RFID network planning using a new hybrid ANNs-based approach
Radio frequency identification (RFID) is a wireless technology that uses radio waves to automatically identify and track objects within a certain range. Due to the benefits of the technology, RFID technology has been adopted as a reliable and efficient solution and is an important technology used in...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Connection Science |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09540091.2022.2115011 |
| _version_ | 1797683980919635968 |
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| author | Mustapha Maimouni Badr Abou El Majd Mohsine Bouya |
| author_facet | Mustapha Maimouni Badr Abou El Majd Mohsine Bouya |
| author_sort | Mustapha Maimouni |
| collection | DOAJ |
| description | Radio frequency identification (RFID) is a wireless technology that uses radio waves to automatically identify and track objects within a certain range. Due to the benefits of the technology, RFID technology has been adopted as a reliable and efficient solution and is an important technology used in various IoT applications. The deployment of the RFID system has caused an RFID network planning (RNP) problem. However, the RNP problem can be defined as an NP-hard combinatorial optimisation problem that requires the examination of a large number of combinations to obtain the best solution. The goal of this research is to introduce and describe a new hybrid approach to solve the problem of RNP optimisation that is based on artificial intelligence algorithms that require a minimum number of initial parameters. Based on widely used benchmarks, our approach is compared against a hybrid approach based on the genetic algorithm, and the results are efficient, cost-effective and assure a good deployment of the RFID system. |
| first_indexed | 2024-03-12T00:23:45Z |
| format | Article |
| id | doaj.art-0c07d5a94d874811a96dceb4c0f611db |
| institution | Directory Open Access Journal |
| issn | 0954-0091 1360-0494 |
| language | English |
| last_indexed | 2024-03-12T00:23:45Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Connection Science |
| spelling | doaj.art-0c07d5a94d874811a96dceb4c0f611db2023-09-15T10:48:01ZengTaylor & Francis GroupConnection Science0954-00911360-04942022-12-013412265229010.1080/09540091.2022.21150112115011RFID network planning using a new hybrid ANNs-based approachMustapha Maimouni0Badr Abou El Majd1Mohsine Bouya2Mohammed V University in RabatMohammed V University in RabatInternational University of RabatRadio frequency identification (RFID) is a wireless technology that uses radio waves to automatically identify and track objects within a certain range. Due to the benefits of the technology, RFID technology has been adopted as a reliable and efficient solution and is an important technology used in various IoT applications. The deployment of the RFID system has caused an RFID network planning (RNP) problem. However, the RNP problem can be defined as an NP-hard combinatorial optimisation problem that requires the examination of a large number of combinations to obtain the best solution. The goal of this research is to introduce and describe a new hybrid approach to solve the problem of RNP optimisation that is based on artificial intelligence algorithms that require a minimum number of initial parameters. Based on widely used benchmarks, our approach is compared against a hybrid approach based on the genetic algorithm, and the results are efficient, cost-effective and assure a good deployment of the RFID system.http://dx.doi.org/10.1080/09540091.2022.2115011meta-heuristicsredundant antenna eliminationoptimisationartificial neural networksrfid network planning |
| spellingShingle | Mustapha Maimouni Badr Abou El Majd Mohsine Bouya RFID network planning using a new hybrid ANNs-based approach Connection Science meta-heuristics redundant antenna elimination optimisation artificial neural networks rfid network planning |
| title | RFID network planning using a new hybrid ANNs-based approach |
| title_full | RFID network planning using a new hybrid ANNs-based approach |
| title_fullStr | RFID network planning using a new hybrid ANNs-based approach |
| title_full_unstemmed | RFID network planning using a new hybrid ANNs-based approach |
| title_short | RFID network planning using a new hybrid ANNs-based approach |
| title_sort | rfid network planning using a new hybrid anns based approach |
| topic | meta-heuristics redundant antenna elimination optimisation artificial neural networks rfid network planning |
| url | http://dx.doi.org/10.1080/09540091.2022.2115011 |
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