{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/implementation-of-an-indoor-location-system","title":"Implementation of an Indoor Location System for Mobile-Based Museum Guidance","arxiv_id":null,"date":"2020-04-23","proceeding":"International Conference on Information Management and Big Data (SIMBig) 2020 4","authors":["Dennis Núñez-Fernández"],"abstract":"In this work we proposed an indoor location system that makes use of a mobile phone and WiFi signal levels to determine the location of a person in the museum “Eduardo de Habich” at the Universidad Nacional de Ingeniería, Peru. Therefore, by determining the location, additional information such as recommendations, multimedia, an more could be shown to each user in order to have a better user experience. The main advantage with similar indoor location systems such as Beacons or RFID technology is that the proposed system does not require additional hardware as it only uses pre-installed WiFi hotspots. The experimental tests show promising results, achieving a location accuracy of 93.61%, which is useful for similar navigation tasks.","url_abs":"https://link.springer.com/chapter/10.1007%2F978-3-030-46140-9_7","url_pdf":"https://dennishnf.bitbucket.io/research/2019%20-%20simbig%202019%20-%20implementation%20of%20an%20indoor%20location%20system%20museum.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"implementation-of-an-indoor-location-system","repo_url":"https://github.com/dennishnf/indoor-location-using-naive-bayes","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}