Abstract:
s we all know 2019 was the year the world burned. The biggest carbon dioxide sinks of the earth "The Amazon Forest" was hit with a catastrophic forest fire which ignited an area of approximately 906,000 hectares. Not only amazon but Australia was also in ashes due to forest fire and claimed the lives of millions of trees and animals. To save our mother nature we need a system that not only detects the forest fire but also predicts it before any mishap. The system uses a Controller to receive data from four sensors which will monitor the condition and climate of the forest. The controller is also connected to a Wi-Fi and GSM module to show the real time monitoring using an app on the smartphone and to send alerts if there is any problem. This system will be powered by sustainable energy, a solar panel will be connected to it to power it and backup batteries will be charged using the same solar panel for night operations. Predictions would be done using machine learning the data of the previous forest fire will be fed to the machine and using that data it will be trained to predict forest fire before it even happens. The main aim of this project is to develop multiple handy devices mounted with the sensors and controllers, which can be installed in the forest some yards away from each other to cover the forest area. Using them we can monitor the forest and predict any catastrophic wildfire which is to happen and can save the lives of millions of trees and wildlife.
