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Abstract: Farming computerization has been on the ascent utilizing, among others, Deep Neural Networks (DNN) and IoT for the turn of events and organization of many controlling, observing, and following applications at a fine-grained level. In this quickly developing situation,dealing with the relationship with the components outside of the agribusiness environment, like natural life, is an applicable open issue. One of the primary worries of the present ranchers is shielding crops from wild animals' assaults. There are different conventional ways to deal with addressing this issue which can be deadly (e.g., shooting, catching) and non-deadly (e.g., scarecrow, compound anti-agents, natural substances, lattice, or electric walls). By and by, a portion of the customary techniques have ecological contamination impacts on the two people and ungulates, while others are pricey with high upkeep costs, restricted dependability, and restricted viability. In this undertaking, we foster a framework, that consolidates AI Computer Vision involving DCNN for distinguishing and perceiving creature species, and explicit ultrasound emanation (i.e., different for every species) for repulsing them. The edge processing gadget enacts the camera, then, at that point, executes its DCNN programming to recognize the objective, and assuming a creature is distinguished, it sends back a message to the Animal Repelling Module including the kind of ultrasound to be produced by the classification of the creature.