Artificial Intelligence Applications in Agricultural Mechanization

Abstract

Agricultural automation has become a crucial and rapidly evolving field globally. With the world's population, expanding at an accelerated pace, the demand for food production is increasing significantly. This growing need is being unmet by traditional farming practices, which results in the overuse of dangerous chemicals that deteriorate soil quality and eventually make land unusable. This study looks at a number of automation technologies, including the Internet of Things, wireless communication, machine learning, artificial intelligence, and deep learning, that may help with significant agricultural issues. These cutting-edge methods can successfully address problems like agricultural diseases, poor storage management, excessive pesticide use, weed control, inefficient irrigation, and water resource management. The pressing need to mitigate the negative impacts of pesticide use, regulate irrigation, reduce pollution, and manage environmental effects on agriculture is emphasized. The automation of farming processes has demonstrated improvements in agricultural yield and soil fertility. In order to present a summary of recent developments in agricultural automation, this paper examines previous research. It also presents a suggested method for botanical farms that makes use of IoT technologies for automated irrigation and flower and leaf identification.