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Remote Testing of Usability in Medical Apps Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Artificial Intelligence at the Edge in the Blockchain of Things

Authors : Tuan Nguyen Gia, Anum Nawaz, Jorge Peña Querata, Hannu Tenhunen, Tomi Westerlund

Published in: Wireless Mobile Communication and Healthcare

Publisher: Springer International Publishing

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Abstract

Traditional cloud-centric architectures for Internet-of-Things applications are being replaced by distributed approaches. The Edge and Fog computing paradigms crystallize the concept of moving computation towards the edge of the network, closer to where the data originates. This has important benefits in terms of energy efficiency, network load optimization and latency control. The combination of these paradigms with embedded artificial intelligence in edge devices, or Edge AI, enables further improvements. In turn, the development of blockchain technology and distributed architectures for peer-to-peer communication and trade allows for higher levels of security. This can have a significant impact on data-sensitive and mission-critical applications in the IoT. In this paper, we discuss the potential of an Edge AI capable system architecture for the Blockchain of Things. We show how this architecture can be utilized in health monitoring applications. Furthermore, by analyzing raw data directly at the edge layer, we inherently avoid the possibility of breaches of sensitive information, as raw data is never stored nor transferred outside of the local network.

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Literature
1.
Al-Fuqaha, A., et al.: Internet of Things: a survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutor. 17(4), 2347–2376 (2015)CrossRef
2.
Gia, T.N., et al.: Edge AI in smart farming IoT: CNNs at the edge and fog computing with lora. In: IEEE AFRICON-2019 (2019)
3.
Moosavi, S.R., et al.: Session resumption-based end-to-end security for healthcare Internet-of-Things. In: 2015 IEEE CIT, pp. 581–588. IEEE (2015)
4.
Gubbi, J., et al.: Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013)CrossRef
5.
Moosavi, S.R., et al.: Sea: a secure and efficient authentication and authorization architecture for IoT-based healthcare using smart gateways. Procedia Comput. Sci. 52, 452–459 (2015)CrossRef
6.
Moosavi, S.R., et al.: End-to-end security scheme for mobility enabled healthcare Internet of Things. Future Gener. Comput. Syst. 64, 108–124 (2016)CrossRef
7.
Fernandes, E., et al.: Security analysis of emerging smart home applications. In: 2016 IEEE Symposium on Security and Privacy (SP), pp. 636–654 (May 2016)
8.
Apthorpe, N., Reisman, D., Feamster, N.: A smart home is no castle: privacy vulnerabilities of encrypted IoT traffic. arXiv preprint arXiv:​1705.​06805 (2017)
9.
Ali, M., et al.: Intelligent autonomous elderly patient home monitoring system. In: ICC 2019–2019 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2019)
10.
Gia, T.N., et al.: Edge AI in smart farming IoT: CNNs at the edge and fog computing with lora (2019)
11.
Dastjerdi, A.V., Buyya, R.: Fog computing: helping the Internet of Things realize its potential. Computer 49(8), 112–116 (2016)CrossRef
12.
Gia, T.N., et al.: Energy efficient fog-assisted iot system for monitoring diabetic patients with cardiovascular disease. Future Gener. Comput. Syst. 93, 198–211 (2019)CrossRef
13.
Ali, M., et al.: Autonomous patient/home health monitoring powered by energy harvesting. In: GLOBECOM 2017–2017 IEEE Global Communications Conference, pp. 1–7. IEEE (2017)
14.
Sarker, V.K., et al.: A survey on lora for IoT: integrating edge computing. In: 2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC), pp. 295–300. IEEE (2019)
15.
Queralta, J.P., et al.: Edge-AI in lora-based health monitoring: fall detection system with fog computing and LSTM recurrent neural networks. In: 2019 42nd International Conference on Telecommunications and Signal Processing (TSP), pp. 601–604. IEEE (2019)
16.
Metwaly, A., et al.: Edge computing with embedded AI: thermal image analysis for occupancy estimation in intelligent buildings. In: INTelligent Embedded Systems Architectures and Applications, INTESA@ESWEEK 2019. ACM (2019)
17.
Roman, R., Lopez, J., Mambo, M.: Mobile edge computing, fog et al.: a survey and analysis of security threats and challenges. Future Gener. Comput. Syst. 78, 680–698 (2018)CrossRef
18.
Conoscenti, M., Vetró, A., De Martin, J.C.: Blockchain for the Internet of Things: a systematic literature review. In: 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), pp. 1–6 (November 2016)
19.
Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system. White Paper (2008)
20.
Shafagh, H., et al.: Towards blockchain-based auditable storage and sharing of IoT data. In: Proceedings of the 2017 on Cloud Computing Security Workshop, CCSW 2017, pp. 45–50. ACM, New York (2017)
21.
Huh, S., Cho, S., Kim, S.: Managing IoT devices using blockchain platform. In: 2017 19th International Conference on Advanced Communication Technology (ICACT), pp. 464–467. IEEE (2017)
22.
Novo, O.: Blockchain meets IoT: an architecture for scalable access management in IoT. IEEE Internet Things J. 5(2), 1184–1195 (2018)CrossRef
23.
Tang, B., et al.: A hierarchical distributed fog computing architecture for big data analysis in smart cities. In: Proceedings of the ASE BigData & SocialInformatics 2015, p. 28. ACM (2015)
24.
Dorri, A., et al.: Blockchain for IoT security and privacy: the case study of a smart home. In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 618–623. IEEE (2017)
25.
Christidis, K., Devetsikiotis, M.: Blockchains and smart contracts for the Internet of Things. IEEE Access 4, 2292–2303 (2016)CrossRef
26.
Kshetri, N.: Can blockchain strengthen the Internet of Things? IT Prof. 19(4), 68–72 (2017)CrossRef
27.
Nawaz, A., et al.: Edge AI and blockchain for privacy-critical and data-sensitive applications. In: The 12th International Conference on Mobile Computing and Ubiquitous Networking (ICMU) (2019)
28.
Ndibanje, B., Lee, H.-J., Lee, S.-G.: Security analysis and improvements of authentication and access control in the Internet of Things. Sensors 14(8), 14786–14805 (2014)CrossRef
29.
Bahga, A., Madisetti, V.: Internet of Things: A Hands-on Approach. VPT, New York (2014)
30.
31.
Mandl, K.D., et al.: Public standards and patients’ control: how to keepelectronic medical records accessible but private. BMJ 322(7281), 283–287 (2001)CrossRef
32.
Mamoshina, P., et al.: Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare. Oncotarget 9(5), 5665 (2018)CrossRef
33.
Peterson, K., et al.: A blockchain-based approach to health information exchange networks. In: Proceedings of NIST Workshop Blockchain Healthcare, vol. 1, pp. 1–10 (2016)
34.
Irving, G., Holden, J.: How blockchain-timestamped protocols could improve the trustworthiness of medical science. F1000Research 5, 22 (2016)CrossRef
35.
Dwivedi, A.D., et al.: A decentralized privacy-preserving healthcare blockchain for IoT. Sensors 19(2), 326 (2019)CrossRef
36.
Simić, M., et al.: A case study IoT and blockchain powered healthcare. In: International Conference on Engineering and Technology (ICET-2017) (June 2017)
37.
Pham, H.L., Tran, T.H., Nakashima, Y.: A secure remote healthcare system for hospital using blockchain smart contract. In: 2018 IEEE Globecom Workshops (GC Wkshps), pp. 1–6. IEEE (2018)
38.
Apthorpe, N., et al.: Spying on the smart home: privacy attacks and defenses on encrypted IoT traffic. arXiv preprint arXiv:​1708.​05044 (2017)
39.
Hernandez, G., et al.: Smart nest thermostat: a smart spy in your home. Black Hat USA, pp. 1–8 (2014)
40.
Albino, V., Berardi, U., Dangelico, R.M.: Smart cities: definitions, dimensions, performance, and initiatives. J. Urban Technol. 22(1), 3–21 (2015)CrossRef
41.
Lasi, H., et al.: Industry 4.0. Bus. Inf. Syst. Eng. 6(4), 239–242 (2014)CrossRef
42.
Qingqing, L., et al.: Edge computing for mobile robots: multi-robot feature-based lidar odometry with FPGAs. In: The 12th International Conference on Mobile Computing and Ubiquitous Networking (ICMU) (2019)
43.
Qingqing, L., et al.: Visual odometry offloading in Internet of vehicles with compression at the edge of the network. In: The 12th International Conference on Mobile Computing and Ubiquitous Networking (ICMU) (2019)
44.
Gia, T.N., et al.: Fog computing approach for mobility support in Internet-of-Things systems. IEEE Access 6, 36064–36082 (2018)CrossRef
45.
Jiang, M., et al.: IoT-based remote facial expression monitoring system with sEMG signal. In: 2016 IEEE Sensors Applications Symposium (SAS), pp. 1–6. IEEE (2016)
46.
Gia, T.N., et al.: Fog computing in healthcare Internet of Things: a case study on ECG feature extraction. In: 2015 IEEE CIT, pp. 356–363. IEEE (2015)
47.
Palacios-Enriquez, A., Ponomaryov, V.: Feature extraction based on wavelet transform using ECG signal. In: 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, pp. 632–634. IEEE (2013)
48.
Gia, T.N., et al.: Fog computing in body sensor networks: an energy efficient approach. In: Proceedings of IEEE International Body Sensor Networks Conference (BSN), pp. 1–7 (2015)
49.
Gia, T.N., et al.: Customizing 6LoWPAN networks towards Internet-of-Things based ubiquitous healthcare systems. In: 2014 Norchip, pp. 1–6. IEEE (2014)
50.
Steinberg, C., et al.: A novel wearable device for continuous ambulatory ECG recording: proof of concept and assessment of signal quality. Biosensors 9(1), 17 (2019)CrossRef
51.
Sarker, V.K., et al.: Portable multipurpose bio-signal acquisition and wireless streaming device for wearables. In: 2017 IEEE Sensors Applications Symposium (SAS), pp. 1–6. IEEE (2017)
52.
Carreiras, C., et al.: BioSPPy: biosignal processing in Python, 2015. Accessed Aug 2019
53.
54.
Dhaou, I.B., et al.: Low-latency hardware architecture for cipher-based message authentication code. In: 2017 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1–4. IEEE (2017)
55.
Gia, T.N., et al.: Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes. In: 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 1765–1770. IEEE (2017)
Metadata
Title
Artificial Intelligence at the Edge in the Blockchain of Things
Authors
Tuan Nguyen Gia
Anum Nawaz
Jorge Peña Querata
Hannu Tenhunen
Tomi Westerlund
Copyright Year
2020
Book
Wireless Mobile Communication and Healthcare

Print ISBN: 978-3-030-49288-5

Electronic ISBN: 978-3-030-49289-2

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-49289-2_21

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