algorithm employed thereby enhances performance. Finally, when detected, Global System Mobiles (GSM) modem transmits messages authorities take required actions. An extensive set simulations were performed results are investigated interms several aspects. obtained highlight betterment various measures.