ArticleIEEE access : practical innovations, open solutions2018
A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective.
Article in IEEE access : practical innovations, open solutions, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Possible Applications of Edge Computing in the Manufacturing Industry-Systematic Literature Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Ecosystem simulation: the software to platform leap.Scientific reports · 2026Article
- Artificial Intelligence of Things for Next-Generation Predictive Maintenance.Sensors (Basel, Switzerland) · 2025Review
- An intelligent job scheduling and real-time resource optimization for edge-cloud continuum in next generation networks.Scientific reports · 2025Article
- Real-time monitoring and optimization methods for user-side energy management based on edge computing.Scientific reports · 2025Article
- Peak Age of Information Analysis in Systems with Multiple Time-Correlated Traffic Streams.Sensors (Basel, Switzerland) · 2025Article
- Editorial: Machine learning for cybersecurity.Frontiers in artificial intelligence · 2025Article
- Performance Analysis and Prediction of 5G Round-Trip Time Based on the VMD-LSTM Method.Sensors (Basel, Switzerland) · 2024Article
- A Dynamic IIoT Framework Based on the Publish-Subscribe Paradigm.Sensors (Basel, Switzerland) · 2023Article
- A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-Based Solutions, and Edge Computing Opportunities.Sensors (Basel, Switzerland) · 2023Review
- Performance Analysis of Embedded Multilayer Perceptron Artificial Neural Networks on Smart Cyber-Physical Systems for IoT Environments.Sensors (Basel, Switzerland) · 2023Article
- QCNN_BaOpt: Multi-Dimensional Data-Based Traffic-Volume Prediction in Cyber-Physical Systems.Sensors (Basel, Switzerland) · 2023Article
- Machine Learning-Enabled Smart Industrial Automation Systems Using Internet of Things.Sensors (Basel, Switzerland) · 2022Article
- Integrated Sensing and Communication: Enabling Techniques, Applications, Tools and Data Sets, Standardization, and Future Directions.IEEE internet of things journal · 2022Article
- Towards Deep Q-Network Based Resource Allocation in Industrial Internet of Things.IEEE internet of things journal · 2022Article
- Delay and Energy Consumption of MQTT over QUIC: An Empirical Characterization Using Commercial-Off-The-Shelf Devices.Sensors (Basel, Switzerland) · 2022Article
- A Comprehensive Review on Time Sensitive Networks with a Special Focus on Its Applicability to Industrial Smart and Distributed Measurement Systems.Sensors (Basel, Switzerland) · 2022Review
- Enabling the Industrial Internet of Things to Cloud Continuum in a Real City Environment.Sensors (Basel, Switzerland) · 2021Article
- Reliable Control Applications with Wireless Communication Technologies: Application to Robotic Systems.Sensors (Basel, Switzerland) · 2021Article
- Software-Defined Networking Solutions, Architecture and Controllers for the Industrial Internet of Things: A Review.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the Internet of Things (IoT) to enable the interconnection of anything, anywhere, and at anytime in the manufacturing system context to improve the productivity, efficiency, safety and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality of service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs, and to present a unified assessment of the technology from a systems perspective, in this paper we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation (FA) and process automation (PA)) and their characteristics. We then consider existing research efforts from the three key systems aspects of control, networking and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space, and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine (M2M) communication, and software defined networking (SDN). Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT, and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning, in an I-IoT context.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.