One of the primary requirements for sustaining a livelihood isagriculture. Low productivity of crops is one of the issues faced by the growers in our country. Crops destroyed by wild creatures is a major issue in low productivity. The agrarian fields must be defended from any undesirable interruption from creatures. In traditional styles, growers use crackers, electrical walls, direct observation etc., to keep creatures down from their fields but it's a threat factor that harms both humans and creatures. Our proposed system detects the presence of creatures using Image Processing and Machine Learning. Every time, crop damaged by wild creatures is dramatically adding in India. It frequently poses pitfalls to humans and creatures. Since further and further wild creatures are causing damage to their civilization; humans couldn't tolerate it. thus, they bear an effective medium to overcome this situation. With that background, the ideal of this study is to descry wild creatures before entering into the crop fields and enforcing applicable dread- down mechanisms in real- time. This paper presents an overview of the methodologies employed in this prototype model , including image segmentation, point birth, and bracket ways. Overall, this study highlights the significance of image processing technologies in advancing our understanding of this model and promoting sustainable relations between humans and wildlife.