Abstract
The Internet of Things (IoT) is used to improve traditional healthcare systems in different aspects, including monitoring patients’ behaviors. Information gathered by sensors in the IoT plays an essential role in healthcare systems. Because of privacy and security issues, the data must be protected against unauthorized changes. On the other hand, Blockchain technology provides a wide range of mechanisms to protect data against changes. Therefore, IoT-based healthcare monitoring using Blockchain constitutes an exciting technological innovation, which may help mitigate security and privacy concerns related to the gathering of information during patient monitoring. In this chapter, the potential applications of IoT–Blockchain systems are studied, and then monitoring mechanisms in healthcare systems are analyzed. To this end, a novel architecture based on recently reported solutions is proposed. The proposed architecture, with the aid of computational power obtained from the IoT, Blockchain and artificial intelligence, can be used in a wide range of solutions aimed at managing the coronavirus disease 2019 (COVID-19). In order to show the potential of the proposed architecture, three case studies are presented. At the end of this chapter, other applications of the proposed architecture are summarized, which can be used in pandemic situations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Abujamra, R., & Randall, D. (2019). Chapter Five—Blockchain applications in healthcare and the opportunities and the advancements due to the new information technology framework. In S. Kim, G. C. Deka, & P. Zhang (Eds.), Advances in Computers (Vol. 115, pp. 141–154). Elsevier. https://doi.org/10.1016/bs.adcom.2018.12.002.
Adler, J., Berryhill, R., Veneris, A., Poulos, Z., Veira, N., & Kastania, A. (2018). Astraea: A decentralized blockchain oracle. In 2018 IEEE international conference on internet of things (IThings) and IEEE green computing and communications (GreenCom) and IEEE cyber, physical and social computing (CPSCom) and IEEE smart data (SmartData) (pp. 1145–1152). https://doi.org/10.1109/Cybermatics_2018.2018.00207.
Ahmadi, V., Benjelloun, S., El Kik, M., Sharma, T., Chi, H., & Zhou, W. (2020). Drug Governance: IoT-based blockchain implementation in the pharmaceutical supply chain. Sixth International Conference on Mobile and Secure Services (MobiSecServ), 2020, 1–8. https://doi.org/10.1109/MobiSecServ48690.2020.9042950.
Ajerla, D., Mahfuz S., Zulkernine F. (2019). A real-time patient monitoring framework for fall detection Hindawi. https://doi.org/10.1155/2019/9507938.
Al-Odat, Z. A., Srinivasan, S. K., Al-qtiemat, E., Dubasi, M. A. L., & Shuja, S. (2018). IoT-based secure embedded scheme for insulin pump data acquisition and monitoring. ArXiv:1812.02357 [Cs]. https://arxiv.org/abs/1812.02357.
Attia, O., Khoufi, I., Laouiti, A., & Adjih, C. (2019). An IoT-blockchain architecture based on hyperledger framework for healthcare monitoring application. In 2019 10th IFIP international conference on new technologies, mobility and security (NTMS) (pp. 1–5). https://doi.org/10.1109/NTMS.2019.8763849.
Azaria, A., Ekblaw, A., Vieira, T., & Lippman, A. (2016). MedRec: Using blockchain for medical data access and permission management. In 2016 2nd International Conference on Open and Big Data (OBD) (pp. 25–30). https://doi.org/10.1109/OBD.2016.11.
Baliga, A. (2017). Understanding blockchain consensus models. https://www.persistent.com/wp-content/uploads/2018/02/wp-understanding-blockchain-consensus-models.pdf.
Bublitz, M., & F., Oetomo, A., S. Sahu, K., Kuang, A., X. Fadrique, L., E. Velmovitsky, P., M. Nobrega, R., & P. Morita, P. . (2019). Disruptive technologies for environment and health research: An overview of artificial intelligence, blockchain, and internet of things. International Journal of Environmental Research and Public Health, 16(20), 3847. https://doi.org/10.3390/ijerph16203847.
BurstIQ. (2020). BurstIQ|research foundry|blockchain based healthcare data solutions. https://www.burstiq.com/.
Cai, W., Wang, Z., Ernst, J. B., Hong, Z., Feng, C., & Leung, V. C. M. (2018). Decentralized applications: The blockchain-empowered software system. IEEE Access, 6, 53019–53033. https://doi.org/10.1109/ACCESS.2018.2870644.
CDC. (2020). CDC Works 24/7. Centers for Disease Control and Prevention. https://www.cdc.gov/index.htm.
Chamola, V., Hassija V., Gupta V., Guizani M. (2020). A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access, 8, 90225–90265. https://doi.org/10.1109/ACCESS.2020.2992341.
Chronicled. (2020). Chronicled. https://www.chronicled.com/.
Conoscenti, M., Vetrò, A., & De Martin, J. C. (2016). 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). https://doi.org/10.1109/AICCSA.2016.7945805.
Coral Health. (2020). Coral health—building a more connected future in healthcare. https://mycoralhealth.com/product/.
Dentcoin. (2020). Dentacoin: The blockchain solution for the global dental industry. https://dentacoin.com/.
Devi, D., Namasudra, S., & Kadry, S. (2020, July 1). A boosting-aided adaptive cluster-based undersampling approach for treatment of class imbalance problem (Article). International Journal of Data Warehousing and Mining (IJDWM). www.igi-global.com/article/a-boosting-aided-adaptive-cluster-based-undersampling-approach-for-treatment-of-class-imbalance-problem/256163.
Dorri, A., Kanhere, S. S., Jurdak, R., & Gauravaram, P. (2017). Blockchain for IoT security and privacy: The case study of a smart home. IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2017, 618–623. https://doi.org/10.1109/PERCOMW.2017.7917634.
Dubovitskaya, A., Xu, Z., Ryu, S., Schumacher, M., & Wang, F. (2018). Secure and trustable electronic medical records sharing using blockchain. AMIA Annual Symposium Proceedings, 2017, 650–659. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977675/.
Dwivedi, A. D., Malina, L., Dzurenda, P., & Srivastava, G. (2019a). Optimized blockchain model for internet of things based healthcare applications. In 2019 42nd international conference on telecommunications and signal processing (TSP) (pp. 135–139). https://doi.org/10.1109/TSP.2019.8769060.
Dwivedi, A. D., Srivastava, G., Dhar, S., & Singh, R. (2019b). A decentralized privacy-preserving healthcare blockchain for IoT. Sensors (Basel, Switzerland), 19(2). https://doi.org/10.3390/s19020326.
Ebadi, A., Xi, P., Tremblay, S., Spencer, B., Pall, R., & Wong, A. (2020). Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing. ArXiv:2007.11604 [Cs]. https://arxiv.org/abs/2007.11604.
Eisenstadt, M., Ramachandran, M., Chowdhury, N., Third, A., & Domingue, J. (2020). COVID-19 Antibody test/vaccination certification: There’s an app for that. IEEE Open Journal of Engineering in Medicine and Biology, 1, 148–155. https://doi.org/10.1109/OJEMB.2020.2999214.
Fernández-Caramés, T. M., & Fraga-Lamas, P. (2018). Design of a fog computing, blockchain and iot-based continuous glucose monitoring system for crowdsourcing mHealth. Proceedings, 4(1), 37. https://doi.org/10.3390/ecsa-5-05757.
Foteinos, V., Kelaidonis, D., Poulios, G., Vlacheas, P., Stavroulaki, V., & Demestichas, P. (2013). Cognitive management for the internet of things: A framework for enabling autonomous applications. IEEE Vehicular Technology Magazine, 8(4), 90–99. https://doi.org/10.1109/MVT.2013.2281657.
GENE-CHAIN. (2020). DNA data marketplace. EncrypGen. https://encrypgen.com/.
Gia, T. N., Ali, M., Dhaou, I. B., Rahmani, A. M., Westerlund, T., Liljeberg, P., & Tenhunen, H. (2017). IoT-based continuous glucose monitoring system: A feasibility study. Procedia Computer Science, 109, 327–334. https://doi.org/10.1016/j.procs.2017.05.359.
Gordon, W. J., & Catalini, C. (2018). Blockchain technology for healthcare: Facilitating the transition to patient-driven interoperability. Computational and Structural Biotechnology Journal, 16, 224–230. https://doi.org/10.1016/j.csbj.2018.06.003.
Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Hayajneh, T. (2018). Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. Journal of Medical Systems, 42(7), 130. https://doi.org/10.1007/s10916-018-0982-x.
Gupta, S., Malhotra, V., & Singh, S. N. (2020). Securing IoT-driven remote healthcare data through blockchain. In M. L. Kolhe, S. Tiwari, M. C. Trivedi, & K. K. Mishra (Eds.), Advances in data and information sciences (pp. 47–56). Springer. https://doi.org/10.1007/978-981-15-0694-9_6.
HamlAbadi, K. G., Saghiri, A. M., Vahdati, M., Dehghan TakhtFooladi, M., & Meybodi, M. R. (2017). A framework for cognitive recommender systems in the internet of things (IoT). In 2017 IEEE 4th international conference on knowledge-based engineering and innovation (KBEI) (pp. 0971–0976). https://doi.org/10.1109/KBEI.2017.8324939.
Hang, L., Choi, E., & Kim, D.-H. (2019). A novel EMR integrity management based on a medical blockchain platform in hospital. Electronics, 8(4), 467. https://doi.org/10.3390/electronics8040467.
Hassanalieragh, M., Page, A., Soyata, T., Sharma, G., Aktas, M., Mateos, G., et al. (2015). Health monitoring and management using internet-of-things (IoT) sensing with cloud-based processing: Opportunities and challenges. IEEE International Conference on Services Computing, 2015, 285–292. https://doi.org/10.1109/SCC.2015.47.
Huh, S., Cho, S., & Kim, S. (2017). Managing IoT devices using blockchain platform. In 2017 19th International Conference on Advanced Communication Technology (ICACT) (pp. 464–467). https://doi.org/10.23919/ICACT.2017.7890132.
Hussain, A. A., Bouachir, O., Al-Turjman, F., & Aloqaily, M. (2020). AI techniques for COVID-19. IEEE Access, 8, 128776–128795. https://doi.org/10.1109/ACCESS.2020.3007939.
Islam, A., & Shin, S. Y. (2019). BHMUS: blockchain based secure outdoor health monitoring scheme using UAV in smart city. In 2019 7th international conference on information and communication technology (ICoICT) (pp. 1–6). https://doi.org/10.1109/ICoICT.2019.8835373.
Jacobsen, H.-A., Sadoghi, M., Tabatabaei, M. H., Vitenberg, R., & Zhang, K. (2018). Blockchain landscape and AI renaissance: The bright path forward. In Proceedings of the 19th international middleware conference tutorials, Vol. 1. https://doi.org/10.1145/3279945.3279947.
Jaiswal, K., Sobhanayak, S., Turuk, A. K., Bibhudatta, S. L., Mohanta, B. K., & Jena, D. (2018). An IoT-cloud based smart healthcare monitoring system using container based virtual environment in edge device. International conference on emerging trends and innovations in engineering and technological research (ICETIETR), 2018, 1–7. https://doi.org/10.1109/ICETIETR.2018.8529141.
Jamil, F., Ahmad, S., Iqbal, N., & Kim, D.-H. (2020). Towards a remote monitoring of patient vital signs based on IoT-based blockchain integrity management platforms in smart hospitals. Sensors, 20(8), 2195. https://doi.org/10.3390/s20082195.
Kassani, S. H., Kassasni, P. H., Wesolowski, M. J., Schneider, K. A., & Deters, R. (2020). Automatic detection of coronavirus disease (COVID-19) in X-ray and CT images: A machine learning-based approach. ArXiv:2004.10641 [Cs, Eess]. https://arxiv.org/abs/2004.10641.
Kazmi, H. S. Z., Nazeer, F., Mubarak, S., Hameed, S., Basharat, A., & Javaid, N. (2020). Trusted remote patient monitoring using blockchain-based smart contracts. In L. Barolli, P. Hellinckx, & T. Enokido (Eds.), Advances on broad-band wireless computing, communication and applications (pp. 765–776). Springer International Publishing. https://doi.org/10.1007/978-3-030-33506-9_70.
Kormiltsyn, A., Udokwu, C., Karu, K., Thangalimodzi, K., & Norta, A. (2019). Improving healthcare processes with smart contracts. In W. Abramowicz & R. Corchuelo (Eds.), Business information systems (pp. 500–513). Springer International Publishing. https://doi.org/10.1007/978-3-030-20485-3_39.
Koshechkin, K. A., Klimenko, G. S., Ryabkov, I. V., & Kozhin, P. B. (2018). Scope for the application of blockchain in the public healthcare of the Russian federation. Procedia Computer Science, 126, 1323–1328. https://doi.org/10.1016/j.procs.2018.08.082.
Kshetri, N. (2017). Can Blockchain strengthen the internet of things? IT Professional, 19(4), 68–72. https://doi.org/10.1109/MITP.2017.3051335.
Lemieux, V. L., Hofman, D., Hamouda, H., Batista, D., Kaur, R., Pan, W., Costanzo, I., Regier, D., Pollard, S., Weymann, D., & Fraser, R. (2020). Having our omic cake and eating it too: Evaluating user response to using blockchain technology for private & secure health data management and sharing. ArXiv:2004.11502 [Cs]. https://arxiv.org/abs/2004.11502.
Liu, D., Alahmadi, A., Ni, J., Lin, X., & Shen, X. (2019). Anonymous reputation system for IIoT-enabled retail marketing atop PoS blockchain. IEEE Transactions on Industrial Informatics, 15(6), 3527–3537. https://doi.org/10.1109/TII.2019.2898900.
Liu, Y., Yu, F. R., Li, X., Ji, H., & Leung, V. C. M. (2020). Blockchain and machine learning for communications and networking systems. IEEE Communications Surveys Tutorials, 22(2), 1392–1431. https://doi.org/10.1109/COMST.2020.2975911.
Lu, Y. (2019). The blockchain: State-of-the-art and research challenges. Journal of Industrial Information Integration, 15, 80–90. https://doi.org/10.1016/j.jii.2019.04.002.
Mashamba-Thompson, T. P., & Crayton, E. D. (2020). Blockchain and artificial intelligence technology for novel coronavirus disease 2019 self-testing. Diagnostics, 10(4), 198. https://doi.org/10.3390/diagnostics10040198.
McGhin, T., Choo, K.-K.R., Liu, C. Z., & He, D. (2019). Blockchain in healthcare applications: Research challenges and opportunities. Journal of Network and Computer Applications, 135, 62–75. https://doi.org/10.1016/j.jnca.2019.02.027.
Medicalchain. (2018). Medicalchain. Medicalchain. https://medicalchain.com/Medicalchain-Whitepaper-EN.pdf.
Mehta, P., McAuley, D. F., Brown, M., Sanchez, E., Tattersall, R. S., & Manson, J. J. (2020). COVID-19: Consider cytokine storm syndromes and immunosuppression. Lancet (London, England), 395(10229), 1033–1034. https://doi.org/10.1016/S0140-6736(20)30628-0.
Mettler, M. (2016). Blockchain technology in healthcare: The revolution starts here. In 2016 IEEE 18th international conference on e-health networking, applications and services (Healthcom) (pp. 1–3). https://doi.org/10.1109/HealthCom.2016.7749510.
Mezghani, E., Exposito, E., & Drira, K. (2017). A model-driven methodology for the design of autonomic and cognitive IoT-based systems: Application to healthcare. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(3), 224–234. https://doi.org/10.1109/TETCI.2017.2699218.
Mišić, V. B., Mišić, J., & Chang, X. (2019). Towards a blockchain-based healthcare information system: Invited paper. IEEE/CIC international conference on communications in China (ICCC), 2019, 13–18. https://doi.org/10.1109/ICCChina.2019.8855911.
Mohammed, J., Lung, C.-H., Ocneanu, A., Thakral, A., Jones, C., & Adler, A. (2014). Internet of things: Remote patient monitoring using web services and cloud computing. In 2014 IEEE international conference on internet of things (IThings), and IEEE green computing and communications (GreenCom) and IEEE cyber, physical and social computing (CPSCom) (pp. 256–263). https://doi.org/10.1109/iThings.2014.45.
Namasudra, S., & Roy, P. (2017). Time saving protocol for data accessing in cloud computing. IET Communications, 11(10), 1558–1565. https://doi.org/10.1049/iet-com.2016.0777.
Namasudra, S., Roy, P., Vijayakumar, P., Audithan, S., & Balusamy, B. (2017). Time efficient secure DNA based access control model for cloud computing environment. Future Generation Computer Systems, 73, 90–105. https://doi.org/10.1016/j.future.2017.01.017.
Namasudra, S. (Ed.). (2018). Taxonomy of DNA-based security models. In Advances of DNA computing in cryptography (pp. 53–68). Taylor & Francis. https://doi.org/10.1201/9781351011419-3.
Namasudra, S., & Deka, G. C. (2018). Advances of DNA computing in cryptography. Taylor & Francis. https://doi.org/10.1201/9781351011419.
Namasudra, S., Deka, G. C., & Deka, G. C. (2018). Introduction of DNA computing in cryptography. In Advances of DNA computing in cryptography (pp. 17–34). Taylor & Francis. https://doi.org/10.1201/9781351011419-1.
Namasudra, S. (2019). An improved attribute-based encryption technique towards the data security in cloud computing. https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4364.
Namasudra, S, Chakraborty, R., Majumder, A., & Moparthi, N. R. (2020a). Securing multimedia by using DNA based encryption in the cloud computing environment. ACM Transactions on Multimedia Computing, Communications, and Applications.
Namasudra, S., Deka, G. C., Johri, P., Hosseinpour, M., & Gandomi, A. H. (2020b). The revolution of blockchain: State-of-the-art and research challenges. Archives of Computational Methods in Engineering. https://doi.org/10.1007/s11831-020-09426-0.
Namasudra, S., Devi, D., Kadry, S., Sundarasekar, R., & Shanthini, A. (2020c). Towards DNA based data security in the cloud computing environment. Computer Communications, 151, 539–547. https://doi.org/10.1016/j.comcom.2019.12.041.
Nelaturu, K., Mavridou, A., Veneris, A., & Laszka, A. (2020). Verified development and deployment of multiple interacting smart contracts with VeriSolid, Vol. 9.
Othman, W. A. F. W. (2019). IoT-based intelligent medication dose calculator for kids in Drugstore. International Journal of Engineering Creativity & Innovation, 1(2), 15–29. https://www.academia.edu/40791933/IoT-Based_Intelligent_Medication_Dose_Calculator_for_Kids_in_Drugstore.
Panarello, A., Tapas, N., Merlino, G., Longo, F., & Puliafito, A. (2018). Blockchain and IoT integration: A systematic survey. Sensors, 18(8), 2575. https://doi.org/10.3390/s18082575.
Ramezan, G., & Leung, C. (2018). A Blockchain-based contractual routing protocol for the internet of things using smart contracts (Research Article). Hindawi: Wireless Communications and Mobile Computing. https://doi.org/10.1155/2018/4029591.
Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018). On blockchain and its integration with IoT. Challenges and opportunities. Future Generation Computer Systems, 88, 173–190. https://doi.org/10.1016/j.future.2018.05.046.
Saddik, A. E., Hossain, M. S., & Kantarci, B. (Eds.). (2020). Connected health in smart cities. Springer International Publishing. https://doi.org/10.1007/978-3-030-27844-1.
Saghiri, A. M. (2020a). Blockchain Architecture. In S. Kim & G. C. Deka (Eds.), Advanced applications of blockchain technology (pp. 161–176). Springer. https://doi.org/10.1007/978-981-13-8775-3_8.
Saghiri, A. M. (2020b). A Survey on challenges in designing cognitive engines. In 2020 6th international conference on web research (ICWR) (pp. 165–171). https://doi.org/10.1109/ICWR49608.2020.9122273.
Saghiri, A. M., HamlAbadi, K. G., & Vahdati, M. (2020). The internet of things, artificial intelligence, and blockchain: implementation perspectives. In S. Kim & G. C. Deka (Eds.), Advanced applications of blockchain technology (pp. 15–54). Springer. https://doi.org/10.1007/978-981-13-8775-3_2.
Saghiri, A. M., Vahdati, M., Gholizadeh, K., Meybodi, M. R., Dehghan, M., & Rashidi, H. (2018). A framework for cognitive Internet of Things based on blockchain. In 2018 4th International Conference on Web Research (ICWR) (pp. 138–143). https://doi.org/10.1109/ICWR.2018.8387250.
Schwartz, J., King, C.-C., & Yen, M.-Y. (2020). Protecting healthcare workers during the coronavirus disease 2019 (COVID-19) outbreak: Lessons From Taiwan’s severe acute respiratory syndrome response. Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciaa255.
SimplyVital Health. (2020). SimplyVital health|F6S. https://www.f6s.com/simplyvitalhealth.
Srivastava, G., Crichigno, J., & Dhar, S. (2019). A light and secure healthcare blockchain for IoT medical devices. IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), 2019, 1–5. https://doi.org/10.1109/CCECE.2019.8861593.
Stark, J. (2016, June 4). Making sense of blockchain smart contracts. CoinDesk. https://www.coindesk.com/making-sense-smart-contracts.
Szabo, N. (1996). Smart contracts: Building blocks for digital markets. Extropy, 16(18), 2.
Torky, M., & Hassanien, A. E. (2020). COVID-19 blockchain framework: Innovative approach. ArXiv:2004.06081 [Cs]. https://arxiv.org/abs/2004.06081.
Vahdati, M., Gholizadeh HamlAbadi, K., Saghiri, A. M., & Rashidi, H. (2018). A self-organized framework for insurance based on internet of things and blockchain. In 2018 IEEE 6th international conference on future internet of things and cloud (FiCloud) (pp. 169–175). https://doi.org/10.1109/FiCloud.2018.00032.
Wang, S., Ouyang, L., Yuan, Y., Ni, X., Han, X., & Wang, F.-Y. (2019a). Blockchain-enabled smart contracts: Architecture, applications, and future trends. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(11), 2266–2277. https://doi.org/10.1109/TSMC.2019.2895123.
Wang, W., Hoang, D. T., Hu, P., Xiong, Z., Niyato, D., Wang, P., et al. (2019b). A survey on consensus mechanisms and mining strategy management in blockchain networks. IEEE Access, 7, 22328–22370. https://doi.org/10.1109/ACCESS.2019.2896108.
Wang, Y., Samavi, R., & Sood, N. (2019c). Blockchain-based marketplace for software testing. In 2019 17th international conference on privacy, security and trust (PST) (pp. 1–3). https://doi.org/10.1109/PST47121.2019.8949025.
Wang, Y., Kwong, S., Leung, H., Lu, J., Smith, M. H., Trajkovic, L., et al. (2020). Brain-inspired systems: A transdisciplinary exploration on cognitive cybernetics, humanity, and systems science toward autonomous artificial intelligence. IEEE Systems, Man, and Cybernetics Magazine, 6(1), 6–13. https://doi.org/10.1109/MSMC.2018.2889502.
Xia, Q., Sifah, E. B., Asamoah, K. O., Gao, J., Du, X., & Guizani, M. (2017). MeDShare: Trust-less medical data sharing among cloud service providers via blockchain. IEEE Access, 5, 14757–14767. https://doi.org/10.1109/ACCESS.2017.2730843.
XMED Chain. (2018). MED chain (XMC) is the world 1st global medical blockchain and AI big data platform, specializing in cross-border medical solutions. https://www.accesswire.com/491915/XMED-Chain-XMC-is-the-World-1st-Global-Medical-Blockchain-and-AI-Big-Data-Platform-Specializing-in-Cross-border-Medical-Solutions.
Zhang, K., Vitenberg, R., & Jacobsen, H.-A. (2018). Deconstructing blockchains: Concepts, systems, and insights. In Proceedings of the 12th ACM international conference on distributed and event-based systems (pp. 187–190). https://doi.org/10.1145/3210284.3219502.
Acknowledgements
Last but not least, I am dedicating this chapter to my late father Mohammad Vahdati gone forever away from our loving eyes and who left a void never to be filled ever. Though your life was short, I will make sure your memory lives on as long as I shall live. I love you all and miss you all beyond words.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Vahdati, M., Gholizadeh HamlAbadi, K., Saghiri, A.M. (2021). IoT-Based Healthcare Monitoring Using Blockchain. In: Namasudra, S., Deka, G.C. (eds) Applications of Blockchain in Healthcare. Studies in Big Data, vol 83. Springer, Singapore. https://doi.org/10.1007/978-981-15-9547-9_6
Download citation
DOI: https://doi.org/10.1007/978-981-15-9547-9_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9546-2
Online ISBN: 978-981-15-9547-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)