An improved low-carbon intelligent agriculture system with energy optimization principles using wireless IoT environment

A low-carbon agricultural plan and intelligent agriculture control system are designed and completed with a green economy to foster the significant expansion of green resources and environmental assets. This research employs a fixed-effect panel model to examine the farming cumulative energy savings in 11 cities and regions along the Yamuna Tributary Commercial Region, focusing on both static and dynamic factors. The directional linear equation and the Malmquist-Luenberger (ML) indicator are the key analytical tools. Unlike conventional techniques, regression analysis using cross-sectional data is the primary tributary. Research has found that a 5.9% decrease in the literacy rate of the working force had a large impact on farming energy efficiency and that for each 1% rise in crop losses, farm energy efficiency would decrease by 0.487%. In addition to mitigating the detrimental effects of industrial design and mechanization on agricultural output, this effort aids in the advancement of smart city design. This activity paves the way for cutting-edge technology by encouraging people to move to cities, educating the workforce, and giving money to the agricultural sector. The ability of proposed model gives the smart agriculture system with intelligent control principles and energy optimization principles in the deployed wireless-IoT platform. On this research problem, this paper contributes to new knowledge by approaching agricultural energy efficiency from a green economy perspective, conducting regression analyses of panel data on the most important influencing factors using the advanced statistical analysis tool Eviews, and then drawing the conclusion from the evaluation of metrics that affect farming energy efficiency in our nation. Enhancing productivity while also fostering long-term growth in the agricultural ecosystem is crucial. It contributes for smart and green technologies adaptation in agriculture filed.