Abstract: Deforestation detection by using RCNN is a new approach to monitoring the emergence of deforested areas. In recent decades, illegal logging has intensified, threatening the environment and contributing to climate change. Deforestation is increasing day by day as no adequate protection is provided. They eventually found one of the most endangered trees in our country. Therefore, in order to protect the trees, the project proposed a way to detect deforestation and fire burning near trees using in-depth learning strategies. The main goal is to see if there is a suspicious person in the forest who could cut down and chop wood and see a fire in the forest that will avoid dangerous damage such as burning trees. A major role is to make a divider that gets a man-made saw. This project is based on the RCNN (Recurrent convolutional Neural Network). After the fire is detected, the system will generate a voice alert and send an email alert to the forest department. To detect the theft of a tree, the system will generate an email alert and send it to the relevant forest department via IMAP protocol and a voice alert is also activated. So we can avoid losing fire by extinguishing a fire if it is a fire alarm or by catching a wood thief trying to steal firewood in case of a theft alarm

PDF | DOI: 10.17148/IJARCCE.2022.114197

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