SMART CROP PROTECTION SYSTEM USING DEEP LEARNING

Abstract

Agriterrorism with regard to animal damage greatly affects the crop yield for farmers, resulting
to some of them recording large losses. Farm animals like buffaloes, cows, goats and birds
trespass in the fields trample the crops and this can only be destructive for farmers since they
cannot constantly protect their shambas. Measures such as the use of barriers, wire fences, or
personnel vigilance yield most of the time insufficient results. In addition to scarecrows, which
enemies can easily bypass with many animals, farmers also employ human effigies.To control
these problems, we introduce an AI-based Scarecrow system using video processing in real-
time for crop protection from wildlife. The system uses a camera to record videos and analyzes
them with YOLOv3, an object detection model together with OpenCV and the COCO names
database. If any animal or bird is identified, then the system produces a sound alerting the
animal not to invade the compound. Moreover, if an animal has been sensed for more than one
minute consecutively, the system will alert the farmer sending him/her an e-mail and dialing
the farmer`s phone number. This approach thus provides an efficient and automated way of
protecting crops than depending on deterrent measures.