IoT Data Qualification for a Logistic Chain Traceability Smart Contract

Area of Science:

• Logistics and Supply Chain Management
• Information Technology
• Blockchain Technology

Background:

• Supply chain traceability involves multiple stakeholders, requiring transparent data for contractual decisions.
• Internet of Things (IoT) and blockchain offer potential for automated, trusted logistic systems.
• Ensuring the quality of IoT data is critical for adopting these advanced technologies.

Purpose of the Study:

• To propose and evaluate an approach for assessing the data quality (DQ) of IoT data sources in logistic traceability.
• To develop a logistic traceability smart contract on a blockchain for automated data quality assessment.
• To establish a data quality model and distributed architecture tailored for the logistic chain domain.

Main Methods:

• Developed a logistic traceability smart contract on a blockchain.
• Selected and defined relevant data quality dimensions: accuracy, completeness, consistency, and currentness.
• Proposed measurement methods for selected data quality dimensions.
• Designed a distributed traceability architecture for the logistic chain.

Main Results:

• The proposed method effectively assesses the data quality of IoT data sources.
• The system ensures user agreement on data qualification rules.
• Demonstrated the capacity of the blockchain-based approach for reliable data quality assessment.

Conclusions:

• The developed approach enhances the trustworthiness of IoT data in logistic traceability.
• The proposed solution facilitates the development of automated and reliable logistic traceability systems.
• This work opens new avenues for leveraging blockchain and IoT in supply chain management.