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Blockchain-based deep learning in IoT, healthcare and cryptocurrency price prediction: a comprehensive review

Shefali Arora (Department of Computer Science and Engineering, National Institute of Technology Jalandhar, Jalandhar, India)
Ruchi Mittal (Data Tech, ICONIC Data Inc., Tokyo, Japan)
Avinash K. Shrivastava (Department of Operations Management and Quantitative Techniques, International Management Institute Kolkata, Kolkata, India)
Shivani Bali (Department of Analytics, Jaipuria Institute of Management Noida, Noida, India)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 27 February 2024

Issue publication date: 10 September 2024

213

Abstract

Purpose

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

Design/methodology/approach

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

Findings

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

Originality/value

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.

Keywords

Citation

Arora, S., Mittal, R., Shrivastava, A.K. and Bali, S. (2024), "Blockchain-based deep learning in IoT, healthcare and cryptocurrency price prediction: a comprehensive review", International Journal of Quality & Reliability Management, Vol. 41 No. 8, pp. 2199-2225. https://doi.org/10.1108/IJQRM-12-2022-0373

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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