International Research Journal of Education and Technology

We address the problem of wild animals damaging agricultural land from several perspectives. Farmers who are impacted by this everywhere are quite worried about it, and it causes them a great deal of social and financial hardship. An investigation was carried out in Katli village, Rupnagar, India, to find the cause of this issue. The primary goal of the current research is to create a device that will minimize agricultural damage without endangering the crops themselves by directing wild animals away from fields. An infrared camera and a convolutional neural network (CNN)-based machine learning model have been coupled to produce an Acoustic Repellent System, which can identify target animals such as deer, wild boar, and nilgai. With the help of a frequency generator and camera, a Pic Microcontroller module can identify various animal species and generate sounds that deter them from visiting the farms of interest. Furthermore, a thorough explanation of the suggested solution's architectural features has been given. Finally, an analysis has been conducted about the possible outcomes of the suggested resolution.

Keywords- Crop Destruction, Crop-Raiding, Wild Animals, Human-Wildlife conflict, ML, CNN, Acoustic, Repellent, IoT, PIC.