Survey on fog computing

The growth of individualized product demands drives high flexibility of manufacturing processes, which requires large-scale deployment of Industrial Internet of Things (IIoT). Since centralized control of IIoT suffers from poor flexibility in coping with disturbances and changes, a decentralized organization structure is a better choice, in which a permissioned blockchain-driven IIoT can enable partially decentralized self-organization and thus offload and accelerate the optimization of upper-level manufacturing planning. A novel iterative bi-level hybrid intelligence model named ManuChain is proposed to get rid of unbalance/inconsistency between holistic planning and local execution in individualized manufacturing systems. Lower-level blockchain-driven smart contracts proactively decentralize fine-grained and individualized task execution among machine tools via Raspberry Pi-based smart gateways and make the results available on an upper-level digital twin model for iterative coarse-grained holistic optimization. A prototype ManuChain based on a permissioned blockchain network is presented to realize both lower-level crowd self-organizing intelligence and upper-level holistic optimization intelligence.

ManuChain: Combining Permissioned Blockchain With a Holistic Optimization Model as Bi-Level Intelligence for Smart Manufacturing

Data aggregation mechanisms in the Internet of things

The connection of embedded computing devices via the Internet has dramatically changed the way people live. This concept has also been extended to the industrial sector. It not only provides a more reliable, real-time and secure communications, but also enables the smart factory concept in the fourth industrial revolution to be realized. However, in the current literature, there is still a lack of a formal and objective review that specifically focuses on this topic. This paper aims to address this gap. First, the applied systematic literature review method is explained. Findings and insights are then illustrated through the analysis of the collected data related to the four research questions. Finally, the strengths and limitations of the work are summarized.

Industrial Internet of Things: A Systematic Literature Review and Insights

In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision-making. This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation. Further, it elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion. This paper also aims to address data analysis integration with emerging technologies, such as cloud computing, fog computing and edge computing, towards various challenges in IoT sensor network and sensor data analysis. In summary, this paper is the first of its kind to present a complete overview of IoT sensor data processing, fusion and analysis techniques.

An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques.

An architecture for aggregating information from distributed data nodes for industrial internet of things

With the advent of the post-epidemic era, O2O e-commerce on community breaks through the original business model and forms a new online-to-offline integrated business model. This study is based on the value co-creation perspective and the TAM-TPB theory systematically builds a theoretical model of consumers’ continuous use intention of O2O e-commerce on the community. A structural equation model (SEM) was used to verify the research hypotheses. The research results were as follows: (1) the subjective norms and structural assurance in social factors have a positive impact on consumers’ continuous use intention; (2) the degree of convenience and safety in platform factors not only positively affect customer satisfaction but also positively affect customers’ continuous use intension, and customer satisfaction mediates between platform factors and customers’ continuous use intension; (3) customer–enterprise co-creation has a positive impact on customer perceived value, and customer perceived value plays a mediating role between customer–enterprise co-creation behavior and consumers’ willingness to continue using; (4) customer perceived value and customer satisfaction in the user factor have a significant impact on consumers’ continuous use intention.

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Zhihao Zhou

Papers

An architecture for aggregating information from distributed data nodes for industrial internet of things

Consumers’ Continuous Use Intention of O2O E-Commerce Platform on Community: A Value Co-Creation Perspective