Integrating IoT and AI for Precision Agriculture

Abstract

There is a technological revolution in agriculture that is being brought about by the use of Internet of Things (IoT) and Artificial Intelligence (AI) to maximize productivity, resource management and sustainability. Precision agriculture is an interconnected system of sensors, drones, and algorithms based on data and real-time monitoring of the conditions of soil, crop growth, and environmental parameters. This combination of the sensing abilities of IoT with the predictive and decision-making capabilities of AI has allowed farmers to base their decisions regarding irrigation, fertilization, pests, and yield projections on actual data. The paper discusses the intersection of IoT and AI technologies in the field of precision agriculture through the system architecture, data analytics, and applications. Among the main breakthroughs, there are mentioned machine learning-based crop disease identification, smart irrigation, and weather and yield predictive analytics. Issues such as lack of interoperability of data and connectivity constraints and cyber security are examined critically. The researchers conclude that the synergies between IoT and AI not only contribute to increasing the agricultural productivity but also lead to the development of a sustainable environment in terms of the wasted inputs and overuse of resources. This convergent solution is a shift of the conventional agricultural system to smart, adaptive agricultural systems that are in line with global food security and sustainability concerns.