Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/180340
Title: iBILL: Using iBeacon and Inertial Sensors for Accurate Indoor Localization in Large Open Areas
Authors: Xudong Wu;Ruofei Shen;Luoyi Fu;Xiaohua Tian;Peng Liu;Xinbing Wang
Year: 2017
Publisher: IEEE
Abstract: As a key technology that is widely adopted in location-based services (LBS), indoor localization has received considerable attention in both research and industrial areas. Despite the huge efforts made for localization using smartphone inertial sensors, its performance is still unsatisfactory in large open areas, such as halls, supermarkets, and museums, due to accumulated errors arising from the uncertainty of users&x2019; mobility and fluctuations of magnetic field. Regarding that, this paper presents iBILL, an indoor localization approach that jointly uses iBeacon and inertial sensors in large open areas. With users&x2019; real-time locations estimated by inertial sensors through an improved particle filter, we revise the algorithm of augmented particle filter to cope with fluctuations of magnetic field. When users enter vicinity of iBeacon devices clusters, their locations are accurately determined based on received signal strength of iBeacon devices, and accumulated errors can, therefore, be corrected. Proposed by Apple Inc. for developing LBS market, iBeacon is a type of Bluetooth low energy, and we characterize both the advantages and limitations of localization when it is utilized. Moreover, with the help of iBeacon devices, we also provide solutions of two localization problems that have long remained tough due to the increasingly large computational overhead and arbitrarily placed smartphones. Through extensive experiments in the library on our campus, we demonstrate that iBILL exhibits 90&x0025; errors within 3.5 m in large open areas.
Description: 
URI: http://localhost/handle/Hannan/180340
volume: 5
More Information: 14589,
14599
Appears in Collections:2017

Files in This Item:
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7982961.pdf16.51 MBAdobe PDF
Title: iBILL: Using iBeacon and Inertial Sensors for Accurate Indoor Localization in Large Open Areas
Authors: Xudong Wu;Ruofei Shen;Luoyi Fu;Xiaohua Tian;Peng Liu;Xinbing Wang
Year: 2017
Publisher: IEEE
Abstract: As a key technology that is widely adopted in location-based services (LBS), indoor localization has received considerable attention in both research and industrial areas. Despite the huge efforts made for localization using smartphone inertial sensors, its performance is still unsatisfactory in large open areas, such as halls, supermarkets, and museums, due to accumulated errors arising from the uncertainty of users&x2019; mobility and fluctuations of magnetic field. Regarding that, this paper presents iBILL, an indoor localization approach that jointly uses iBeacon and inertial sensors in large open areas. With users&x2019; real-time locations estimated by inertial sensors through an improved particle filter, we revise the algorithm of augmented particle filter to cope with fluctuations of magnetic field. When users enter vicinity of iBeacon devices clusters, their locations are accurately determined based on received signal strength of iBeacon devices, and accumulated errors can, therefore, be corrected. Proposed by Apple Inc. for developing LBS market, iBeacon is a type of Bluetooth low energy, and we characterize both the advantages and limitations of localization when it is utilized. Moreover, with the help of iBeacon devices, we also provide solutions of two localization problems that have long remained tough due to the increasingly large computational overhead and arbitrarily placed smartphones. Through extensive experiments in the library on our campus, we demonstrate that iBILL exhibits 90&x0025; errors within 3.5 m in large open areas.
Description: 
URI: http://localhost/handle/Hannan/180340
volume: 5
More Information: 14589,
14599
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7982961.pdf16.51 MBAdobe PDF
Title: iBILL: Using iBeacon and Inertial Sensors for Accurate Indoor Localization in Large Open Areas
Authors: Xudong Wu;Ruofei Shen;Luoyi Fu;Xiaohua Tian;Peng Liu;Xinbing Wang
Year: 2017
Publisher: IEEE
Abstract: As a key technology that is widely adopted in location-based services (LBS), indoor localization has received considerable attention in both research and industrial areas. Despite the huge efforts made for localization using smartphone inertial sensors, its performance is still unsatisfactory in large open areas, such as halls, supermarkets, and museums, due to accumulated errors arising from the uncertainty of users&x2019; mobility and fluctuations of magnetic field. Regarding that, this paper presents iBILL, an indoor localization approach that jointly uses iBeacon and inertial sensors in large open areas. With users&x2019; real-time locations estimated by inertial sensors through an improved particle filter, we revise the algorithm of augmented particle filter to cope with fluctuations of magnetic field. When users enter vicinity of iBeacon devices clusters, their locations are accurately determined based on received signal strength of iBeacon devices, and accumulated errors can, therefore, be corrected. Proposed by Apple Inc. for developing LBS market, iBeacon is a type of Bluetooth low energy, and we characterize both the advantages and limitations of localization when it is utilized. Moreover, with the help of iBeacon devices, we also provide solutions of two localization problems that have long remained tough due to the increasingly large computational overhead and arbitrarily placed smartphones. Through extensive experiments in the library on our campus, we demonstrate that iBILL exhibits 90&x0025; errors within 3.5 m in large open areas.
Description: 
URI: http://localhost/handle/Hannan/180340
volume: 5
More Information: 14589,
14599
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7982961.pdf16.51 MBAdobe PDF