Experimental Comparison of Bluetooth and WiFi Signal Propagation for Indoor Localisation

Dimitrova, Desislava; Alyafawi, Islam; Braun, Torsten

doi:10.1007/978-3-642-30630-3_11

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…According to [9], we expect the amount of RSS loss to be related with the type and number of obstructions, e.g., concrete walls have higher loss than wooden doors.…”

Section: Indoor Environment Impactmentioning

confidence: 99%

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SDR-based passive indoor localization system for GSM

Alyafawi

Dimitrova

Braun

2014

Proceedings of the 2014 ACM Workshop on Software Radio Implementation Forum

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This study deals with indoor positioning using GSM radio, which has the distinct advantage of wide coverage over other wireless technologies. In particular, we focus on passive localization systems that are able to achieve high localization accuracy without any prior knowledge of the indoor environment or the tracking device radio settings. In order to overcome these challenges, newly proposed localization algorithms based on the exploitation of the received signal strength (RSS) are proposed. We explore the effects of non-line-of-sight communication links, opening and closing of doors, and human mobility on RSS measurements and localization accuracy. We have implemented the proposed algorithms on top of software defined radio systems and carried out detailed empirical indoor experiments. The performance results show that the proposed solutions are accurate with average localization errors between 2.4 and 3.2 meters.

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“…According to [9], we expect the amount of RSS loss to be related with the type and number of obstructions, e.g., concrete walls have higher loss than wooden doors.…”

Section: Indoor Environment Impactmentioning

confidence: 99%

“…Second, Ptx and the Tx antenna gain for a specific MD are difficult to know, unless provided by the MD. Third, Prx depends on the MD's hardware specifications and antenna orientation [9].…”

Section: Range-based Positioningmentioning

confidence: 99%

SDR-based passive indoor localization system for GSM

Alyafawi

Dimitrova

Braun

2014

Proceedings of the 2014 ACM Workshop on Software Radio Implementation Forum

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“…Like all RF signals, the Bluetooth signal is susceptible to multipath propagation and fading [27]. Therefore, it is necessary to filter the RSSI data before it can be used to obtain an adequate estimate of the proximity between the person and the beacons.…”

Section: Rssi Filtermentioning

confidence: 99%

Framework for Simultaneous Indoor Localization, Mapping, and Human Activity Recognition in Ambient Assisted Living Scenarios

Ceron

López

Kluge

et al. 2022

Sensors

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Indoor localization and human activity recognition are two important sources of information to provide context-based assistance. This information is relevant in ambient assisted living (AAL) scenarios, where older adults usually need supervision and assistance in their daily activities. However, indoor localization and human activity recognition have been mostly considered isolated problems. This work presents and evaluates a framework that takes advantage of the relationship between location and activity to simultaneously perform indoor localization, mapping, and human activity recognition. The proposed framework provides a non-intrusive configuration, which fuses data from an inertial measurement unit (IMU) placed in the person’s shoe, with proximity and human activity-related data from Bluetooth low energy beacons (BLE) deployed in the indoor environment. A variant of the simultaneous location and mapping (SLAM) framework was used to fuse the location and human activity recognition (HAR) data. HAR was performed using data streaming algorithms. The framework was evaluated in a pilot study, using data from 22 people, 11 young people, and 11 older adults (people aged 65 years or older). As a result, seven activities of daily living were recognized with an F1 score of 88%, and the in-door location error was 0.98 ± 0.36 m for the young and 1.02 ± 0.24 m for the older adults. Furthermore, there were no significant differences between the groups, indicating that our proposed method works adequately in broad age ranges.

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“…For location prediction in interior context, distance-based [4] [5] or angle-based [6] [7] techniques were applied in the past. Multipath propagation of WiFi or Bluetooth signal due to varied impediments is a significant issue with these systems [8]. A far more recent technique is fingerprinting, which uses a collection of vectors made up of signal strength measurements from different fixed sources taken at a certain location to uniquely identify that particular location.…”

Section: Introductionmentioning

confidence: 99%