Nowadays, we have become so dependent on Big Data Analytics that it is difficult to think of almost any industry where it has not shown its presence. Be it in urban development to control traffic, using sensors to detect heavy traffic; or in healthcare department where deadly diseases can be detected early. Even in the entertainment industry, analytics plays a vital role to increase Television Rating Point (TRPs) and improve shows. In sports arena to increase ticket sales and other related business. All of these show its presence in urban areas. However, if properly utilized, Artificial Intelligence (AI) has much to offer in farming too. Using Big Data proves to be a smarter farming technique than the traditional way.
Using Artificial Intelligence in Smart Farming
Big data helps farmers speed up plant-growth and increase their yield, and it allows scientists to engineer plants that will grow in harsh climates to prevent famine. Artificial Intelligence as a tool to kill weeds, harvest better crops, and produce better yield. Drones, intelligent monitoring systems are the methods that enhance farming techniques. Smarter farming technique calls for some of the following prerequisites: Facial/Image recognition. This technology that is popular in smartphones has helped easy monitoring of crops, plants with minimal interaction. Next new wave comes with the introduction of drones in fields. Drones facilitate in-depth field analysis, easy and efficient crop spraying and crop monitoring. Crop Health monitoring is an automated detection and analysis technology that consists of 3D laser scanning which increases data collection volume, which enhances accuracy of analysis and providing better results. Satellite imaging helps in financial security and crop insurance.
Application of Artificial Intelligence in Smart Farming
Analyzing plant data has helped agricultural scientists to develop crops that can grow in any environment. Chemically engineered seeds designed using big data and artificial intelligence could put an end to world hunger. Even in India, smarter farming technique has started to emerge. SatSure, a data analytics company uses machine learning and parallel computing techniques, to resolve complex relationships and get insights into the crop phenology. Microsoft has developed a multivariate agricultural commodity price forecasting model to predict future commodity arrival and the corresponding prices.
Technologies aided by artificial intelligence help improve efficiency and address challenges including, crop yield, soil health and herbicide-resistance. Wide adoption of robotics in the dairy farming is evident where thousands of milking robots are already operating. But extensive usage of smart farming technique using AI applications will be critical as agriculture is impacted by environmental factors that cannot be controlled unlike other industries where risk is easier to model and predict.
