Abstract

AI plays a crucial role in agricultural management by enabling precise agricultural practices. By leveraging technologies such as IoT, data mining, machine learning and deep learning, it helps farmers make data-driven decisions for optimal crop health and productivity. These technologies, such as seasonal prediction models, AI sensors for herbicide optimization, and AI-powered drones for real-time monitoring, contribute to improved agricultural safety, lower toxin levels in food, and higher crop yields. Additionally, AI bots address labor shortages by efficiently harvesting crops and controlling weeds, ultimately increasing productivity. Integrating AI into operations not only increases efficiency, but also ensures sustainable practices, profitability and environmental protection. To further strengthen trust in AI solutions for precision agriculture, measures on transparency, accountability, fairness and data security are recommended. This technology improves decision-making through data-driven insights into weather patterns, soil conditions and plant health. This results in better yield prediction, timely pest and disease control interventions and overall improved crop management. This results in higher yields, lower operating costs and better risk management for farms. Ultimately, it helps increase profitability and sustainability in the long term.

Keywords: Artificial intelligence, Agriculture, Productivity