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A Scalable, Standards-Based Approach for IoT Data Sharing and Ecosystem Monetization

Authors :
Chonggang Wang
K. Figueredo
D. Seed
Source :
IEEE Internet of Things Journal. 9:5645-5652
Publication Year :
2022
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2022.

Abstract

The full potential of IoT data is often unrealized because data are restricted to single-purpose use-cases or accessible to a few, siloed users. The opportunities are significantly greater when data can be shared using a marketplace concept. This provides a framework where many suppliers of data can interact with consumers of data, such as AI developers and IoT service providers. Their marketplace interactions provide a means to identify demand for specific types of data and, to incentivize suppliers to offer high quality and dependable data. Standardization is a pre-requisite for an effective marketplace in terms of setting the rules for interactions and in establishing a technical baseline for data supply and consumption. This paper introduces an IoT data marketplace framework and illustrates its application through a set of smart city and intelligent transport system deployments. It highlights use of oneM2M, which is an open standard for the middleware layer in the IoT technology stack. oneM2M’s middleware capabilities reside between IoT devices and communications networks and, the AI/ML and IoT applications that consume IoT data. The proposed IoT data marketplace also includes licensing, usage tracking and secured data sharing features. These provide marketplace users with the tools to control data sharing and monetization. Through reference to multiple deployments of the IoT data marketplace, the paper highlights the benefits of standardization for replicable solutions in multiple IoT segments, interoperability, and business model innovation involving multi-stakeholder ecosystems.

Details

ISSN :
23722541
Volume :
9
Database :
OpenAIRE
Journal :
IEEE Internet of Things Journal
Accession number :
edsair.doi...........e251d10f6d5c2913de6766234474bf1b
Full Text :
https://doi.org/10.1109/jiot.2020.3023035