RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review
With the development of intelligent manufacturing in China, Radio Frequency Identification (RFID), a key technology for smart factories, has received widespread attention. As RFID applications expand, so does the size of their networks. It makes it more difficult to ensure RFID signal coverage, lea...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Ieee Acces
2024
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/12294/1/J17728_689559ccc061dbc5987d4740a173b2cc.pdf |
| _version_ | 1824446615043178496 |
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| author | YEJIAO, WANG KAMALUDIN, HAZALILA MOHAMMED ALDUAIS, NAYEF ABDULWAHAB MOHD SAFAR, NOOR ZURAIDIN ZHONGCHAO, HAO |
| author_facet | YEJIAO, WANG KAMALUDIN, HAZALILA MOHAMMED ALDUAIS, NAYEF ABDULWAHAB MOHD SAFAR, NOOR ZURAIDIN ZHONGCHAO, HAO |
| author_sort | YEJIAO, WANG |
| collection | UTHM |
| description | With the development of intelligent manufacturing in China, Radio Frequency Identification (RFID), a key technology for smart factories, has received widespread attention. As RFID applications expand, so does the size of their networks. It makes it more difficult to ensure RFID signal coverage,
leads to communication problems, and increases equipment energy consumption and costs, thereby posing challenges in the realm of RFID network planning (RNP). The RNP problem needs to consider multiple objectives and constraints such as coverage, conflicts, economic benefit, and load balance which have been proven to be optimized by swarm intelligent optimization algorithms. Therefore, this study reviews smart
factories, RFID technology, swarm intelligence optimization algorithms and RFID network planning. The improvement direction of swarm intelligence optimization algorithms and factors affecting RFID network performance are also explored. In addition, it reviews and analyzes the applications of swarm intelligence algorithms to RNP problems and discusses the innovations and drawbacks of these approaches. Finally, some research limitations and directions are identified. |
| first_indexed | 2025-02-19T01:17:58Z |
| format | Article |
| id | uthm.eprints-12294 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2025-02-19T01:17:58Z |
| publishDate | 2024 |
| publisher | Ieee Acces |
| record_format | dspace |
| spelling | uthm.eprints-122942024-12-16T23:49:52Z http://eprints.uthm.edu.my/12294/ RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review YEJIAO, WANG KAMALUDIN, HAZALILA MOHAMMED ALDUAIS, NAYEF ABDULWAHAB MOHD SAFAR, NOOR ZURAIDIN ZHONGCHAO, HAO TK Electrical engineering. Electronics Nuclear engineering With the development of intelligent manufacturing in China, Radio Frequency Identification (RFID), a key technology for smart factories, has received widespread attention. As RFID applications expand, so does the size of their networks. It makes it more difficult to ensure RFID signal coverage, leads to communication problems, and increases equipment energy consumption and costs, thereby posing challenges in the realm of RFID network planning (RNP). The RNP problem needs to consider multiple objectives and constraints such as coverage, conflicts, economic benefit, and load balance which have been proven to be optimized by swarm intelligent optimization algorithms. Therefore, this study reviews smart factories, RFID technology, swarm intelligence optimization algorithms and RFID network planning. The improvement direction of swarm intelligence optimization algorithms and factors affecting RFID network performance are also explored. In addition, it reviews and analyzes the applications of swarm intelligence algorithms to RNP problems and discusses the innovations and drawbacks of these approaches. Finally, some research limitations and directions are identified. Ieee Acces 2024 Article PeerReviewed text en http://eprints.uthm.edu.my/12294/1/J17728_689559ccc061dbc5987d4740a173b2cc.pdf YEJIAO, WANG and KAMALUDIN, HAZALILA and MOHAMMED ALDUAIS, NAYEF ABDULWAHAB and MOHD SAFAR, NOOR ZURAIDIN and ZHONGCHAO, HAO (2024) RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review. Digital Object Identifier. pp. 64980-64996. https://doi.org/ 10.1109/ACCESS.2024.3397402 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering YEJIAO, WANG KAMALUDIN, HAZALILA MOHAMMED ALDUAIS, NAYEF ABDULWAHAB MOHD SAFAR, NOOR ZURAIDIN ZHONGCHAO, HAO RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review |
| title | RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review |
| title_full | RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review |
| title_fullStr | RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review |
| title_full_unstemmed | RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review |
| title_short | RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review |
| title_sort | rfid network planning of smart factory based on swarm intelligent optimization algorithm a review |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.uthm.edu.my/12294/1/J17728_689559ccc061dbc5987d4740a173b2cc.pdf |
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