Artificial intelligence and agriculture 5. 0

Abstract

Use of Artificial Intelligence and Robotics in agriculture is called as Agriculture 5.0 Disruptive technology should help in solving the social needs. Rogers suggest to develop human centric “ Ubiquitous Computing ” solution, for specific domain (agriculture production). Crop yield prediction (CYP) is vital to address the ever growing demand of food requirements of burgeoning world population and to prevent starvation. Artificial Intelligence can offer effective and practical solution for the problem. Machine Learning (ML) and Deep learning (DL) have been evaluated. Machine Learning models (using python, R, Seaborn) have been experimented in this paper. Data of crop yield is used for model evaluation, which includes horticultural product (Banana), cash crop (Sugarcane), food crop (Rice), for kharif, rabi season (Dataset of Tamil Nadu and US region); Future research could combine remote sensing data and machine learning to predict the yield (using google earth engine). Better accuracy in crop prediction is possible when vital data like soil moisture content (ground level, root level and extreme ends of the field), 14 micro nutrients of soil is made available, for many seasons.