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Leveraging Fog Computing for Healthcare IoT

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Fog Computing in the Internet of Things

Abstract

Developments in technology have shifted the focus of medical practice from treating a disease to prevention. Currently, a significant enhancement in healthcare is expected to be achieved through the Internet of Things (IoT). There are various wearable IoT devices that track physiological signs and signals in the market already. These devices usually connect to the Internet directly or through a local smart phone or a gateway. Home-based and in hospital patients can be continuously monitored with wearable and implantable sensors and actuators. In most cases, these sensors and actuators are resource constrained to perform computing and operate for longer periods. The use of traditional gateways to connect to the Internet provides only connectivity and limited network services. With the introduction of the Fog computing layer, closer to the sensor network, data analytics and adaptive services can be realized in remote healthcare monitoring. This chapter focuses on a smart e-health gateway implementation for use in the Fog computing layer, connecting a network of such gateways, both in home and in hospital use. To show the application of the services, simple healthcare scenarios are presented. The features of the gateway in our Fog implementation are discussed and evaluated.

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References

  1. European Commission Information Society, Internet of Things Strategic Research Roadmap (2009), http://www.internet-of-things-research.eu/. Accessed 14 July 2015

  2. European Commission Information Society, Internet of Things in 2020: a Roadmap for the Future (2008), http://www.iot-visitthefuture.eu. Accessed 14 July 2015

  3. A. Dohr, R. Modre-Opsrian, M. Drobics, D. Hayn, G. Schreier, The internet of things for ambient assisted living, in Proceedings of the International Conference on Information Technology: New Generations (2010), pp. 804–809

    Google Scholar 

  4. D. Miorandi, S. Sicari, F. De Pellegrini, I. Chlamtac, Internet of things: vision, applications and research challenges. Ad Hoc Networks 10 (7), 1497–1516 (2012)

    Article  Google Scholar 

  5. M. Carmen Domingo, An overview of the internet of things for people with disabilities. J. Netw. Comput. Appl. 35 (2), 584–596 (2012)

    Article  Google Scholar 

  6. H. Yan, L. Da Xu, Z. Bi, Z. Pang, J. Zhang, Y. Chen, An emerging technology – wearable wireless sensor networks with applications in human health condition monitoring. J. Manage. Anal. 2 (2), 121–137 (2015)

    Google Scholar 

  7. Y.J. Fan, Y.H. Yin, L.D. Xu, Y. Zeng, F. Wu, Iot-based smart rehabilitation system. IEEE Trans. Ind. Inf. 10 (2), 1568–1577 (2014)

    Article  Google Scholar 

  8. B. Farahani, F. Firouzi, V. Chang, M. Badaroglu, K. Mankodiya, Towards fog-driven IoT eHealth: promises and challenges of IoT in medicine and healthcare. Elsevier Future Generation Computer Systems (2017)

    Google Scholar 

  9. C.E. Koop, R. Mosher, L. Kun, J. Geiling, E. Grigg, S. Long, C. Macedonia, R. Merrell, R. Satava, J. Rosen, Future delivery of health care: Cybercare. IEEE Eng. Med. Biol. Mag. 27 (6), 29–38 (2008)

    Article  Google Scholar 

  10. European Research Cluster on the Internet of Things, IoT semantic interoperability: research challenges, best practices, solutions and next steps, in IERC AC4 Manifesto - “Present and Future” (2014)

    Google Scholar 

  11. B. Xu, L.D. Xu, H. Cai, C. Xie, J. Hu, F. Bu, Ubiquitous data accessing method in IoT-based information system for emergency medical services. IEEE Trans. Ind. Inf. 10 (2), 1578–1586 (2014)

    Article  Google Scholar 

  12. L. Jiang, L.D. Xu, H. Cai, Z. Jiang, F. Bu, B. Xu, An IoT-oriented data storage framework in cloud computing platform. IEEE Trans. Ind. Inf. 10 (2), 1443–1451 (2014)

    Article  Google Scholar 

  13. F. Bonomi, R. Milito, J. Zhu, S. Addepalli, Fog computing and its role in the internet of things, in Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing (2012), pp. 13–16

    Google Scholar 

  14. M. Aazam, E.N. Huh, Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT, in 2015 IEEE 29th International Conference on Advanced Information Networking and Applications (2015), pp. 687–694

    Google Scholar 

  15. M. Aazam, E.N. Huh, Fog computing and smart gateway based communication for cloud of things, in 2014 International Conference on Future Internet of Things and Cloud (FiCloud) (2014), pp. 464–470

    Google Scholar 

  16. A.-M. Rahmani, N.K. Thanigaivelan, T.N. Gia, J. Granados, B. Negash, P. Liljeberg, H. Tenhunen, Smart e-Health gateway: bringing intelligence to IoT-based ubiquitous healthcare systems, in Proceeding of 12th Annual IEEE Consumer Communications and Networking Conference (2015), pp. 826–834

    Google Scholar 

  17. A.M. Rahmani, T.N. Gia, B. Negash, A. Anzanpour, I. Azimi, M. Jiang, P. Liljeberg, Exploiting smart e-health gateways at the edge of healthcare internet-of-things: a fog computing approach. Futur. Gener. Comput. Syst. (2017). In Press, Corrected Proof. https://doi.org/10.1016/j.future.2017.02.014

  18. Health Level Seven Int’l, Introduction to HL7 Standards (2012). www.hl7.org/implement/standards. Accessed 30 July 2015

  19. M.L. Hilton, Wavelet and wavelet packet compression of electrocardiograms. IEEE Trans. Biomed. 44 (5), 394–402 (1997)

    Article  Google Scholar 

  20. Z. Lu, D. Youn Kim, W.A. Pearlman, Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm. IEEE Trans. Biomed. 47 (7), 849–856 (2000)

    Article  Google Scholar 

  21. R. Benzid, A. Messaoudi, A. Boussaad, Constrained ECG compression algorithm using the block-based discrete cosine transform. Digital Signal Process. 18 (1), 56–64 (2008)

    Article  Google Scholar 

  22. H.F. Durrant-Whyte, Sensor models and multisensor integration. Int. J. Rob. Res. 7 (6), 97–113 (1988)

    Article  Google Scholar 

  23. T.N. Gia, T. Igor, V.K. Sarker, A.-M. Rahmani, T. Westerlund, P. Liljeberg, H. Tenhunen, IoT-based fall detection system with energy efficient sensor nodes, in IEEE Nordic Circuits and Systems Conference (NORCAS’16) (2016)

    Google Scholar 

  24. T.N. Gia, M. Jiang, A.-M. Rahmani, T. Westerlund, K. Mankodiya, P. Liljeberg, H. Tenhunen, Fog computing in body sensor networks: an energy efficient approach, in IEEE International Body Sensor Networks Conference (BSN’15) (2015)

    Google Scholar 

  25. T.N. Gia, M. Jiang, A.M. Rahmani, T. Westerlund, P. Liljeberg, H. Tenhunen, Fog computing in healthcare internet of things: A case study on ecg feature extraction, in Proceeding of International Conference on Computer and Information Technology (2015), pp. 356–363

    Google Scholar 

  26. B. Negash, A.M. Rahmani, T. Westerlund, P. Liljeberg, H. Tenhunen, Lisa: lightweight internet of things service bus architecture. Procedia Comput. Sci. 52, 436–443 (2015). The 6th International Conference on Ambient Systems, Networks and Technologies (ANT-2015), the 5th International Conference on Sustainable Energy Information Technology (SEIT-2015)

    Google Scholar 

  27. N. Paul, T. Kohno, D.C. Klonoff, A review of the security of insulin pump infusion systems. J. Diabetes Sci. Technol. 5 (6), 1557–1562 (2011)

    Article  Google Scholar 

  28. netfilter/iptables - nftables project. http://netfilter.org/projects/nftables/. Accessed 24 July 2015

  29. G. Kambourakiset, E. Klaoudatou, S. Gritzalis, Securing medical sensor environments: the CodeBlue Framework case, in Proceeding of the Second International Conference on Availability, Reliability and Security (2007), pp. 637–643

    Google Scholar 

  30. R. Chakravorty, A programmable service architecture for mobile medical care, in Proceeding of Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (2006), pp. 5, 536

    Google Scholar 

  31. J. Ko, J.H. Lim, Y. Chen, R. Musvaloiu-E, A. Terzis, G.M. Masson, T. Gao, W. Destler, L. Selavo, R.P. Dutton, Medisn: medical emergency detection in sensor networks. ACM Trans. Embed. Comput. Syst. 10 (1), 11:1–11:29 (2010)

    Google Scholar 

  32. S.R. Moosavi, T.N. Gia, A. Rahmani, E. Nigussie, S. Virtanen, H. Tenhunen, J. Isoaho, SEA: a secure and efficient authentication and authorization architecture for IoT-based healthcare using smart gateways, in Proceeding of 6th International Conference on Ambient Systems, Networks and Technologies (2015), pp. 452–459

    Google Scholar 

  33. S.R. Moosavi, T.N. Gia, E. Nigussie, A. Rahmani, S. Virtanen, H. Tenhunen, J. Isoaho, Session resumption-based end-to-end security for healthcare internet-of-things, in Proceeding of IEEE International Conference on Computer and Information Technology (2015), pp. 581–588

    Google Scholar 

  34. PyCrypto API Documentation, https://pythonhosted.org/pycrypto/. Accessed 26 May 2016

  35. Texas Instruments, Low-Power, 2-Channel, 24-Bit Analog Front-End for Biopotential Measurements (2012)

    Google Scholar 

  36. Texas Instruments, ECG Implementation on the TMS320C5515 DSP Medical Development Kit (MDK) with the ADS1298 ECG-FE (2011)

    Google Scholar 

  37. RTX Real-Time Operating System, http://www.keil.com/rl-arm/kernel.asp. 04 August 2015

  38. R. Barry, Using The FreeRTOS Real Time Kernel, Microchip PIC32 Edition. FreeRTOS Tutorial Books (2010)

    Google Scholar 

  39. A. Dunkels, B. Gronvall, T. Voigt, Contiki - a lightweight and flexible operating system for tiny networked sensors, in Proceeding of International Conference on Local Computer Networks (2004), pp. 455–462

    Google Scholar 

  40. OMAP®;4, PandaBoard System Reference Manual (2010), http://pandaboard.org. Accessed 04 August 2015

  41. SmartRF06, Evaluation Board User’s Guide (2013), http://www.ti.com/lit/ug/swru321a/swru321a.pdf. Accessed 04 August 2015

  42. Olimex, MOD-ENC28J60 development board, Users Manual (2008). https://www.olimex.com/Products/Modules/Ethernet/MOD-ENC28J60/resources/MOD-ENC28J60.pdf. Accessed 04 August 2015

  43. IEEE standard for medical device communication, overview and framework, in ISO/IEEE 11073 Committee (1996)

    Google Scholar 

  44. V.S. Miller et al., Data compression method. US4814746 A, Filing date August 11, 1986. Publication date March 21, 1989

    Google Scholar 

  45. G.B. Moody, R.G. Mark, The impact of the MIT-BIH arrhythmia database. Eng. Med. Biol. Mag. IEEE 20 (3), 45–50 (2001)

    Article  Google Scholar 

  46. S. Luo, B. Ren, The monitoring and managing application of cloud computing based on internet of things. Comput. Methods Programs Biomed. 130, 154–161 (2016)

    Article  Google Scholar 

  47. J. Gomez, B. Oviedo, E. Zhuma, Patient monitoring system based on internet of things. Proc. Comput. Sci. 83, 90–97 (2016)

    Article  Google Scholar 

  48. G. Ji, W. Ouyang, K. Yang, G. Yang, Skin-attached sensor and artifact removal using cloud computing, in 7th International Conference on e-Health (eHealth2015) (2015)

    Google Scholar 

  49. D. Bimschas, H. Hellbrück, R. Mietz, D. Pfisterer, K. Römer, T. Teubler, Middleware for smart gateways connecting sensornets to the Internet, in Proceedings of the International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks (2010), pp. 8–14

    Google Scholar 

  50. Y. Shi, G. Ding, H. Wang, H.E. Roman, S. Lu, The fog computing service for healthcare, in 2015 2nd International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare (Ubi-HealthTech), May 2015, pp. 1–5

    Google Scholar 

  51. L. Prieto González, C. Jaedicke, J. Schubert, V. Stantchev, Fog computing architectures for healthcare: wireless performance and semantic opportunities. J. Inf. Commun. Ethics Soc. 14 (4), 334–349 (2016)

    Article  Google Scholar 

  52. V. Stantchev, A. Barnawi, S. Ghulam, J. Schubert, G. Tamm, Smart items, fog and cloud computing as enablers of servitization in healthcare. Sens. Transducers 185 (2), 121 (2015)

    Google Scholar 

  53. Y. Cao, S. Chen, P. Hou, D. Brown, Fast: a fog computing assisted distributed analytics system to monitor fall for stroke mitigation, in 2015 IEEE International Conference on Networking, Architecture and Storage (NAS) (IEEE, New York, 2015), pp. 2–11

    Google Scholar 

  54. A. Monteiro, H. Dubey, L. Mahler, Q. Yang, K. Mankodiya, Fit a fog computing device for speech teletreatments. arXiv preprint arXiv:1605.06236 (2016)

    Google Scholar 

  55. O. Fratu, C. Pena, R. Craciunescu, S. Halunga, Fog computing system for monitoring mild dementia and COPD patients-Romanian case study, in 2015 12th International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS) (IEEE, New York, 2015), pp. 123–128

    Google Scholar 

  56. J.K. Zao, T.-T. Gan, C.-K. You, C.-E. Chung, Y.-T. Wang, S. José Rodríguez Méndez, T. Mullen, C. Yu, C. Kothe, C.-T. Hsiao, et al., Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology. Front. Hum. Neurosci. 8(370), 1–16 (2014)

    Google Scholar 

  57. M. Abu-Elkheir, H.S. Hassanein, S.M.A. Oteafy, Enhancing emergency response systems through leveraging crowdsensing and heterogeneous data, in Wireless Communications and Mobile Computing Conference (IWCMC), 2016 International (IEEE, New York, 2016), pp. 188–193

    Google Scholar 

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Correspondence to Behailu Negash .

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Negash, B. et al. (2018). Leveraging Fog Computing for Healthcare IoT. In: Rahmani, A., Liljeberg, P., Preden, JS., Jantsch, A. (eds) Fog Computing in the Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-319-57639-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-57639-8_8

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