Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A Review
The growing importance and widespread adoption of Wireless Sensor Network (WSN) technologies have helped the enhancement of smart environments in various fields such as manufacturing, smart city, transport, health and the Internet of Things, by providing pervasive real-time applications. In this pap...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9727161/ |
| _version_ | 1818775283874922496 |
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| author | Walid Osamy Ahmed M. Khedr Ahmed Salim Amal Ibrahim Al Ali Ahmed A. El-Sawy |
| author_facet | Walid Osamy Ahmed M. Khedr Ahmed Salim Amal Ibrahim Al Ali Ahmed A. El-Sawy |
| author_sort | Walid Osamy |
| collection | DOAJ |
| description | The growing importance and widespread adoption of Wireless Sensor Network (WSN) technologies have helped the enhancement of smart environments in various fields such as manufacturing, smart city, transport, health and the Internet of Things, by providing pervasive real-time applications. In this paper, we analyze the existing research trends of Coverage, Deployment and Localization challenges in WSN concerning Artificial Intelligence (AI) methods for WSN enhancement. We present a comprehensive discussion on the recent studies that utilized various AI methods to meet specific objectives of WSN, from 2010 to 2021. This would guide the reader towards an understanding of up-to-date applications of AI methods with respect to different WSN challenges. Then, we provide a general evaluation and comparison of different AI methods used in WSNs, which will be a guide for for research community in identifying the most adapted methods and the benefits of using various AI methods for solving the Coverage, Deployment and Localization challenges related to WSNs. Finally, we conclude the paper by stating the open research issues and new directions for future research. |
| first_indexed | 2024-12-18T10:54:35Z |
| format | Article |
| id | doaj.art-6e205b13d27341e690c38d8c0e4eed43 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-18T10:54:35Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-6e205b13d27341e690c38d8c0e4eed432022-12-21T21:10:22ZengIEEEIEEE Access2169-35362022-01-0110302323025710.1109/ACCESS.2022.31567299727161Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A ReviewWalid Osamy0https://orcid.org/0000-0001-6911-4346Ahmed M. Khedr1https://orcid.org/0000-0001-7957-7862Ahmed Salim2Amal Ibrahim Al Ali3Ahmed A. El-Sawy4https://orcid.org/0000-0003-3704-0164Computer Science Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha, EgyptComputer Science Department, University of Sharjah, Sharjah, United Arab EmiratesMathematics Department, College of Sciences, Zagazig University, Zagazig, EgyptInformation Systems Department, University of Sharjah, Sharjah, United Arab EmiratesComputer Science Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha, EgyptThe growing importance and widespread adoption of Wireless Sensor Network (WSN) technologies have helped the enhancement of smart environments in various fields such as manufacturing, smart city, transport, health and the Internet of Things, by providing pervasive real-time applications. In this paper, we analyze the existing research trends of Coverage, Deployment and Localization challenges in WSN concerning Artificial Intelligence (AI) methods for WSN enhancement. We present a comprehensive discussion on the recent studies that utilized various AI methods to meet specific objectives of WSN, from 2010 to 2021. This would guide the reader towards an understanding of up-to-date applications of AI methods with respect to different WSN challenges. Then, we provide a general evaluation and comparison of different AI methods used in WSNs, which will be a guide for for research community in identifying the most adapted methods and the benefits of using various AI methods for solving the Coverage, Deployment and Localization challenges related to WSNs. Finally, we conclude the paper by stating the open research issues and new directions for future research.https://ieeexplore.ieee.org/document/9727161/Artificial intelligencecoveragedeploymentInternet of Thingslocalizationwireless sensor networks |
| spellingShingle | Walid Osamy Ahmed M. Khedr Ahmed Salim Amal Ibrahim Al Ali Ahmed A. El-Sawy Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A Review IEEE Access Artificial intelligence coverage deployment Internet of Things localization wireless sensor networks |
| title | Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A Review |
| title_full | Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A Review |
| title_fullStr | Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A Review |
| title_full_unstemmed | Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A Review |
| title_short | Coverage, Deployment and Localization Challenges in Wireless Sensor Networks Based on Artificial Intelligence Techniques: A Review |
| title_sort | coverage deployment and localization challenges in wireless sensor networks based on artificial intelligence techniques a review |
| topic | Artificial intelligence coverage deployment Internet of Things localization wireless sensor networks |
| url | https://ieeexplore.ieee.org/document/9727161/ |
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