Recommender System with Machine Learning and Artificial Intelligence

5A Machine Learning Approach to Recommend Suitable Crops and Fertilizers for Agriculture

Govind Kumar Jha¹*, Preetish Ranjan² and Manish Gaur³

¹ Dept. of CSE, BCE Bhagalpur, Bhagalpur, Bihar, India

² Dept. of CSE, Amity University Patna, Patna, Bihar, India

³ Centre for Advanced Studies, AKTU, Lucknow, UP, India

Abstract

Agriculture and allied sectors contribute more than 53% of GDP in India and 50% of the workforce is involved with it. Besides being the first and foremost contributor to the economic development of India, this sector is facing many problems and has the lowest per capita productivity. Despite the huge size of the agricultural sector, yields per hectare of crops are low compared to international standards. People are quite reluctant to choose it as their occupation and sometimes confused about their investment in agriculture. This is due to lack of information about their land, nutrition in the soil, level of water, composition of fertilizers required by soil and many others. This kind of very particular information may be availed to farmers through the internet and communication technology. By applying machine learning-enabled programs may provide rich insights for farmer decision support. A recommender system based on a machine learning approach may be developed which could suggest the type of crop and the fertilizer may be used to increase their productivity and consequently, their income.

Keywords: Machine learning, soil health card, recommendations, random ...