Abstract
Smart irrigation system requires long-distance transmission, low power consumption and accurate data analysis for precise irrigation and water conservation. In this paper, we designed the long-distance transmission and low power consumption smart irrigation node with SoC CC1310, and the system applies 6LoWPAN in smart irrigation system to implement low power networking and transmission. This paper also proposes an improved fuzzy algorithm for smart irrigation, which determines irrigation strategies. The software design of smart irrigation node is based on Contiki operating system, and we compared the shortest path networking method with the default networking method ETX in Contiki, when the amount of nodes increase to 50, the shortest path networking method could save 10% energy compare with the ETX method.
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Xiang, C., Yang, P., Xuangou, W., He, H., Xiao, S.: QoS-based service selection with lightweight description for large-scale service-oriented internet of things. Tsinghua Sci. Technol. 20(04), 336–347 (2015)
Zhang, B., Ma, X.-X., Qin, Z.-G.: Security architecture on the trusting internet of things. J. Electr. Sci. Technol. 9(04), 364–367 (2011)
Kumar, V., Oikonomou, G.: Digital investigations for IPv6-based wireless sensor networks. Digit. Invest. 11(4), 66–75 (2014)
Chang, K.-D., Chen, J.-L., Chao, H.-C.: Prototype for integrating internet of things and emergency service in an IP multimedia subsystem for wireless body area networks. ZTE Commun. 12(03), 30–37 (2014)
Viani, F., Robol, F., Polo, A., Giarola, E., Massa, A.: Localization strategies in WSNs as applied to landslide monitoring. In: American Geophysical Union Fall Meeting 2013, vol. 13, pp. 107–107. San Francisco (2013)
Benedetti, M., Ioriatti, L., Martinelli, M., Viani, F.: Wireless sensor network: a pervasive technology for earth observation. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 3(4), 488–497 (2010)
Anand, K., Jayakumar, C., Muthu, M., Amirneni, S.: Automatic drip irrigation system using fuzzy logic and mobile technology. In: Technological Innovation In ICT for Agriculture and Rural Development IEEE 2015, pp. 54–58. Chennai (2015)
Zhao, Y., Bai, C., Zhao, B.: An automatic control system of precision irrigation for City Greenbelt. In: 2nd IEEE Conference on Industrial Electronics and Applications 2007, pp. 2013–2017 (2007)
Hamouda, Y.E.M.: Smart irrigation decision support based on fuzzy logic using wireless sensor network. In: International Conference on Promising Electronic Technologies 2017, pp. 109–133. Deir El-Balah (2017)
Alfin, A.A., Sarno, R.: Soil Irrigation fuzzy estimation approach based on decision making in sugarcane industry. In: International Conference on Information & Communication Technology and System, pp. 137–142 (2017)
Qiu, R., Du, T., Kang, S.: Root length density distribution and associated soil water dynamics for tomato plants under furrow irrigation in a solar greenhouse. J. Arid Land 9(05), 637–650 (2017)
Pishgar-Komleh, S.H., Akram, A.: Variability in the carbon footprint of open-field tomato production in Iran - a case study of Alborz and East-Azerbaijan provinces. J. Clean. Prod. 142, 1510–1517 (2017)
Alboghdady, M.A.: Nonparametric model for measuring impact of inputs density on Egyptian tomato production efficiency. Int. J. Food Agric. Econ. 2(4) (2014)
Raheli, H., Rezaei, R.M.: A two-stage DEA model to evaluate sustainability and energy efficiency of tomato production. Inf. Process. Agric. 4(4) (2017)
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Jiang, X., Yi, W., Chen, Y., He, H. (2018). Energy Efficient Smart Irrigation System Based on 6LoWPAN. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11067. Springer, Cham. https://doi.org/10.1007/978-3-030-00018-9_28
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DOI: https://doi.org/10.1007/978-3-030-00018-9_28
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