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@article{156090,
        author = {Manasa M R and Dr. Yuvaraju B.N },
        title = {E-FARMING: COMPLETE SUPPORT SYSTEM FOR SMART AGRICULTURE},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {2},
        pages = {823-829},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156090},
        abstract = {In our country, India agriculture it’s the backbone of the county’s monetary development. In our county, 1/3rd of the population is based directly or indirectly depending on agriculture. Agriculture plays a crucial function in human lifestyles. In our agriculture for crop prediction and yield prediction, the use of Machine Learning strategies has come to be more efficient. Yield prediction performs an important position in agriculture. Nowadays all people beginning farming should recognize simple facts about the rural place, plants to be sown, what the necessities desired for agriculture we are thinking about our historical records and related attributes which include Temperature, climatic situations, soil, and locality. For yield prediction soil additionally, plays a crucial role in farming. In this research study, we've got proposed a system to help farmers with smart farming and agriculture. We have designed the machine to crop yield prediction with the use of machine learning strategies. We are predicting the yield of two major crops grown in our county paddy and ragi and we've gathered datasets from the Mysore agriculture department. This proposed device is designed to work as actual-time software and is relevant for a couple of regions we are making use of supervised classification strategies consisting of KNN, Naïve Bayes, and Decision trees algorithm, and those anticipated results are displayed in the form of GUI.},
        keywords = {Agriculture, Smart Farming, Machine Learning, Crops, Yield prediction, KNN. Naïve Bayes, Decision tree.},
        month = {},
        }