Abstract
Smart farming is a modern way to bring ease in the field of agriculture with less manpower and more modern equipment. To know the features and characteristics of various crop types, machine learning techniques can be used. In these past few years, it is developed and used effectively in various fields. Machine learning is a booming and challenging research field in agricultural data analysis. This paper uses sensing parameters like PH, contents of soil, temperature, rainfall and humidity. The project emphasis, machine learning-based real-time analytics are performed to suggest the most suitable crop, pesticides and technique. To get a better classification of crops, logistic regression and support vector machines (SVM) are used. The outcome demonstrates that the proposed technique provides 20% more accuracy than the existing algorithm. The complete project comes up with the idea to help farmers to start with zero farming knowledge and helps them to yield the maximum profit.
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Rohit, R.V.S., Chandrawat, D., Rajeswari, D. (2021). Smart Farming Techniques for New Farmers Using Machine Learning. In: Mahapatra, R.P., Panigrahi, B.K., Kaushik, B.K., Roy, S. (eds) Proceedings of 6th International Conference on Recent Trends in Computing. Lecture Notes in Networks and Systems, vol 177. Springer, Singapore. https://doi.org/10.1007/978-981-33-4501-0_20
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DOI: https://doi.org/10.1007/978-981-33-4501-0_20
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