Collaborative Data-Access Enablers in the Industrial Internet of Things
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 1504
Special Issue Editors
Interests: IIoT; programmable logic controllers (PLC); machine learning
Interests: intelligent software; edge computing; intelligent control; embedded system; programmable technology
Special Issue Information
Dear Colleagues,
The Industrial Internet of Things (IIoT) is being increasingly implemented in various fields such as smart manufacturing, industrial automation, logistics, and warehousing to promote industrial modernization and intelligence. However, due to the differences in devices, data formats, and protocols involved in the IIoT, interoperability and standardization of data face challenges. Therefore, it is necessary to balance the diversity of devices and the consistency of data while achieving automation and intelligence on a large scale. Thus, standardization, data acquisition, data fusion, and scalable architecture play critical roles in overcoming the challenges of data interoperability and standardization in the IIoT. These technologies and solutions provide robust technological and theoretical support for achieving industrial intelligence.
In the IIoT domain, data access is a paramount research area. Nevertheless, numerous challenges must be confronted. Firstly, the sensors' colossal data collection demands an aptitude to accumulate and handle immense loads of data. This necessity encompasses efficacious access, transmission, storage, and management. Secondly, the multiformity of devices and technologies employed cultivates distinguishing data formats and divergent semantics, affording impediments to data integration and processing. Additionally, the data's profuse application venues underscore the indispensability of efficient processing, application and data security. Given the multitude of incompatible data sources, the challenge arises as to how to acquire these heterogeneous data flexibly, and how to uniformly format them to be suitable for a range of diverse applications. Only through surmounting these challenges can one manifest the efficiency, scalability, and customizability of IIoT systems.
In this special issue, we aim to provide a forum for colleagues to publish recent research results related to the frontiers of sensing data access, as well as comprehensive surveys of state-of-the-art industry intelligence in relevant specific areas. Both original contributions with theoretical novelty and practical solutions for addressing particular problems are solicited. Prospective authors are invited to submit original manuscripts reporting novel theoretical and experimental contributions on topics including but not limited to:
- Standardization of data access in IIoT;
- Trust and identity management in data access;
- Blockchain technologies in data access;
- Scalable architecture of data access in IIoT;
- Data acquisition in of data access in IIoT;
- Data fusion of data access in IIoT;
- Access control for shared data in IIoT devices;
- Communication protocols in data access;
- Machine learning or deep learning-based data access solutions in IIoT;
- Hardware and software co-design for data access;
- Cloud computing integration and big data analysis in data access.
Dr. Danfeng Sun
Prof. Dr. Huifeng Wu
Dr. Jin Fan
Guest Editors
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Keywords
- data access
- IIoT
- machine learning
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