{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T16:26:41Z","timestamp":1783787201110,"version":"3.55.0"},"reference-count":40,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T00:00:00Z","timestamp":1691366400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Wuhan Institute of Technology, China","award":["CX2022138"],"award-info":[{"award-number":["CX2022138"]}]},{"name":"Wuhan Institute of Technology, China","award":["2022CFB776"],"award-info":[{"award-number":["2022CFB776"]}]},{"name":"Wuhan Institute of Technology, China","award":["2022CFB313"],"award-info":[{"award-number":["2022CFB313"]}]},{"name":"Hubei Provincial Natural Science Foundation, China","award":["CX2022138"],"award-info":[{"award-number":["CX2022138"]}]},{"name":"Hubei Provincial Natural Science Foundation, China","award":["2022CFB776"],"award-info":[{"award-number":["2022CFB776"]}]},{"name":"Hubei Provincial Natural Science Foundation, China","award":["2022CFB313"],"award-info":[{"award-number":["2022CFB313"]}]},{"name":"Natural Science Foundation of Hubei Province of China","award":["CX2022138"],"award-info":[{"award-number":["CX2022138"]}]},{"name":"Natural Science Foundation of Hubei Province of China","award":["2022CFB776"],"award-info":[{"award-number":["2022CFB776"]}]},{"name":"Natural Science Foundation of Hubei Province of China","award":["2022CFB313"],"award-info":[{"award-number":["2022CFB313"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Despite the high demand for Internet location service applications, Wi-Fi indoor localization often suffers from time- and labor-intensive data collection processes. This study proposes a novel indoor localization model that utilizes fingerprinting technology based on a convolutional neural network to address this issue. The aim is to enhance Wi-Fi indoor localization by streamlining the data collection process. The proposed indoor localization model leverages a 3D ray-tracing technique to simulate the wireless received signal strength intensity (RSSI) across the field. By incorporating this advanced technique, the model aims to improve the accuracy and efficiency of Wi-Fi indoor localization. In addition, an RSSI heatmap fingerprint dataset generated from the ray-tracing simulation is trained on the proposed indoor localization model. To optimize and evaluate the model\u2019s performance in real-world scenarios, experiments were conducted using simulated datasets obtained from the publicly available databases of UJIIndoorLoc and Wireless InSite. The results show that the new approach solves the problem of resource limitation while achieving a verification accuracy of up to 99.09%.<\/jats:p>","DOI":"10.3390\/s23156992","type":"journal-article","created":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T06:38:48Z","timestamp":1691390328000},"page":"6992","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Neural-Network-Based Localization Method for Wi-Fi Fingerprint Indoor Localization"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7751-4346","authenticated-orcid":false,"given":"Hui","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Electrical Information, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2705-5610","authenticated-orcid":false,"given":"Li","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Electrical Information, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electrical Information, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haiwen","family":"Yuan","sequence":"additional","affiliation":[{"name":"College of Electrical Information, Wuhan Institute of Technology, Wuhan 430205, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/CC.2013.6488829","article-title":"Situation and development tendency of indoor positioning","volume":"10","author":"Deng","year":"2013","journal-title":"China Commun."},{"key":"ref_2","first-page":"32","article-title":"Indoor positioning and location service based on the integration of navigation and communication","volume":"22","author":"Deng","year":"2016","journal-title":"Commun. 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