A Secure Blockchain Platform for Supporting AI-Enabled IoT Applications at the Edge Layer

【Author】 Alrubei, Subhi M.; Ball, Edward; Rigelsford, Jonathan M.

【Source】IEEE ACCESS

【影响因子】3.476

【Abstract】In this study, a new blockchain protocol and a novel architecture that integrate the advantages offered by edge computing, artificial intelligence (AI), IoT end-devices, and blockchain were designed, developed, and validated. This new architecture has the ability to monitor the environment, collect data, analyze it, process it using an AI-expert engine, provide predictions and actionable outcomes, and finally share it on a public blockchain platform. For the use-case implementation, the pandemic caused by the wide and rapid spread of the novel coronavirus COVID-19 was used to test and evaluate the proposed system. Recently, various authors traced the spread of viruses in sewage water and studied how it can be used as a tracking system. Early warning notifications can allow governments and organizations to take appropriate actions at the earliest stages possible. The system was validated experimentally using 14 Raspberry Pis, and the results and analyses proved that the system is able to utilize low-cost and low-power flexible IoT hardware at the processing layer to detect COVID-19 and predict its spread using the AI engine, with an accuracy of 95%, and share the outcome over the blockchain platform. This is accomplished when the platform is secured by the honesty-based distributed proof of authority (HDPoA) and without any substantial impact on the devices' power sources, as there was only a power consumption increase of 7% when the Raspberry Pi was used for blockchain mining and 14% when used to produce an AI prediction.

【Keywords】Blockchains; Internet of Things; Artificial intelligence; Security; Computer architecture; Smart contracts; Edge computing; Edge computing; blockchain protocol; the Internet of Things (IoT); flexible IoT hardware; artificial intelligence (AI); coronavirus disease (COVID-19)

【发表时间】2022

【收录时间】2022-08-28

【文献类型】实证数据

【主题类别】

区块链技术-协同技术-物联网