Towards An Intelligent Farmland Intrusion Detection And Vandalization Prevention System Using Deep Learning And Raspberry Pi

Abstract

Farming is one of the most lucrative business in the world and one of the largest employers of labour worldwide. In addition, farming has been able to guarantee food security and increase the GDP of many countries. However, this sector in recent times have been threatened by conflicts between farmers and herders especially in developing countries such as Nigeria where loss of lives and properties have been recorded in many states. This emerging problem has brought to the fore the need for efficient intelligent farmland intruder detection and vandalization prevention system. Existing intruder detection and vandalization prevention systems do not have the capability to detect, recognize, prevent and alert the farmer in real time of an intrusion.Hence, this paper proposes the development of an intelligent intruder detection, recognition and vandalization prevention system using a Faster Regions with Convolution Neural Network (faster R-CNN) for efficient intruder recognition, IR sensors for intruder detection and Rasberry pi as hardware for efficient deployment. The successful development and deployment of this system will not only prevent vandalization of crops, minimize clashes between farmers and herders, but also, save lives and properties and guarantee food security.