A blockchain-based framework for trusted quality data sharing towards zero-defect manufacturing

Isaja, Mauro; Nguyen, Phu H.; Göknil, Arda; Sen, Sagar; Husom, Erik Johannes; Tverdal, Simeon; Anand, Abhilash; Jiang, Yunman; Pedersen, Karl John; Myrseth, Per; Stang, Jørgen; Niavis, Harris; Pfeifhofer, Simon; Lamplmair, Patrick

doi:10.1016/j.compind.2023.103853

Cited by 30 publications

(3 citation statements)

References 22 publications

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“…To allow safe and private data sharing among IoT devices, Li [3] suggested a blockchain-based model for IoT data sharing. Smart contracts are used by Isaja et al [4] to handle access control and information-sharing policies in their blockchainbased architecture for secure and reliable data sharing in the Internet of Things. A blockchain-based information-sharing strategy for the Internet of Things was put forth by Muhammed et al [5].…”

Section: Related Workmentioning

confidence: 99%

BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts

M. Rajkumar, N. S. Usha

2023

IJRITCC

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The rapid growth and integration of the Internet of Things (IoT) emphasizes the crucial need for effective data governance. This research unveils a novel framework, capitalizing on blockchain and smart contracts, aimed at decentralizing data governance in the IoT sphere. Our approach allows stakeholders to formulate and enforce data governance collaboratively, ensuring a balance between transparency, adaptability, and flexibility. Using the Ethereum platform and Solidity as our smart contract language, we constructed a demonstrative proof-of-concept. Our comparative evaluations highlighted our system's superiority, outpacing previous works with a scalability score of 95%, flexibility at 90%, and an unmatched transparency score of 100%. This framework presents a transformative paradigm for organizations and individuals working with IoT data, offering an efficient, transparent, and robust data governance mechanism.

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Section: Related Workmentioning

confidence: 99%

BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts

M. Rajkumar, N. S. Usha

2023

IJRITCC

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“…The authors implemented a prototype of MapChain-D using open-source communication protocols and blockchain platforms and show that it is more suitable for resource-constrained IIoT devices. Isaja et al [14] designed a heterogeneous encrypted data sharing scheme supported by blockchain, which is used for tucker decomposition to protect privacy when the homomorphic encryption method extracts knowledge. Feng et al [15] emphasized the significance of data analysis and the sharing of data between stakeholders in order to achieve greater values.…”

Section: Progress Of Researchmentioning

confidence: 99%

Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain

Wu,

Liang,

Chen

et al. 2023

Journal on Big Data

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Enabling data sharing among smart grid power suppliers is a pressing challenge due to technical hurdles in verifying, storing, and synchronizing energy metering data. Access and sharing limitations are stringent for users, power companies, and researchers, demanding significant resources and time for permissions and verification. This paper proposes a blockchain-based architecture for secure and efficient sharing of electric energy metering data. Further, we propose a data sharing model based on evolutionary game theory. Based on the Lyapunov stability theory, the model's evolutionary stable strategy (ESS) is analyzed. Numerical results verify the correctness and practicability of the scheme proposed in this paper, and provide a new method for realizing convenient, safe and fast data sharing.

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“…The Industrial Internet of Things (IIoT) is the interconnection of sensors, computing devices (on the edge and the cloud), and industrial machines (e.g., industrial robots, machine tools, boilers) in a production network. IIoT provides streaming access to thousands of sources of time-varying data from sensors used in numerous use cases supported by Machine Learning (ML) applications [1], [2]. These applications include predictive maintenance [3], remote quality monitoring [4], and energy optimization [5].…”

Section: Introductionmentioning

confidence: 99%

Replay-Driven Continual Learning for the Industrial Internet of Things

Sen

Nielsen

Husom

et al. 2023

2023 IEEE/ACM 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN)

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The Industrial Internet of Things (IIoT) leverages thousands of interconnected sensors and computing devices to monitor and control large and complex industrial processes. Machine learning (ML) applications in IIoT use data acquired from multiple sensors to perform tasks such as predictive maintenance. While remembering useful learning from the past, these applications need to adapt learning for evolving sensor data stemming from changes in industrial processes and environmental conditions. This paper presents a continual learning pipeline to learn from the evolving data while replaying selected parts of the old data. The pipeline is configured to produce ML experiences (e.g., training a baseline neural network model), improve the baseline model with the new data while replaying part of the old data, and infer/predict using a specific model version given a stream of IIoT sensor data. We have evaluated our approach from an AI Engineering perspective using three industrial case studies, i.e., predicting tool wear, remaining useful lifetime, and anomalies from sensor data acquired from CNC machining and broaching operations. Our results show that configuring experiences for replay-driven continual learning allows dynamic maintenance of ML performance on evolving data while minimizing the excessive accumulation of legacy sensor data.

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A blockchain-based framework for trusted quality data sharing towards zero-defect manufacturing

Cited by 30 publications

References 22 publications

BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts

BlockGov: Blockchain-Based Data Governance in the Internet of Things using Smart Contracts

Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain

Replay-Driven Continual Learning for the Industrial Internet of Things

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