| 1. |
- Chen, Feng, et al.
(författare)
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Data mining for the internet of things : Literature review and challenges
- 2015
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Ingår i: International Journal of Distributed Sensor Networks. - : SAGE Publications. - 1550-1329 .- 1550-1477. ; 2015
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Tidskriftsartikel (refereegranskat)abstract
- The massive data generated by the Internet of Things (IoT) are considered of high business value, and data mining algorithms can be applied to IoT to extract hidden information from data. In this paper, we give a systematic way to review data mining in knowledge view, technique view, and application view, including classification, clustering, association analysis, time series analysis and outlier analysis. And the latest application cases are also surveyed. As more and more devices connected to IoT, large volume of data should be analyzed, the latest algorithms should be modified to apply to big data. We reviewed these algorithms and discussed challenges and open research issues. At last a suggested big data mining system is proposed
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| 2. |
- Leng, Jiewu, et al.
(författare)
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Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges
- 2024
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Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 73, s. 349-363
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Forskningsöversikt (refereegranskat)abstract
- With the continuous development of human-centric, resilient, and sustainable manufacturing towards Industry 5.0, Artificial Intelligence (AI) has gradually unveiled new opportunities for additional functionalities, new features, and tendencies in the industrial landscape. On the other hand, the technology-driven Industry 4.0 paradigm is still in full swing. However, there exist many unreasonable designs, configurations, and implementations of Industrial Artificial Intelligence (IndAI) in practice before achieving either Industry 4.0 or Industry 5.0 vision, and a significant gap between the individualized requirement and actual implementation result still exists. To provide insights for designing appropriate models and algorithms in the upgrading process of the industry, this perspective article classifies IndAI by rating the intelligence levels and presents four principles of implementing IndAI. Three significant opportunities of IndAI, namely, collaborative intelligence, self-learning intelligence, and crowd intelligence, towards Industry 5.0 vision are identified to promote the transition from a technology-driven initiative in Industry 4.0 to the coexistence and interplay of Industry 4.0 and a value-oriented proposition in Industry 5.0. Then, pathways for implementing IndAI towards Industry 5.0 together with key empowering techniques are discussed. Social barriers, technology challenges, and future research directions of IndAI are concluded, respectively. We believe that our effort can lay a foundation for unlocking the power of IndAI in futuristic Industry 5.0 research and engineering practice.
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| 3. |
- Li, Di, et al.
(författare)
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Towards a model-integrated computing paradigm for reconfigurable motion control system
- 2017
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Ingår i: IEEE International Conference on Industrial Informatics (INDIN). - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 9781509028702 ; , s. 756-761
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Konferensbidrag (refereegranskat)abstract
- To accommodate the trend toward mass customization launched by intelligent manufacturing, the paper proposes the adoption of model-integrated computing (MIC) paradigm in the motion control system development process for enhancing flexibility and robustness. Hierarchical structural and behavioral diversities in motion control system are considered during the implementation of MIC paradigm. For design-phase implementation, a motion-control-domain-specific modeling language is developed, and formal semantics are integrated. With regard to execution-phase implementation, a real-time runtime framework compliant with the IEC 61499 standard is proposed. Extensions of function block chain and priority-based event propagation are proposed. Dynamically extendable FB types library for motion control domain is constructed. A prototype three-axis motion control system is modeled using the proposed modelling language and is then deployed to the implemented framework to prove the feasibility of the adoption of the MIC paradigm in motion control domain
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| 4. |
- Li, Xiaomin, et al.
(författare)
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A review of industrial wireless networks in the context of Industry 4.0
- 2017
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Ingår i: Wireless networks. - : Springer. - 1022-0038 .- 1572-8196. ; 23:1, s. 23-41
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Tidskriftsartikel (refereegranskat)abstract
- There have been many recent advances in wireless communication technologies, particularly in the area of wireless sensor networks, which have undergone rapid development and been successfully applied in the consumer electronics market. Therefore, wireless networks (WNs) have been attracting more attention from academic communities and other domains. From an industrial perspective, WNs present many advantages including flexibility, low cost, easy deployment and so on. Therefore, WNs can play a vital role in the Industry 4.0 framework, and can be used for smart factories and intelligent manufacturing systems. In this paper, we present an overview of industrial WNs (IWNs), discuss IWN features and related techniques, and then provide a new architecture based on quality of service and quality of data for IWNs. We also propose some applications for IWNs and IWN standards. Then, we will use a case from our previous achievements to explain how to design an IWN under Industry 4.0. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make IWNs truly ubiquitous for a wide range of applications.
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| 5. |
- Liu, Yongxin, et al.
(författare)
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Exploring data validity in transportation systems for smart cities
- 2017
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Ingår i: IEEE Communications Magazine. - : Institute of Electrical and Electronics Engineers (IEEE). - 0163-6804 .- 1558-1896. ; 55:5, s. 26-33
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Tidskriftsartikel (refereegranskat)abstract
- Efficient urban transportation systems are widely accepted as essential infrastructure for smart cities, and they can highly increase a city°s vitality and convenience for residents. The three core pillars of smart cities can be considered to be data mining technology, IoT, and mobile wireless networks. Enormous data from IoT is stimulating our cities to become smarter than ever before. In transportation systems, data-driven management can dramatically enhance the operating efficiency by providing a clear and insightful image of passengers° transportation behavior. In this article, we focus on the data validity problem in a cellular network based transportation data collection system from two aspects: Internal time discrepancy and data loss. First, the essence of time discrepancy was analyzed for both automated fare collection (AFC) and automated vehicular location (AVL) systems, and it was found that time discrepancies can be identified and rectified by analyzing passenger origin inference success rate using different time shift values and evolutionary algorithms. Second, the algorithmic framework to handle location data loss and time discrepancy was provided. Third, the spatial distribution characteristics of location data loss events were analyzed, and we discovered that they have a strong and positive relationship with both high passenger volume and shadowing effects in urbanized areas, which can cause severe biases on passenger traffic analysis. Our research has proposed some data-driven methodologies to increase data validity and provided some insights into the influence of IoT level data loss on public transportation systems for smart cities.
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| 6. |
- Lu, Yuqian, et al.
(författare)
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Smart manufacturing enabled by intelligent technologies
- 2024
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Ingår i: International journal of computer integrated manufacturing (Print). - : Informa UK Limited. - 0951-192X .- 1362-3052. ; 37:1-2, s. 1-3
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Shu, Zhaogang, et al.
(författare)
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Security in Software-Defined Networking : Threats and Countermeasures
- 2016
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Ingår i: Mobile Networks and Applications. - : Springer Science and Business Media LLC. - 1383-469X .- 1572-8153. ; 21:5, s. 764-776
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, Software-Defined Networking (SDN) has been a focus of research. As a promising network architecture, SDN will possibly replace traditional networking, as it brings promising opportunities for network management in terms of simplicity, programmability, and elasticity. While many efforts are currently being made to standardize this emerging paradigm, careful attention needs to be also paid to security at this early design stage. This paper focuses on the security aspects of SDN. We begin by discussing characteristics and standards of SDN. On the basis of these, we discuss the security features as a whole and then analyze the security threats and countermeasures in detail from three aspects, based on which part of the SDN paradigm they target, i.e., the data forwarding layer, the control layer and the application layer. Countermeasure techniques that could be used to prevent, mitigate, or recover from some of such attacks are also described, while the threats encountered when developing these defensive mechanisms are highlighted.
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| 8. |
- Wan, Jiafu, et al.
(författare)
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A Manufacturing Big Data Solution for Active Preventive Maintenance
- 2017
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 13:4, s. 2039-2047
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Tidskriftsartikel (refereegranskat)abstract
- Industry 4.0 has become more popular due to recent developments in Cyber-Physical Systems (CPS), big data, cloud computing, and industrial wireless networks. Intelligent manufacturing has produced a revolutionary change, and evolving applications such as product lifecycle management are becoming a reality. In this paper, we propose and implement a manufacturing big data solution for active preventive maintenance in manufacturing environments. First, we provide the system architecture that is used for active preventive maintenance. Then, we analyze the method used for collection of manufacturing big data according to the data characteristics. Subsequently, we perform data processing in the cloud, including the cloud layer architecture, the real-time active maintenance mechanism, and the off-line prediction and analysis method. Finally, we analyze a prototype platform and implement experiments to compare the traditionally-used method with the proposed active preventive maintenance method. The manufacturing big data method used for active preventive maintenance has the potential to accelerate implementation of Industry 4.0.
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| 9. |
- Wan, Jiafu, et al.
(författare)
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Cloud robotics: Current status and open issues
- 2016
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 4, s. 2797-2807
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Tidskriftsartikel (refereegranskat)abstract
- With the development of cloud computing, big data and other emerging technologies, the integration of cloud technology and multi-robot systems makes it possible to design multi-robot systems with improved energy efficiency, high real-time performance and low cost. In order to address the potential of clouds in enhancing robotics for industrial systems, this paper describes the basic concepts and development process of cloud robotics and the overall architecture of these systems. Then, the major driving forces behind the development of cloud robotics are carefully analyzed from the point of view of cloud computing, big data, open source resources, robot cooperative learning, and network connectivity. Subsequently, the key issues and challenges in the current cloud robotic systems are proposed, and some possible solutions are also given. Finally, the potential value of cloud robotic systems in different practical applications is discussed.
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| 10. |
- Wan, Jiafu, et al.
(författare)
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Guest Editorial Special Issue on Cloud-Integrated Cyber-Physical Systems
- 2017
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Ingår i: IEEE Systems Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-8184 .- 1937-9234. ; 11:1, s. 84-87
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The advances in wireless sensor devices, big data, mobile computing, and cloud computing offer tremendous opportunities to realize the seamless integration between the physical world and the cyber space. The cloud-integrated cyberphysical system (CCPS) refers to virtually representing physical system components, such as sensors, actuators, robots, and other devices in clouds, accessing (e.g., monitoring, actuating and navigating) those physical components through their virtual representations, and processing/managing/controlling the large amount of data collected from physical components in clouds in a scalable, real-time, efficient, and reliable manner. Particularly, integrating cloud computing techniques (e.g., virtualization, elastic re-configuration, and multi-tenancy of resources) with CPS techniques (e.g., real-time scheduling, adaptive resource management and control, and embedded system design) will bring hope to advance the state of the art, and allow previously unachievable systems such as cloud-integrated internet of vehicles to be built, deployed, managed, and controlled effectively. This Special Issue on CCPS solicits the manuscripts on rigorous research on theories, methodologies, tools, and testbeds for CCPS. In this special issue, we selected ten papers. Each paper was carefully reviewed by peer review and guest editors. In the following, we will overview the accepted papers that reflect recent advances.
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