Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT
Industrial Internet of Things (IIoT) is systems aim to facilitate human monitoring and the direction of efficient production of goods in industrial settings by linking a wide variety of intelligent devices such as sensors, actuators, and controllers. This is achieved by utilizing Internet of Things...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Measurement: Sensors |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917423002805 |
| _version_ | 1797258683141324800 |
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| author | Deepak sharma Anuj kumar Nitin Tyagi Sunil S. Chavan Syam Machinathu Parambil Gangadharan |
| author_facet | Deepak sharma Anuj kumar Nitin Tyagi Sunil S. Chavan Syam Machinathu Parambil Gangadharan |
| author_sort | Deepak sharma |
| collection | DOAJ |
| description | Industrial Internet of Things (IIoT) is systems aim to facilitate human monitoring and the direction of efficient production of goods in industrial settings by linking a wide variety of intelligent devices such as sensors, actuators, and controllers. This is achieved by utilizing Internet of Things (IoT) to diagnose a problem with a specific IIoT part is to employ a basic diagnostic technique that's based on models and data. Physical models, signal patterns, and machine-learning strategies must be adequately built to account for system challenges. Another factor that could lead to an exponential rise in complexity is the ever-increasing interconnections between different electronic hardware. The knowledge-based defect diagnosis methods boost interoperability in the operation. Users don't need to be experts in the field to benefit from the system's high-level thinking and response to their queries. So, in advanced IIoT systems, a knowledge-based fault diagnostic approach is favored over traditional model-based and data-driven diagnosis methods. The goal of this study is to evaluate recent improvements in the design of knowledge-based defect detection in the context of IIoT systems, deductive and inductive reasoning, and many other forms of logical reasoning. IIoT-based systems have revolutionized industrial settings by connecting intelligent devices such as sensors, actuators, and controllers to enable efficient production and human monitoring. In this survey paper, we explore machine learning-based sensor fusion techniques within the realm of Industrial Internet of Things (IIoT), addressing critical challenges in fault detection and diagnosis. |
| first_indexed | 2024-03-08T11:53:40Z |
| format | Article |
| id | doaj.art-cc91802ba9924d28b67244423a31ff5c |
| institution | Directory Open Access Journal |
| issn | 2665-9174 |
| language | English |
| last_indexed | 2024-04-24T22:57:26Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj.art-cc91802ba9924d28b67244423a31ff5c2024-03-18T04:34:33ZengElsevierMeasurement: Sensors2665-91742024-04-0132100944Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoTDeepak sharma0Anuj kumar1Nitin Tyagi2Sunil S. Chavan3Syam Machinathu Parambil Gangadharan4Department of Computer Science, Aryabhatta College, University of Delhi, IndiaDepartment of Information Technology, Management Education & Research Institute (MERI), Guru Gobind Singh Indraprasth University, Janakpuri, Delhi, IndiaDepartment of Computer Science and Engineering, GL Bajaj Institute of Technology and Management, Greater Noida, IndiaSmt.Indira Gandhi College of Engineering, University of Mumbai, Navi Mumbai, India; Corresponding author.Liverpool John Moores University, USAIndustrial Internet of Things (IIoT) is systems aim to facilitate human monitoring and the direction of efficient production of goods in industrial settings by linking a wide variety of intelligent devices such as sensors, actuators, and controllers. This is achieved by utilizing Internet of Things (IoT) to diagnose a problem with a specific IIoT part is to employ a basic diagnostic technique that's based on models and data. Physical models, signal patterns, and machine-learning strategies must be adequately built to account for system challenges. Another factor that could lead to an exponential rise in complexity is the ever-increasing interconnections between different electronic hardware. The knowledge-based defect diagnosis methods boost interoperability in the operation. Users don't need to be experts in the field to benefit from the system's high-level thinking and response to their queries. So, in advanced IIoT systems, a knowledge-based fault diagnostic approach is favored over traditional model-based and data-driven diagnosis methods. The goal of this study is to evaluate recent improvements in the design of knowledge-based defect detection in the context of IIoT systems, deductive and inductive reasoning, and many other forms of logical reasoning. IIoT-based systems have revolutionized industrial settings by connecting intelligent devices such as sensors, actuators, and controllers to enable efficient production and human monitoring. In this survey paper, we explore machine learning-based sensor fusion techniques within the realm of Industrial Internet of Things (IIoT), addressing critical challenges in fault detection and diagnosis.http://www.sciencedirect.com/science/article/pii/S2665917423002805Sensor fusionMachine learningFault toleranceFault predictionNeural network |
| spellingShingle | Deepak sharma Anuj kumar Nitin Tyagi Sunil S. Chavan Syam Machinathu Parambil Gangadharan Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT Measurement: Sensors Sensor fusion Machine learning Fault tolerance Fault prediction Neural network |
| title | Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT |
| title_full | Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT |
| title_fullStr | Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT |
| title_full_unstemmed | Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT |
| title_short | Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT |
| title_sort | towards intelligent industrial systems a comprehensive survey of sensor fusion techniques in iiot |
| topic | Sensor fusion Machine learning Fault tolerance Fault prediction Neural network |
| url | http://www.sciencedirect.com/science/article/pii/S2665917423002805 |
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