Abstract
In recent times, the amount of data generated by the IoT devices is very huge and the traditional databases do not have enough storage space. So the need for cloud storage becomes essential. Data mining techniques are used to analyze this big amount of data available in cloud. The study of smart agriculture system has cloud-based data analytics with IoT as a major role. The role of Information and Communication Technologies in the field of smart agriculture model is very important to extract the information from the field. In this paper, the IoT device records the data from the agriculture field and stored in the cloud database. Data analysis is done on the data available in cloud, and based on the data mining technique used, the prediction is performed. The predicted information is sent to the farmer through a mobile phone application. The main aim is to increase the production and reduce the cost of the products based on the predicted information.
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References
Sindhu MR, Pabshettiwar A, Ghumatkar KK, Budhehalkar PH, Jaju PV (2012) E farming. Int J Comput Sci Inform Tech 3(2):3479–3482
Wang Q, Terzis A, Szalay A (2010) A novel soil measuring wireless sensor network. IEEE Trans Instrum Measur 1:412–415
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Anand Prabu, P., Jayashree, L.S. (2020). A Smart Agricultural Model Using IoT, Mobile, and Cloud-Based Predictive Data Analytics. In: Kumar, L., Jayashree, L., Manimegalai, R. (eds) Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications. AISGSC 2019 2019. Springer, Cham. https://doi.org/10.1007/978-3-030-24051-6_37
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DOI: https://doi.org/10.1007/978-3-030-24051-6_37
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-030-24051-6
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