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A six-step\n methodology is employed, encompassing received signal strength indicator (RSSI)-to-image transformation, feature extraction using a pre-trained convolutional neural network (CNN) model, dimensionality reduction, clustering, and classification. By converting RSSI values into images, we capture spatial patterns more effectively. A multi-power level fusion strategy combines RSSI data from three distinct power levels into RGB images, improving localization accuracy and robustness against interference. K-means clustering segments the environment into distinct zones, streamlining classification. Experiments demonstrate the significant contributions of power level fusion, clustering, and classification, with the multi-power level fusion yielding improved performance compared to single power levels. Our approach, based on a custom CNN architecture, offers enhanced precision and efficiency for indoor localization tasks, providing valuable insights into the integration of advanced signal processing and deep learning.<\/jats:p>","DOI":"10.1177\/18761364251370774","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T14:17:41Z","timestamp":1758723461000},"page":"176-192","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring the fusion of multi-power levels in received signal strength indicator-to-image transformation for accurate indoor positioning with deep learning"],"prefix":"10.1177","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6075-335X","authenticated-orcid":false,"given":"Ikbal","family":"Chammakhi Msadaa","sequence":"first","affiliation":[{"name":"LaRINa, ENSTAB, University of Carthage, Borj Cedria, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amen","family":"Debbiche","sequence":"additional","affiliation":[{"name":"LaRINa, ENSTAB, University of Carthage, Borj Cedria, Tunisia"},{"name":"ENSIT, University of Tunis, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0334-0687","authenticated-orcid":false,"given":"Khaled","family":"Grayaa","sequence":"additional","affiliation":[{"name":"LaRINa, ENSTAB, University of Carthage, Borj Cedria, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105509"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/JCN.2020.000018"},{"key":"e_1_3_2_4_1","doi-asserted-by":"publisher","DOI":"10.3233\/AIS-150316"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.3390\/s22239531"},{"key":"e_1_3_2_6_1","unstructured":"Digi International Inc. 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