The growing demand for food security and environmental sustainability necessitates the adoption of more sustainable farming methods. This research involved Artificial Intelligence (AI) and Internet of Things (IoT) integration in the agricultural practices toward improving monitoring, management, and decision-making efficiency. The study is based on the real time data collection and analysis in order to revolutionize sustainable agriculture through the automatic decision making processes.Environmental data is collected by IoT sensors, in this case, soil moisture detectors and weather stations, and is sent then to the hands of AI systems for analysis that yields actionable insights. A result of these insights is that information about irrigation, fertilization, pest control, etc are made available for making informed decisions thus ensuring resource efficiency and sustainable farming. Incorporating AI and IoT maximises such potential in terms of productivity, waste reductions and aids in ecological conservation.Nevertheless, adoption of such technologies is hampered by the lack of infrastructure in rural areas and technology support required to overcome these challenges. It is important to address these issues for the widespread implementation and effectiveness. The goal of this research is essentially to demonstrate the potential of AI and IoT to support sustainable agricultural practices based on practical solutions for effective ecosystem management. In this study we provide proof positive of both the revolutionary potential of AI and IoT to enable agriculture's sustaining into the future as a global supplier of food supply and the resilience of the environment.
Soy et al. (2025) studied this question.