| Issue |
EPJ Web Conf.
Volume 380, 2026
International Conference on Information Systems and Communication Technologies (ICISCT’25)
|
|
|---|---|---|
| Article Number | 01023 | |
| Number of page(s) | 9 | |
| Section | Microwave Components and 5G/6G Communication Systems | |
| DOI | https://doi.org/10.1051/epjconf/202638001023 | |
| Published online | 03 August 2026 | |
https://doi.org/10.1051/epjconf/202638001023
Enhancing Indoor RFID Localization Using Artificial Intelligence Algorithms: A Support Vector Machine (SVM)-Based Approach
1 Institut National des postes et télécommunication, Rabat, Morocco
2 Centre Régional des Métiers de l’Education et de la Formation, Casablanca, Morocco
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 3 August 2026
Abstract
Localization of objects inside has been a great issue within domains like logistics, health care, and security. In this paper, we discuss AI approaches for indoor RFID localization, specifically concentrating on the application of Support Vector Machine (SVM) approach in order to calculate the coordinates X and Y for the RFID tag. The conducted research shows that applying SVM helps achieve an average accuracy of 85%, which is 25% better than the classical methods. Also, increasing the number of training dataset from 50 to 500 helped us reduce the prediction error. In spite of all difficulties that arise from environmental interference, the conducted research proves that AI approaches can help overcome the limitations of classical approaches.
© The Authors, published by EDP Sciences, 2026
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