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.
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