Crop Protection from Animals Using Deep Learning


  • Iniyaa K K
  • Divya J K
  • Devdharshini S
  • Sangeethapriya R


Crop protection, CNN, Wild animal attacks, Deep learning.


Crop damage caused by animal’s attacks is one of the major threats in reducing the crop yield. Due to the expansion of cultivated land into previous wildlife habitat, crop raiding is becoming one of the most conflicts antagonizing human-wildlife relationships. Farmers in India face serious threats from pests, natural calamities and damage by animals resulting in lower yields. Traditional methods followed by farmers are not that effective and it is not feasible to keep an eye on crops and prevent wild animals. Since safety of both human and animal is equally important. It is important to protect the crops from damage caused by animal as well as divert the animal without any harm. In order to overcome above problems and to reach our aim, we use machine to detect animals, entering into our farm by using neural network concept, a division in computer vision. In this project, we will monitor entire farm at regular intervals through a camera which will be recording. With the help of deep learning model, we detect the entry of animals and we play appropriate sounds to drive the animal away. In our project, we use various libraries and concepts of convolutional neural networks used to create the model.


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How to Cite

Iniyaa K K, Divya J K, Devdharshini S, & Sangeethapriya R. (2021). Crop Protection from Animals Using Deep Learning . International Journal of Progressive Research in Science and Engineering, 2(3), 41–44. Retrieved from