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ICBM-Based Smart Farm Environment Management System

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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 790))

Abstract

The combination of Internet of Things (IoT), cloud computing, big data, and mobile technologies is a new technology paradigm referred to as ICBM technology. In this study, we designed and implemented a smart farm environment management system based on the ICBM paradigm that can collect and monitor information on crop growth. Our proposed wireless system not only collects environmental data from inside a greenhouse and controls the greenhouse facilities, but also enhances energy efficiency through effective management of IoT sensor network topology. Our system provides convenience by allowing remote monitoring and controlling of the smart farm environment while establishing a database that enables big data analysis in the cloud to optimize the environment for crop growth. The safety of all functions related to information collection, information delivery, and smart farm control by the user have been confirmed through application of this technology on fields. Furthermore, our proposed system also grants flexibility of time and location when it comes to monitoring and controlling farms or greenhouses.

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References

  1. Lee, M., Hwang, J., Yoe, H.: Agricultural production system based on IOT. In: 16th International Conference on Computational Science and Engineering (CSE), 2013 IEEE, pp. 833–837. IEEE (2013)

    Google Scholar 

  2. Lee, M., Yoe, H.: Analysis of environmental stress factors using an artificial growth system and plant fitness optimization. Biomed. Res. Int. 2015, 6 (2015)

    Google Scholar 

  3. Jayaraman, P., Yavari, A., Georgakopoulos, D., Morshed, A., Zaslavsky, A.: Internet of Things platform for smart farming: experiences and lessons learnt. Sensors 16, 1884 (2016)

    Article  Google Scholar 

  4. Weber, R.H., Weber, R.: Internet of Things. Springer, Heidelberg (2010)

    Book  Google Scholar 

  5. Wu, G., Talwar, S., Johnsson, K., Himayat, N., Johnson, K.D.: M2 M: from mobile to embedded internet. IEEE Commun. Mag. 49, 36–43 (2011)

    Google Scholar 

  6. Lynggaard, P., Skouby, K.: Complex IoT systems as enablers for smart homes in a smart city vision. Sensors 16, 1840 (2016)

    Article  Google Scholar 

  7. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1, 7–18 (2010)

    Article  Google Scholar 

  8. Mell, P., Grance, T.: The NIST Definition of Cloud Computing (2011)

    Google Scholar 

  9. Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25, 599–616 (2009)

    Article  Google Scholar 

  10. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H.: Big Data: The Next Frontier for Innovation, Competition, and Productivity (2011)

    Google Scholar 

  11. Chen, M., Mao, S., Zhang, Y., Leung, V.C.: Big Data: Related Technologies, Challenges and Future Prospects. Springer, New York (2014)

    Book  Google Scholar 

  12. Jara, A.J., Zamora, M.A., Skarmeta, A.F.: An Initial Approach to Support Mobility in Hospital Wireless Sensor Networks Based on 6LoWPAN (HWSN6) (2010)

    Google Scholar 

  13. Kuladinithi, K., Bergmann, O., Pötsch, T., Becker, M., Görg, C.: Implementation of CoAP and its application in transport logistics. In: Proceedings of IP + SN, Chicago, IL, USA (2011)

    Google Scholar 

  14. Fielding, R., Gettys, J., Mogul, J., Frystyk, H., Masinter, L., Leach, P., Berners-Lee, T.: Hypertext Transfer Protocol–HTTP/1.1 (1999)

    Google Scholar 

  15. Mulligan, G.: The 6LoWPAN architecture. In: Proceedings of the 4th Workshop on Embedded Networked Sensors, pp. 78–82. ACM (2007)

    Google Scholar 

  16. Shelby, Z., Bormann, C.: 6LoWPAN: The Wireless Embedded Internet. John Wiley & Sons, Chichester (2011)

    Google Scholar 

  17. Winter, T.: RPL: IPv6 Routing Protocol for Low-Power and Lossy Networks (2012)

    Google Scholar 

  18. Hui, J.W.: The Routing Protocol for Low-Power and Lossy Networks (RPL) Option for Carrying RPL Information in Data-Plane Datagrams (2012)

    Google Scholar 

  19. Bormann, C., Castellani, A.P., Shelby, Z.: CoAP: an application protocol for billions of tiny internet nodes. IEEE Internet Comput. 16, 62 (2012)

    Article  Google Scholar 

  20. Kovatsch, M., Duquennoy, S., Dunkels, A.: A low-power CoAP for Contiki. In: 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems, pp. 855–860. IEEE (2011)

    Google Scholar 

  21. Raza, S., Trabalza, D., Voigt, T.: 6LoWPAN compressed DTLS for CoAP. In: 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems, pp. 287–289. IEEE (2012)

    Google Scholar 

  22. Ma, X., Luo, W.: The analysis of 6LoWPAN technology. In: 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application (2008)

    Google Scholar 

  23. Efendi, A.M., Negara, A.F.P., Kyo, O.S., Choi, D.: A design of 6LoWPAN routing protocol border router with multi-uplink interface: ethernet and Wi-Fi. Adv. Sci. Lett. 20, 56–60 (2014)

    Article  Google Scholar 

  24. Lee, M., Kim, H., Yoe, H.: Intelligent environment management system for controlled horticulture. In: 2017 4th NAFOSTED Conference on Information and Computer Science, pp. 116–119 (2017)

    Google Scholar 

  25. Lee, M.-h., Eom, K.-b., Kang, H.-j., Shin, C.-s., Yoe, H.: Design and implementation of wireless sensor network for ubiquitous glass houses. In: Seventh IEEE/ACIS International Conference on Computer and Information Science 2008, ICIS 08, pp. 397–400. IEEE (2008)

    Google Scholar 

  26. Han, J., Haihong, E., Le, G., Du, J.: Survey on NoSQL database. In: 6th International Conference on Pervasive Computing and Applications (ICPCA) 2011, pp. 363–366. IEEE (2011)

    Google Scholar 

  27. Lee, M.-h., Yoe, H.: Comparative analysis and design of wired and wireless integrated networks for wireless sensor networks. In: 5th ACIS International Conference on Software Engineering Research, Management & Applications (SERA 2007), pp. 518–522. IEEE (2007)

    Google Scholar 

  28. Gardner, J.W., Varadan, V.K., Awadelkarim, O.O.: Microsensors, MEMS, and Smart Devices. Wiley, New York (2001)

    Book  Google Scholar 

  29. Capella, J., Campelo, J., Bonastre, A., Ors, R.: A reference model for monitoring IoT WSN-based applications. Sensors 16, 1816 (2016)

    Article  Google Scholar 

  30. Zikopoulos, P., Eaton, C.: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media, New York (2011)

    Google Scholar 

  31. Shen, W., Xu, Y., Xie, D., Zhang, T., Johansson, A.: Smart border routers for ehealthcare wireless sensor networks. In: 7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM) 2011, pp. 1–4. IEEE (2011)

    Google Scholar 

  32. Chang, H.-L., Wang, C.-G., Wu, M.-T., Tsai, M.-H., Lin, C.-Y.: Gateway-assisted retransmission for lightweight and reliable IoT communications. Sensors 16, 1560 (2016)

    Article  Google Scholar 

  33. Choe, Y.C.: Analysis method of measurement data for solution of difficulties in agricultural field. Report, Seoul National University (2015)

    Google Scholar 

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Acknowledgments

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2018-2013-1-00877) supervised by the IITP (Institute for Information & communications Technology Promotion).

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Authors and Affiliations

  1. Department of Agricultural Engineering, National Institute of Agricultural Sciences, Wanju, Jeollabuk-do, 55365, Republic of Korea

    Meonghun Lee

  2. School of Information Technology, Catholic University of Daegu, Republic of Korea, Gyeongsan, Gyeongbuk-do, 38430, Republic of Korea

    Haengkon Kim

  3. Department of Information and Communication Engineering, Sunchon National University, Suncheon, Jeollanam-do, 57922, Republic of Korea

    Hyun Yoe

Authors
  1. Meonghun Lee
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  2. Haengkon Kim
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  3. Hyun Yoe
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Correspondence to Hyun Yoe .

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Editors and Affiliations

  1. Software Engineering and Information Technology Institute, Central Michigan University, Mount Pleasant, MI, USA

    Roger Lee

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Lee, M., Kim, H., Yoe, H. (2019). ICBM-Based Smart Farm Environment Management System. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. SNPD 2018. Studies in Computational Intelligence, vol 790. Springer, Cham. https://doi.org/10.1007/978-3-319-98367-7_4

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