Showing papers in "Journal of Industrial Information Integration in 2020"

TL;DR: By selectively analyzing the literature, this paper systematically survey how the adoption of the above-mentioned Industry 4.0 technologies (and their integration) applied to the health domain is changing the way to provide traditional services and products.

TL;DR: The exploration revealed that due to the exponential uses of blockchain, investments involved, and a number of start-up businesses contributing to Industry 4.0, blockchain indeed has a credible potential in the construction industry.

TL;DR: Its prospects, core technologies, scenarios, challenges, and the related issues are discussed and a potential framework for 6 G is proposed as well.

TL;DR: The identification of a substantial disconnect in knowledge of 4.0 based on seniority, function and industry is identified, while the implementation of 5.0 is playing an increasingly significant role in the modernisation of the Pharmaceutical and Biopharmaceutical industries.

TL;DR: The results show that the overall relevance of the IIN of industrial sectors is low, and the network density fluctuates, with high network efficiency and poor stability.

TL;DR: In this paper, the authors review the state of the art on new emerging technologies, summarizing how ports and terminals are deploying specific projects in the new era of smart ports and ports 4.0.

TL;DR: An encoder-decoder structural model with a fully convolutional neural network, namely, PCSN, by referring to SegNet is proposed, which outperforms other algorithm on crack detection.

TL;DR: This paper presents a short but comprehensive review of these air pollution monitoring systems (APMS), their enabling technologies and protocols, and summaries the objectives that need to attain in the future air monitoring systems to make them more accurate and realistic.

TL;DR: Three autonomic cycles can create a coordinated plan for self-configuration, self-optimization, and self-healing during the manufacturing process that can be appropriately coordinated, oriented to autonomously manufacture Smart Products, detect failures, and recover from errors or failures.

TL;DR: The developed Integrated IoT architecture is experimentally validated in real-time lab-scale fluid transportation pipeline system and the performance of Linear Quadratic Regulator-PID controller to regulate pressure and flow rate of the fluid being tansported is analyzed by comparing with convnetional controllers like Internal-Mode controller and Zigler–Nichols controller.

TL;DR: The proposed digital twin is continuously capable to predict the production status and provide information for monitoring of production performance thanks to the real time connections of the RTLS and adaptive simulation models.

TL;DR: A mapping of tracking technologies and their suitability for industrial ARSG was done and identified Bluetooth, micro-electro mechanical sensors (MEMS) and infrared sensors as potentially suitable technologies to improve tracking.

TL;DR: A Systematic Literature Review (SLR) of simulation methods that deal with risks in SCs, with particular emphasis on the type of data integration employed by such works, is proposed.

TL;DR: A Cluster-Tree based Energy Efficient Data Gathering (CTEEDG) protocol is proposed to increase the lifetime and throughput of WSNs and reduces energy consumption when compared to the FAMACROW and DL-LEACH.

TL;DR: A preliminary study is conducted on cyber-physical based intelligent structural disaster prevention technologies and structural systems using the Building Information Model (BIM) platform and Internet of things (IoT) technology to achieve a high degree of integration of monitoring, identification and control.

TL;DR: In this article, the authors used bibliometric analysis to investigate trends and knowledge in Industry 4.0 research and compared it with that focused on the plastics industry by using data collected from current literature in the field.

TL;DR: This research hypothesizes that combining several big data analytical methods for analyzing integrated customer data can provide more effective and intelligent strategies, and proposes a hybrid model combining recency, frequency, and monetary value (RFM) model, K-means clustering, Naive Baye's algorithm, and linked Bloom filters to target different customer segments.

TL;DR: This paper looks into how the available technology, models and ontology-based solutions might interact within the manufacturing industry environment to achieve semantic interoperability among industrial information systems.

TL;DR: An integrated approach for service selection and composition to meet the needs of users and social system is presented and the Fuzzy Analytic Hierarchy Process (F-AHP) is introduced to evaluate non-functional specifications quantitatively with less uncertainty.

TL;DR: This paper will classify each category by their techniques and tasks that contribute to the significance of data representation in Geographic Visual Display and develop perspectives of each area and evaluating trends of Geographic Visual display Techniques.

TL;DR: A smart gateway is rationally designed for industrial interconnection scenes with hardware platformization and software modularization based on the idea of "software-defined", which obtains an advanced design concept, scalable architecture and strong applicability in heterogeneous scenes.

TL;DR: In this study, 5-core research areas and 100 research trends were identified and future directions with potential to steer future research were also given.

TL;DR: A novel temporal and spatial panorama stream processing engine is proposed that forms an effective link between bottom sensors and upper stream-based applications, and provides configurable, flexible, available and usable stream services for various upper applications.

TL;DR: This paper presents the architecture of a multi-agent system, which allows the capitalization of the distributed and heterogeneous knowledge, and how the agents extract knowledge from different users’ databases by using a semantic approach.

TL;DR: A technique that uses the operational data, produced in an organization, in order to model OT, with the purpose of applying analysis methods as those applied to enterprise modeling is presented.

TL;DR: A new graphical notation is introduced and evaluated in three industrial case-studies and proved that the notation is powerful in supporting the engineering of data collection and analysis architectures in industrial automation.

TL;DR: With the aid of the proposed method, the time of human inspection can be significantly reduced and the field safety can also be improved, and false alarms caused by sensor failure can be prevented, leading to increase in reliability of the facility monitoring system.