An IoT Solutions for Ungulates Attacks in Farmland

Abstract

Agriculture is considered to be a significant contributor to the global financial system and human diets. It has been recognized as the country’s primary source of income and employment. So, it’s really important to protect crops from various dangerous hazards, such as diseases, insects, bird and animal attacks, high atmospheric temperature, etc., and also from weak irrigation systems, poor soil quality, weeds management, etc. Specific insect attacks and diseases have long been a primary crop sector concern. Computer vision (CV)-based automatic insect and disease detection methods are used in smart farming systems because of their high cost-effectiveness and efficient automation. This paper gives an overview of the use of Machine Learning (ML), Deep Learning (DL), and the Internet of Things (IoT) in agriculture to protect crops from various dangerous hazards and proposes an automatic Animal-Repelling System (ARS). This study implements a system based on IoT to protect crops from animals. The proposed low-cost agricultural field protection system helps farmers to protect their crops and increase production yield and income.