Wild animal invasion has been on the rise in agricultural fields, causing significant damage to crops. Hence, a solution is proposed that uses neural training with the backpropagation algorithm to identify different animals based on their forms, surface details, and color. This training process contains multiple perspectives of wild animals—frontal, back, and lateral views—focusing on features like coloration, form, and patterns. A live camera feed is examined through the MATLAB video processing algorithm to extract image features and compare them with a real-time neural-trained database. The database is created with wild animal image features along with their disturbing frequency range. The similarity result of the database with the camera feed will trigger a speaker with a stored frequency level. Thus, the novel idea of this work is to produce a sound signal that can alert humans about the presence of animals and prevent the animals from entering the fields.