Abstract
Internet of Things (IoT) technologies represent the future challenges of computing and communications. They can also be useful to improve traditional farming practices worldwide. Since the areas where agricultural land is located in remote places, there is a need for new technologies. These technologies must be suitable and reliable for communication over long distances and, at the same time, consume little energy. In particular, one of these relatively new technologies is the LoRa communication protocol, which uses long waves to work over long distances. This is extremely useful in agriculture, where the communicating areas are broad fields of crops and greenhouses. This study developed a greenhouse monitoring system based on LoRa technology, designed to work over long distances. The edge computing paradigms with a machine learning mechanism are proposed to analyze and control the state of the greenhouse, and in particular, to reduce the mount of data transmitted to the server.
The publication has been prepared with the support of the “RUDN University Program 5-100” (recipients A. Khakimov). For the research, infrastructure of the 5G Lab RUDN (Russia) was used.
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References
Chen, L., et al.: A LoRa-based air quality monitor on unmanned aerial vehicle for smart city. In: 2018 International Conference on System Science and Engineering (ICSSE), pp. 1–5, June 2018
General Electric.: What is edge computing? https://www.ge.com/digital/blog/what-edge-computing. Accessed 18 Apr 2019
He, Y., Yu, F.R., Zhao, N., Leung, V.C.M., Yin, H.: Software-defined networks with mobile edge computing and caching for smart cities: a big data deep reinforcement learning approach. IEEE Commun. Mag. 55(12), 31–37 (2017). https://doi.org/10.1109/MCOM.2017.1700246
Khakimov, A., Muthanna, A., Muthanna, M.S.A.: Study of fog computing structure. In: Proceedings of the 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), Moscow, Russia, 29 January–1 February 2018, pp. 51–54 (2018)
Perera, C., Qin, Y., Estrella, J.C., Reiff-Marganiec, S., Vasilakos, A.V.: Fog computing for sustainable smart cities: a survey. ACM Comput. Surv. 50(3) (2017). https://doi.org/10.1145/3057266
Taleb, T., Dutta, S., Ksentini, A., Iqbal, M., Flinck, H.: Mobile edge computing potential in making cities smarter. IEEE Commun. Mag. 55(3), 38–43 (2017). https://doi.org/10.1109/MCOM.2017.1600249CM
Suresh, V.M., Sidhu, R., Karkare, P., Patil, A., Lei, Z., Basu, A.: Powering the IoT through embedded machine learning and LoRa. In: IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings, vol. 2018, pp. 349–354. Institute of Electrical and Electronics Engineers Inc., January 2018. https://doi.org/10.1109/WF-IoT.2018.8355177
Carlin, A., Hammoudeh, M., Aldabbas, O.: Defence for distributed denial of service attacks in cloud computing. Procedia Comput. Sci. 73, 490–497 (2015). https://doi.org/10.1109/NORCHIP.2014.7004716
Nguyen Gia, T., et al.: Energy efficient wearable sensor node for IoT-based fall detection systems. Microprocess. Microsyst. 56, 34–46 (2018). https://doi.org/10.1016/j.micpro.2017.10.014
Rahmani, A.M., et al.: Exploiting smart e-Health gateways at the edge of healthcare internet-of-things: a fog computing approach. Future Gener. Comput. Syst. 78, 641–658 (2018). https://doi.org/10.1016/j.future.2017.02.014
Muthanna, M.S.A., Wang, P., Wei, M., Ateya, A.A., Muthanna, A.: Toward an ultra-low latency and energy efficient LoRaWAN. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART -2019. LNCS, vol. 11660, pp. 233–242. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30859-9_20
Dongare, A., et al.: Charm: exploiting geographical diversity through coherent combining in low-power wide-area networks. In: Proceedings of the International Conference on Information Processing in Sensor Networks, pp. 60–71 (2018)
Hammoudeh, M., Newman, R., Dennett, C., Mount, S., Aldabbas, O.: Map as a service: a framework for visualising and maximising information return from multi-modal wireless sensor networks. Sensors 15(9), 22970–23003 (2015)
Carlin, A., Hammoudeh, M., Aldabbas, O.: Intrusion detection and countermeasure of virtual cloud systems-state of the art and current challenges. Int. J. Adv. Comput. Sci. Appl. 6(6), 1–15 (2015)
Gia, T.N., Thanigaivelan, N.K., Rahmani, A.M., Westerlund, T., Liljeberg, P., Tenhunen, H.: Customizing 6LoWPAN networks towards internet-of-things based ubiquitous healthcare systems. In: NORCHIP 2014–32nd NORCHIP Conference: The Nordic Microelectronics Event. Institute of Electrical and Electronics Engineers Inc. (2015). https://doi.org/10.1109/NORCHIP.2014.7004716
Daraseliya, A.V., Sopin, E.S., Samuylov, A.K., Shorgin, S.Y.: Comparative analysis of the mechanisms for energy efficiency improving in cloud computing systems. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART -2018. LNCS, vol. 11118, pp. 268–276. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01168-0_25
Sopin, E.S., Daraseliya, A.V., Correia, L.M.: Performance analysis of the offloading scheme in a fog computing system. In: International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, vol. 2018, art. no. 8631245 (2019)
Daraseliya, A.V., Sopin, E.S., Rykov, V.V.: On optimization of energy consumption in cloud computing system. In: CEUR Workshop Proceedings, vol. 2332, pp. 23–31 (2018)
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Sharofidinov, F., Muthanna, M.S.A., Pham, V.D., Khakimov, A., Muthanna, A., Samouylov, K. (2020). Agriculture Management Based on LoRa Edge Computing System. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds) Distributed Computer and Communication Networks. DCCN 2020. Lecture Notes in Computer Science(), vol 12563. Springer, Cham. https://doi.org/10.1007/978-3-030-66471-8_10
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