Machine Learning-Based Intrusion Detection System For Space Monitoring : Case Study Of Farming In Benin

Abstract

The Internet of Things (IoT) is one of the major tools of the new era of digital transformation. Through the Internet of Things, we are looking forward to exploring the new technologies in the digital world and how they help in improving the real world. In this work, we provide an overview of the approach used to deploy a surveillance system for monitoring any indoor space in general and specifically for agricultural spaces. The entire process starts after motion detection by motion sensors using Machine Learning techniques. This requires coverage and response processing algorithms implemented in the electronic chain. The electronic part of the system relates to microcontrollers, sensors and communications between them. A mobile application has been created to allow competent authorities to receive alerts for real-time intervention with the aim of preventing the destruction of crops slaughtered near herds passage. We have introduced the monitoring system’s synoptic diagram and its operation along with the power modules description. Prototype has been designed and performance evaluation has been performed to show the system is responsive most of time.