Research on Sustainable development of green energy and manufacturing in smart agriculture based on big data analysis

In response to global environmental changes, smart agriculture (SA) has emerged as a means of boosting agricultural output and the income of low-income communities. This article assesses the efficacy of SA strategies for advancing sustainable agriculture to ensure the availability of safe, nutritious food globally. It looks at how different aspects of SA work together to further the goals of sustainable agriculture. A deeper understanding of the intricate agricultural ecosystems is required to control the expanding issues in agricultural output. It's possible with today's digital technology, which can constantly monitor the physical surroundings and generate massive volumes of data at breakneck speeds. Farmers and companies might enhance output via the study of data. While big data analysis has been widely used in other sectors, it is still uncommon in agriculture. The study aims to examine current agricultural studies and research, which applies the newest big data analysis practices to deal with many important green energy challenges in smart agriculture by analyzing big data (GE-SABDA). Data analytics and the internet could boost safety and product quality while reducing production downtime. The experimental results show the proposed method achieves a rising green energy level ratio of 94.3 %, overall accuracy of smart agriculture ratio of 90.7%, crop disease identification ratio of 98.1 %, daily productivity ratio of 450, and production wastage ratio of 18.5% compared to other methods.