Smart Agriculture Land Crop Protection Intrusion Detection Using Artificial Intelligence

¹ Electrical and Electronics Engineering, M.Kumarasamy College of Engineering, Karur, India
² Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur, India
³ Electronic and Instrumentation Engineering, M.Kumarasamy College of Engineering, Karur, India
⁴ Electronics and Communication Engineering, K.Ramakrishnan College of Technology, Trichy, Tamilnadu, India

^* Corresponding author: kiruthikavlsi@gmail.com

Abstract

Human-wildlife conflict is the term used to describe when human activity results in a negative outcome for people, their resources, wild animals, or their habitat. Human population growth encroaches on wildlife habitat, resulting in a decrease in resources. In particular habitats, there are numerous forms of human and domesticated animal death or injury as a result of conflict. Farmers and the animals that invade farmland suffer greatly as a result. Our project’s primary objective is to lessen human-animal conflict and loss. The embedded system and image processing technique are utilized in the project. Python is used to perform image processing techniques like segmentation, statistical and feature extraction using expectation maximization, and classification using CNN. The classification is used to determine whether the land is empty or if animals are present. A buzzer sound is produced, a light electric current is passed to the fence, and a message alerting the farmer to the animal’s entry into the farmland is transmitted. This prevents the animal from entering the field and enables the landowner to take the necessary steps to get the animal back to the forest. The result is serially sent to the controller broad from the control board.