{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T16:06:39Z","timestamp":1770221199515,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,3,28]],"date-time":"2017-03-28T00:00:00Z","timestamp":1490659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["NO.61401040"],"award-info":[{"award-number":["NO.61401040"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Key Research and Development Program","award":["No.2016YFB0502002"],"award-info":[{"award-number":["No.2016YFB0502002"]}]},{"name":"the National High Technology Research and Development Program of China","award":["NO.2015AA124103"],"award-info":[{"award-number":["NO.2015AA124103"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Considering the installation cost and coverage, the received signal strength indicator (RSSI)-based indoor positioning system is widely used across the world. However, the indoor positioning performance, due to the interference of wireless signals that are caused by the complex indoor environment that includes a crowded population, cannot achieve the demands of indoor location-based services. In this paper, we focus on increasing the signal strength estimation accuracy considering the population density, which is different to the other RSSI-based indoor positioning methods. Therefore, we propose a new wireless signal compensation model considering the population density, distance, and frequency. First of all, the number of individuals in an indoor crowded scenario can be calculated by our convolutional neural network (CNN)-based human detection approach. Then, the relationship between the population density and the signal attenuation is described in our model. Finally, we use the trilateral positioning principle to realize the pedestrian location. According to the simulation and tests in the crowded scenarios, the proposed model increases the accuracy of the signal strength estimation by 1.53 times compared to that without considering the human body. Therefore, the localization accuracy is less than 1.37 m, which indicates that our algorithm can improve the indoor positioning performance and is superior to other RSSI models.<\/jats:p>","DOI":"10.3390\/s17040704","type":"journal-article","created":{"date-parts":[[2017,3,28]],"date-time":"2017-03-28T10:24:33Z","timestamp":1490696673000},"page":"704","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["A Smartphone Camera-Based Indoor Positioning Algorithm of Crowded Scenarios with the Assistance of Deep CNN"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1200-5525","authenticated-orcid":false,"given":"Jichao","family":"Jiao","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing 100088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing 100088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongliang","family":"Deng","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing 100088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjing","family":"Ma","sequence":"additional","affiliation":[{"name":"China Academy of Information and Communication Technology (CAICT), Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TSMCC.2007.905750","article-title":"Survey of Wireless Indoor Positioning Techniques and Systems","volume":"37","author":"Liu","year":"2007","journal-title":"IEEE Trans. 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