IoT Based Gadgets to Update a Moderate Condition of Farmer and Animal Detection in Farming Field

Abstract

(AI) and Internet of Things (IoT) technologies, aimed at advancing precision agriculture practices. This project unfolds in two distinct phases. The initial phase focuses on employing advanced deep learning algorithms for accurate animal detection. The effectiveness of these algorithms is validated through thorough training and real-world testing, demonstrating their capability to precisely identify animals. The subsequent phase transitions to the deployment of an intelligent irrigation system. This system utilizes ambient temperature and humidity data to dynamically adjust irrigation schedules, thereby conserving water and promoting sustainable farming practices. By integrating these two facets, the project aims to enhance early animal threat detection while simultaneously improving water management efficiency. This comprehensive approach is set to push the boundaries of smart farming, promoting both sustainability and productivity in agricultural practices.