• Aditya Halle
• Mrs. Bhoomi Patil
• Sanket Halle
• Omkar Nikharge

Farmers face a huge number of issues, for example, insufficiency of water for irrigation, crops withering because of climatic changes, soils lacking in nutrients, and harm to crops because of pests and wildlife. In any case, the protection of farm wild creatures has not been adequately tended to till now. Elephants, monkeys, wild boars, etc. cause serious damage to the fields. The productivity is decreased by the wild creatures trampling over harvests and eating them. This project provides a solution for these problems without hurting creatures or setting human life at stake. In this project, we use Raspberry Pi to protect the farmland from animals. Farmland intrusions are detected utilizing PIR sensors and photos are taken utilizing a Pi camera. Classification of the intruded animals as local or wild animals is done using the photos taken utilizing a Convolutional Neural Network. CNN a special architecture of artificial neural networks model is mainly used for the classification of images. After classification is done accordingly, sounds are used to ward off the creature, and an Email is sent to the landowner on account of the wild creature. Data regarding these intrusions of wild and domestic creatures are sent to the cloud by means of the web. This way it is easy to arrive at useful information regarding the intrusions and take action against them.

Image Classification, Convolution Neural Networks, Image Processing, Raspberry Pi, IR Sensors, Pi Camera

"Innovative Approach to Protect Crops Using Deep Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.301-307, May-2023, Available :http://www.jetir.org/papers/JETIRFX06053.pdf

"Innovative Approach to Protect Crops Using Deep Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp301-307, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06053.pdf