Abstract
Wireless sensor network is implemented and communicated with the cloud through IPv6. The entire system is applied to precision irrigation systems for lettuce crops in Ecuador. The main objective is to provide optimization system for irrigation water for productive purposes and providing crops with the adequate amount of water needed for surviving and producing. To do that the system has a data acquisition system by sensors and this data is stored in web services. By improving the irrigation system crops can be planted throughout the year including summer, the system has a remarkable result for efficient water savings and lettuce crops.
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References
Sartillo Salazar, E., Hernández Hérnandez, J.C., Caporal, R.M., Martinez Hernández, H.P., Ordoñez Flores, R.: Maximum expectation algorithm and neuronal network base radial applied to the estimate of an environmental variable, evapotranspiration in a greenhouse. In: 2014 International Conference on Electronics, Communications and Computers (CONIELECOMP), Cholula, pp. 225–230 (2014). https://doi.org/10.1109/CONIELECOMP.2014.6808595
Bennis, N., et al.: Greenhouse climate modelling and robust control. Comput. Electron. Agric. 61(2), 96–107 (2008). https://doi.org/10.1016/j.compag.2007.09.014
Food and Agriculture Organization. http://www.fao.org/docrep/009/x0490s/x0490s00.htm
Ponce, J.: Ministerio de Agricultura, Ganadería, Acuacultura y Pesca. Plan Nacional de Riego y Drenaje 2012–2026, p. 5
Ministerio de Coordinación de la Producción, Empleo y Competitividad. Agenda de Transformación Productiva 2010–2013, p. 137
Singh, K., Kumar, P., Singh, B.K.: An associative relational impact of water quality on crop yield: a comprehensive index analysis using LISS-III sensor. IEEE Sens. J. 13(12), 4912–4917 (2013). https://doi.org/10.1109/JSEN.2013.2276760
Lee, J., Kang, H., Bang, H., Kang, S.: Dynamic crop field analysis using mobile sensor node. In: 2012 International Conference on ICT Convergence (ICTC), Jeju Island, pp. 7–11 (2012). https://doi.org/10.1109/ICTC.2012.6386766
Vijayabaskar, P.S., Sreemathi, R., Keertanaa, E.: Crop prediction using predictive analytics. In: 2017 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC), Melmaruvathur, pp. 370–373 (2017). https://doi.org/10.1109/ICCPEIC.2017.8290395
Ponce-Guevara, K.L.: GreenFarm-DM: a tool for analyzing vegetable crops data from a greenhouse using data mining techniques (first trial). In: IEEE Second Ecuador Technical Chapters Meeting (ETCM), Salinas 2017, pp. 1–6 (2017). https://doi.org/10.1109/ETCM.2017.8247519
Sahu, S., Chawla, M., Khare, N.: An efficient analysis of crop yield prediction using Hadoop framework based on random forest approach. In: 2017 International Conference on Computing, Communication and Automation (ICCCA), Greater Noida, pp. 53–57 (2017). https://doi.org/10.1109/CCAA.2017.8229770
Rosero-Montalvo, P.D., et al.: Data visualization using interactive dimensionality reduction and improved color-based interaction model. In: Biomedical Applications Based on Natural and Artificial Computing. IWINAC. LNCS, vol 10338. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59773-7_30
Velasquez, L.C., Argueta, J., Mazariegos, K.: Implementation of a low cost aerial vehicle for crop analysis in emerging countries. In: IEEE Global Humanitarian Technology Conference (GHTC), Seattle, WA, pp. 21–27 (2016). https://doi.org/10.1109/GHTC.2016.7857255
Bhanu, B.B., Rao, K.R., Ramesh, J.V.N., Hussain, M.A.: Agriculture field monitoring and analysis using wireless sensor networks for improving crop production. In: 2014 Eleventh International Conference on Wireless and Optical Communications Networks (WOCN), Vijayawada, pp. 1–7 (2014). https://doi.org/10.1109/WOCN.2014.6923043
Ma, X., Luo, W.: The analysis of 6LowPAN technology. In: Pacific-Asia Workshop, vol. 1, pp. 963–966, 19–20 December 2008 (2008)
Zhang, Y., Li, Z.: IPv6 conformance testing: theory and practice. In: Test Conference Proceedings ITC 2004, pp. 719–727, 26–28 October 2004 (2004)
Accettura, N., Grieco, L., Boggia, G, Camarda, P.: Performance analysis of the RPL routing protocol. In: 2011 IEEE International Conference on Mechatronics (ICM), pp. 767–772, 13–15 April 2011 (2011)
Nuñez, D.: Estudio para la migracion de IPv4 a IPv6 para la empresa proveedora de internet Milltec S.A. Quito, Ecuador. EPN, p. 22 (2009)
Aslam, M., Rea, S., Pesch, D.: Service provisioning for the WSN cloud, pp. 962–969 (2012)
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Maya-Olalla, E. et al. (2020). A New Approach of Service Platform for Water Optimization in Lettuce Crops Using Wireless Sensor Network. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_1
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