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iBlock: An Intelligent Decentralised Blockchain-based Pandemic Detection and Assisting System

Publication Type : Journal Article

Publisher : Springer

Source : Journal of Signal Processing Systems

Url :

Campus : Amaravati

School : School of Engineering

Year : 2021

Abstract : The recent COVID-19 outbreak highlighted the requirement for a more sophisticated healthcare system and real-time data analytics in the pandemic mitigation process. Moreover, real-time data plays a crucial role in the detection and alerting process. Combining smart healthcare systems with accurate real-time information about medical service availability, vaccination, and how the pandemic is spreading can directly affect the quality of life and economy. The existing architecture models are become inadequate in handling the pandemic mitigation process using real-time data. The present models are server-centric and controlled by a single party, where the management of confidentiality, integrity, and availability (CIA) of data is doubtful. Therefore, a decentralised user-centric model is necessary, where the CIA of user data is assured. In this paper, we have suggested a decentralized blockchain-based pandemic detection and assistance system (iBlock). The iBlock uses robust technologies like hybrid computing and IPFS to support system functionality. A pseudo-anonymous personal identity is introduced using H-PCS and cryptography for anonymous data sharing. The distributed data management module guarantees data CIA, security, and privacy using cryptography mechanisms. Furthermore, it delivers useful intelligent information in the form of suggestions and alerts to assist the users. Finally, the iBlock reduces stress on healthcare infrastructure and workers by providing accurate predictions and early warnings using AI/ML.

Cite this Research Publication : Egala, B.S., Pradhan, A.K., Badarla, V. et al. “iBlock: An Intelligent Decentralised Blockchainbased Pandemic Detection and Assisting System”. J Sign Process Syst (2021). doi:10.1007/s11265- 021-01704-9.

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