Indoor Localization System Based on Bluetooth Low Energy for Museum Applications
In the last few years, indoor localization has attracted researchers and commercial developers. Indeed, the availability of systems, techniques and algorithms for localization allows the improvement of existing communication applications and services by adding position information. Some examples can...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-06-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/9/6/1055 |
| _version_ | 1797564083361284096 |
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| author | Romeo Giuliano Gian Carlo Cardarilli Carlo Cesarini Luca Di Nunzio Francesca Fallucchi Rocco Fazzolari Franco Mazzenga Marco Re Alessandro Vizzarri |
| author_facet | Romeo Giuliano Gian Carlo Cardarilli Carlo Cesarini Luca Di Nunzio Francesca Fallucchi Rocco Fazzolari Franco Mazzenga Marco Re Alessandro Vizzarri |
| author_sort | Romeo Giuliano |
| collection | DOAJ |
| description | In the last few years, indoor localization has attracted researchers and commercial developers. Indeed, the availability of systems, techniques and algorithms for localization allows the improvement of existing communication applications and services by adding position information. Some examples can be found in the managing of people and/or robots for internal logistics in very large warehouses (e.g., Amazon warehouses, etc.). In this paper, we study and develop a system allowing the accurate indoor localization of people visiting a museum or any other cultural institution. We assume visitors are equipped with a Bluetooth Low Energy (BLE) device (commonly found in modern smartphones or in a small chipset), periodically transmitting packets, which are received by geolocalized BLE receivers inside the museum area. Collected packets are provided to the locator server to estimate the positions of the visitors inside the museum. The position estimation is based on a feed-forward neural network trained by a measurement campaign in the considered environment and on a non-linear least square algorithm. We also provide a strategy for deploying the BLE receivers in a given area. The performance results obtained from measurements show an achievable position estimate accuracy below 1 m. |
| first_indexed | 2024-03-10T18:52:24Z |
| format | Article |
| id | doaj.art-7a52e378ebf1462fadf61d0ecf18a5ea |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T18:52:24Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-7a52e378ebf1462fadf61d0ecf18a5ea2023-11-20T05:03:56ZengMDPI AGElectronics2079-92922020-06-0196105510.3390/electronics9061055Indoor Localization System Based on Bluetooth Low Energy for Museum ApplicationsRomeo Giuliano0Gian Carlo Cardarilli1Carlo Cesarini2Luca Di Nunzio3Francesca Fallucchi4Rocco Fazzolari5Franco Mazzenga6Marco Re7Alessandro Vizzarri8Department of Innovation & Information Engineering, Guglielmo Marconi University, via Plinio 44, 00193 Rome, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133 Rome, ItalyDepartment of Innovation & Information Engineering, Guglielmo Marconi University, via Plinio 44, 00193 Rome, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133 Rome, ItalyDepartment of Innovation & Information Engineering, Guglielmo Marconi University, via Plinio 44, 00193 Rome, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133 Rome, ItalyDepartment of Enterprise Engineering “Mario Lucertini”, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133 Rome, ItalyDepartment of Electronics Engineering, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133 Rome, ItalyDepartment of Enterprise Engineering “Mario Lucertini”, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133 Rome, ItalyIn the last few years, indoor localization has attracted researchers and commercial developers. Indeed, the availability of systems, techniques and algorithms for localization allows the improvement of existing communication applications and services by adding position information. Some examples can be found in the managing of people and/or robots for internal logistics in very large warehouses (e.g., Amazon warehouses, etc.). In this paper, we study and develop a system allowing the accurate indoor localization of people visiting a museum or any other cultural institution. We assume visitors are equipped with a Bluetooth Low Energy (BLE) device (commonly found in modern smartphones or in a small chipset), periodically transmitting packets, which are received by geolocalized BLE receivers inside the museum area. Collected packets are provided to the locator server to estimate the positions of the visitors inside the museum. The position estimation is based on a feed-forward neural network trained by a measurement campaign in the considered environment and on a non-linear least square algorithm. We also provide a strategy for deploying the BLE receivers in a given area. The performance results obtained from measurements show an achievable position estimate accuracy below 1 m.https://www.mdpi.com/2079-9292/9/6/1055bluetooth low energyindoor localization systemreceived signal strength indicatorneural network |
| spellingShingle | Romeo Giuliano Gian Carlo Cardarilli Carlo Cesarini Luca Di Nunzio Francesca Fallucchi Rocco Fazzolari Franco Mazzenga Marco Re Alessandro Vizzarri Indoor Localization System Based on Bluetooth Low Energy for Museum Applications Electronics bluetooth low energy indoor localization system received signal strength indicator neural network |
| title | Indoor Localization System Based on Bluetooth Low Energy for Museum Applications |
| title_full | Indoor Localization System Based on Bluetooth Low Energy for Museum Applications |
| title_fullStr | Indoor Localization System Based on Bluetooth Low Energy for Museum Applications |
| title_full_unstemmed | Indoor Localization System Based on Bluetooth Low Energy for Museum Applications |
| title_short | Indoor Localization System Based on Bluetooth Low Energy for Museum Applications |
| title_sort | indoor localization system based on bluetooth low energy for museum applications |
| topic | bluetooth low energy indoor localization system received signal strength indicator neural network |
| url | https://www.mdpi.com/2079-9292/9/6/1055 |
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