SUSTAINABLE PRECISION AGRICULTURE: INTEGRATING ARTIFICIAL INTELLIGENCE AND IOT FOR OPTIMIZED GREEN FARMING PRACTICES

Agriculture is the backbone of Indian economy. It is evolved in due course of time. The purpose of this study is to assess how well internet of things (IoT) and artificial intelligence (AI) technologies can improve precision farming methods and encourage resource sustainability. The goal of the project is to determine the obstacles farmers have when implementing these innovations and to examine the economic and environmental effects of incorporating these technologies into farming, with an emphasis on yield enhancement and resource conservation. Method: To investigate the connection between AI, IoT, and sustainable farming results, data were collected from a sample of 225 farmers via trials and sensor readings using a quantitative descriptive research technique. Descriptive statistics, independent t-tests, and regression analysis were among the statistical techniques used to evaluate how AI and IoT affected productivity and environmentally friendly agricultural methods. Result: The results reveal a strong positive correlation, with the regression model indicating that IoT and AI play a substantial role in sustainable agriculture and higher production, accounting for around 55.2% of the variation in results. The model's effectiveness is further supported by the ANOVA findings, which show that smart farming, AI, and IoT have a major influence on green agricultural practices (p < 0.001). It is found that AI and IoT have a great deal of contribution towards sustainable agriculture by increasing sustainability and production. However, it is significant to address certain challenges for wider acceptance and scalability across many agricultural groups.