Examining the Applications of Artificial Intelligence in Agriculture

Abstract

In contemporary times, there has been a discernible incorporation of Artificial Intelligence (AI) applications inside the agricultural sector. The driving force behind this development stems from the enduring challenges faced by the agricultural sector. These challenges encompass concerns such as inadequate soil treatment, the prevalence of diseases and pests, the need for comprehensive data analysis, suboptimal agricultural productivity, and the disparity in understanding between conventional farming methods and advanced technology. The fundamental proposition underlying the involvement of artificial intelligence (AI) in the agricultural sector is based on its exceptional adaptability, superior performance capacities, precision in decision-making, and cost-efficiency. This study offers a comprehensive examination of artificial intelligence (AI) implementations in several domains of agriculture, encompassing soil management, crop management, weed control, and disease management. Significantly, the aforementioned statement underscores the importance of acknowledging both the positive attributes and constraints inherent in these artificial intelligence (AI) applications, thereby illuminating their capacity to bring about transformative changes in agricultural methodologies. Moreover, this research explores the application of expert systems in the agricultural domain, revealing its potential to bridge the knowledge deficit and enhance production in the farming sector. The potential for sustained growth and increased production in the agriculture industry is promising through the combination of AI's adaptability and the knowledge amplification of expert systems.