Development of Framework for Forest Fire Disaster Management using Sensor Networks

Abstract

The impact of forest fire is one of the major concerns in the loss of natural atmosphere. These kind of forest fires are activated by humans, wood, stone, and plants and other elements. In order to minimize forest fire disasters and increasing economic development will lead to ecological changes. The purpose this framework model is to process the data and evolve new techniques and update the firefighters. In this research, the work is to monitor the flame, humidity/temperature, and smoke detection. Forecasts for such data will be assessed using the innovation that IoT platforms employ to construct a software solution based on data obtained through sensing and networking capabilities with cloud computing in WSNs. The goal of this study is to fire detection in different places, discover wildfires accidents, and avoid incidents prior to threatening any wildfires mishaps on the site. Fire catastrophe is a quenching technique that uses FFPA and EDTA approach to give real-time surveillance and identify disasters in order to protect the forests and control the wildfire. The sensor data is sensed by a smoke detector, temperature, related humidity, and flame. When the node is collecting the data and checking the threshold value for detection of fire, it sends a piece of immediate information to various levels of firefighters and authorizers for preventing an accident. This research focus to predict and process the data using a framework that provides necessary steps in an updated manner to the authorized person. A framework has been implemented to predict forest fire detection using different parameters to detect for identifying the performance of prediction by FFPA (Forest fire prevention algorithm) and Enhancing Decision Tree Methodology (EDTA) to detect and prevent the forest fire. In this work, effective prevention for forest fire disaster management has been carried out and based upon value analysis of different parameters like temperature, humidity, smoke, and flame for various measurements to predict the forest env