Abstract

 Farming has been a traditional, manual and labor-intensive industry, and it will continue to be so in the future. Agriculture is one of humanity's oldest businesses and practices. Extrinsic elements, comprising climatic parameters and general environmental variables, have strongly dictated crop yield and productivity. Disruptive technologies such as the Internet of Things (IoT), Big Data Insights, Artificial Intelligence (AI), Machine Learning (ML), etc., have significantly affected most every enumerated industry area. Farming based on the implementation of the above advancements leads to “Smart Farming”, also known as the “Green Revolution 4.0” in agriculture, which combines agricultural methodologies with technologies to accomplish desired processing efficiencies at manageable costs. The entire development is software-based and sensor-monitored from farm to hand-held devices, lowering overall costs, and increasing aggregate yield and ubiquity level, thereby enhancing user engagement. Predictive analytics for crops may certainly contribute to data-driven decision-making with the help of “failure prediction systems.” Climate conditions can be tracked and forecasted to help with forecasting, from seeding to development and delivery of the final crop to the consumer. An increase in global concerns about food safety, as a result of large-scale flood disasters, puts more pressure on smart farming methodologies. The study discusses more of the latest avenues of research and future trends in smart farming with case studies about Indian states. The work also examines major disruptive technologies that govern agricultural phenomena in the twenty-first century.