Smart Farming with application of Model-Based Design, Big Data & Machine Learning
Agriculture is recognised as a craft that has much to gain by harnessing the Internet of Things. Climate change is already affecting agriculture, with effects inequitably distributed across the world. The disparity in diverse atmospheric and soil parameters like temperature, humidity, pH, electrical conductivity, light intensity, air pressure and atmospheric gases can have an adverse effect on crop yields and disrupt the balance of crops in a region. The Internet of Things Technology with the help of Model-Based Design (MBD), Big Data Analytics and Machine Learning can provide effective agriculture service by constant monitoring, processing, communicating, visualising, controlling, storing and reporting the condition of the crops. In this paper, we have made an attempt to provide a novel strategic framework and a computationally intelligent prototype which takes effective decisions based on Machine Learning Algorithms and Big Data Analytics. By making use of Model-Based Design paradigm we have tried to provide effective solutions with minimal manual intervention as the system synchronously communicates bi-directionally to provide alternate optimised decisions to the agronomists. The deployment of Big Data Analytics along with Machine Learning has helped to put a check on the ever fluctuating parameters; thereby controlling them if they exceed beyond a particular threshold.