Case Study: Hyper Automation In Agriculture

Currently, the global population is 8.2 billion and is estimated to reach 10 billion by 2050. This will lead to a doubling of demand for food, feed, fiber, and biofuels compared with the same demand in 2005. Simultaneously, the agricultural sector needs solutions that are economically viable, environmentally sustainable, socially acceptable, and beneficial. Using new technologies, such as Hyperautomation, can help change farming practices. Hyperautomation, which is the combination of Artificial Intelligence (AI), Machine Learning (ML), Robotic Process Automation (RPA), data analytics, and other latest technologies, is used to optimize the productivity, efficiency, and sustainability of agricultural practices. Technologies help meet the rising demand for food, which will lead to increases in agricultural productivity and income while enhancing the efficiency and effectiveness of agriculture. Moreover, it will lead to a transformation in farming systems. This section discusses the use of Hyperautomation in agriculture, which can revolutionize farming processes. Hyperautomation can enhance decision-making and optimal resource usage by automating processes such as crop monitoring, irrigation, pest control, and harvest prediction. Additionally, Hyperautomation can enhance the productivity and adaptability of farming systems while reducing waste by reducing inefficiencies and encouraging informed strategies. It can also be crucial for digitizing crop certificates, which can help in speedy crop insurance claims and damage assessment during natural disasters to better support farmers. Technologies such as AI, drones, and blockchain not only help the sustainable longevity of the Agri sector but also assist in the realization of the UN SDGs, specifically, Zero Hunger, Decent Work and Economic Growth, Climate Action, Responsible Consumption and Production.