Abstract
Water is considered to be the most precious natural resource for agriculture in this twenty-first century. To avoid the scarcity of water we must have to use it precisely. For this task a smart irrigation recommendation system is the need of the hour. In this era of automation we may use technologies like machine learning and IoT to build a smart irrigation recommendation system for efficient water usage with nominal human intervention. Here, we propose an IoT based irrigation framework with machine intelligence. The intelligence is incorporated with various machine learning based regression and classification models. To make our proposed system even robust we have integrated the forecasted weather data using their available APIs. We use our own collected sensor data along with the NIT Raipur dataset to validate the effectiveness of this system. From all the experimentation, it is found that the proposed support vector regression (SVR) along with the KNN classifier trained system is very much effective for this challenging task.
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Acknowledgements
This work was supported and funded by Collaborative Research Scheme (CRS) of National Project Implementation Unit (NPIU), MHRD, Government of India. The authors wish to thank department of Computer Application, NIT Raipur for making available of the Crops dataset.
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Bhoi, A., Nayak, R.P., Bhoi, S.K., Sethi, S. (2021). Automated Precision Irrigation System Using Machine Learning and IoT. In: Udgata, S.K., Sethi, S., Srirama, S.N. (eds) Intelligent Systems. Lecture Notes in Networks and Systems, vol 185. Springer, Singapore. https://doi.org/10.1007/978-981-33-6081-5_24
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DOI: https://doi.org/10.1007/978-981-33-6081-5_24
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