Artificial Intelligence Impact on the Global FarmingSystem Concerning Agriculture: A SystematicReview

Abstract

The purpose of this study is to investigate how the use of AI in agriculture has changed farming around the world. Incorporating AI technologies into agriculture can radically alter current farming methods and solve significant problems like boosting output, maximizing efficiency, and safeguarding the future of food production. After a thorough search and selection process, 4136 articles from the Scopus database were applicable. The chosen research included a broad spectrum of AI applications in agriculture, from keeping tabs on crops and livestock to predicting crop yields and detecting diseases. According to this analysis's conclusions, AI-based technologies have shown considerable promise in enhancing different facets of the agricultural system. Data can be collected, analyzed, and decisions made in real-time with the help of these technologies thanks to cutting-edge algorithms, machine learning, and big data analytics. They aid farmers by giving them helpful information and suggestions, which improves operational efficiency and allows for precision agriculture. The paper also emphasizes the potential of AI in supporting sustainable farming methods, minimizing adverse effects on the environment, and maximizing the distribution of available resources. It is possible to reduce input waste and environmental concerns using AI-driven systems that allow for precise irrigation, targeted pesticide application, and optimum nutrient management. The assessment also highlights some of the difficulties and restrictions of using AI in farming. Data privacy and security, technology infrastructure, farmer adoption, and the digital gap are all issues that must be addressed. Future research and development should focus on ethical concerns, algorithm bias, and the requirement for interpretability and transparency in AI decision-making. The promise of AI to revolutionize agriculture is highlighted in this extensive assessment of the field's literature. The results emphasize the importance of ongoing study, regulatory support, and stakeholder collaboration to maximize the benefits of AI in agriculture while tackling associated obstacles. This analysis adds to our knowledge of the potential of AI to improve farming methods worldwide in the future. The study's primary focus was AI to create a more advanced farming system for the global economy. Artificial intelligence has taken on the difficult task of developing new services and methods to improve agricultural output. The meta-analysis examined information about the worldwide framing system and AI. We gathered data and ran it through the PRISMA Model to determine whether a particular domain was appropriate for a documentation review.