Abstract
The sensor-cloud technology alleviates the restrictions of the traditional wireless sensor networks (WSNs) in terms of storage, computation, and scalability by integrating WSNs with cloud computing. In recent years, sensor-cloud technology is increasingly applied to various real-world applications, especially in agriculture irrigation. With the powerful computing and storage sources, the sensor-cloud enables the massive on-field sensing data to be processed efficiently. Furthermore, the virtualization technology allows multiple clients, typically farmers, to share the same infrastructure resources at a low cost. In this paper, we propose a novel agriculture irrigation system by applying the sensor-cloud technology into the traditional sprinkler irrigation. Targeting the practical irrigation scenes, we illustrate the specific work pattern of the proposed system. Finally, compared with the conventional WSN-based scheme, the simulation results show that our system achieves about 31.06%–41.24% decrease in energy consumption.
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References
Li, Y., Bai, G., et al.: Development and validation of a modified model to simulate the sprinkler water distribution. Comput. Electron. Agric. 111, 38–47 (2015)
Elijah, O., Rahman, T.A., et al.: An overview of Internet of Things (IoT) and data analytics in agriculture: benefits and challenges. IEEE Internet Things J. 5(5), 3758–3773 (2018)
Corke, P., Wark, T., et al.: Environmental wireless sensor networks. Proc. IEEE 98(11), 1903–1917 (2010)
Malaver, A., Motta, N., et al.: Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases. Sensors 15(2), 4072–4096 (2015)
Goap, A., Sharma, D., et al.: An IoT based smart irrigation management system using machine learning and open source technologies. Comput. Electron. Agric. 155, 41–49 (2018)
Roopaei, M., Rad, P., et al.: Cloud of things in smart agriculture: intelligent irrigation monitoring by thermal imaging. IEEE Cloud Comput. 4(1), 10–15 (2017)
Nikolidakis, S., Kandris, D., et al.: Energy efficient automated control of irrigation in agriculture by using wireless sensor networks. Comput. Electron. Agric. 113, 154–163 (2015)
Sudha, M.N., Valarmathi, M., et al.: Energy efficient data transmission in automatic irrigation system using wireless sensor networks. Comput. Electron. Agric. 78(2), 215–221 (2011)
Ojha, T., Misra, S., et al.: Sensing-cloud: leveraging the benefits for agricultural applications. Comput. Electron. Agric. 135, 96–107 (2017)
Alamri, A., Ansari, W.S., et al.: A survey on sensor-cloud: architecture, applications, and approaches. Int. J. Distrib. Sens. Netw. 9(2), 917–923 (2013)
Dinh, N., Kim, Y.: An energy efficient integration model for sensor cloud systems. IEEE Access 7, 3018–3030 (2018)
Misra, S., Chatterjee, S., et al.: On theoretical modeling of sensor cloud: a paradigm shift from wireless sensor network. IEEE Syst. J. 11(2), 1084–1093 (2014)
Chen, N., Zhang, X., et al.: Integrated open geospatial web service enabled cyber-physical information infrastructure for precision agriculture monitoring. Comput. Electron. Agric. 111, 78–91 (2015)
Navarro, H.H., Torres, S.R., et al.: A wireless sensors architecture for efficient irrigation water management. Agric. Water Manag. 15, 64–74 (2015)
Fazackerley, S., Lawrence, R.: Reducing turfgrass water consumption using sensor nodes and an adaptive irrigation controller. In: 2010 IEEE Sensors Applications Symposium (SAS), pp. 90–94. IEEE, Limerick (2010)
Coates, R.W., Delwiche, M.J., et al.: Wireless sensor network with irrigation valve control. Comput. Electron. Agric. 96, 13–22 (2013)
Yuriyama, M., Kushida, T.: Sensor-cloud infrastructure-physical sensor management with virtualized sensors on cloud computing. In: NBiS, vol. 10, pp. 1–8 (2010)
Dwivedi, R.K., Kumar, R.: Sensor cloud: integrating wireless sensor networks with cloud computing. In: 2018 5th IEEE Uttar Pradesh Section International Conference on Electrical. Electronics and Computer Engineering (UPCON), pp. 1–6. IEEE, Gorakhpur, India (2018)
Lim, Y., Park, J.: Sensor resource sharing approaches in sensor-cloud infrastructure. Int. J. Distrib. Sens. Netw. 10(4), 1–8 (2014)
Madria, S., Kumar, V., et al.: Sensor cloud: a cloud of virtual sensors. IEEE Softw. 31(2), 70–77 (2013)
Kim, K., Lee, S., et al.: Agriculture sensor-cloud infrastructure and routing protocol in the physical sensor network layer. Int. J. Distrib. Sens. Netw. 10(3), 1–13 (2014)
Tyagi, S., Obaidat, M.S., et al.: Sensor cloud based measurement to management system for precise irrigation. In: GLOBECOM 2017–2017 IEEE Global Communications Conference, pp. 1–6. IEEE, Singapore (2018)
Salvatierra, B.B., Montero, M., et al.: Development of an automatic test bench to assess sprinkler irrigation uniformity in different wind conditions. Comput. Electron. Agric. 151, 31–40 (2018)
Vuran, M.C., Akan, O.B., et al.: Spatio-temporal correlation: theory and applications for wireless sensor networks. Comput. Netw. 45(3), 245–259 (2004)
Lemos, M., Rabelo, R., et al.: An approach for provisioning virtual sensors in sensor clouds. Int. J. Netw. Manag. 29(2), 1–21 (2019)
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Zhang, M., Xiong, S., Wang, L. (2019). Sensor-Cloud Based Precision Sprinkler Irrigation Management System. In: Guo, S., Liu, K., Chen, C., Huang, H. (eds) Wireless Sensor Networks. CWSN 2019. Communications in Computer and Information Science, vol 1101. Springer, Singapore. https://doi.org/10.1007/978-981-15-1785-3_14
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DOI: https://doi.org/10.1007/978-981-15-1785-3_14
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