A statistical indoor localization method for supporting location-based access control

Gao, Chunwang

doi:10.31274/etd-180810-2531

Cited by 4 publications

(6 citation statements)

References 10 publications

(10 reference statements)

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“…For example, time-of-arrival (ToA) [3], [6], [31], [32], [33] and direction-of-arrival (DoA) [34], [7], [35], [36] methods require a strong enough line-of-sight (LOS) signal component between the access point (AP) and the user, which is often not the case in indoor environments that contain a lot of obstacles and partitions. Fingerprint schemes [4], [5], [8], [37], [38], [39], [40], [41] don't require LOS, but require measurements from many different APs to get accurate results. Since the main reason of having a WLAN is for data transmission, there is no incentive to cover locations with multiple APs.…”

Section: Espite Its Huge Market Potential Indoor Localizationmentioning

confidence: 99%

“…Motivated by this, the third major indoor positioning scheme called "fingerprinting", see, for example, [4], [5], [8], [37], [38], [39], [40], [56] has attracted a lot of attention. Fingerprint-based localization systems involve two phases: during the offline phase vectors of received signal strength indicator (RSSI) from APs are collected at many reference points whose locations are known, and, during the online phase, RSSI vectors from a user in an unknown location are compared with the RSSI vectors of the known locations to estimate the most likely user location.…”

Section: Prior Workmentioning

confidence: 99%

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Efficient Indoor Localization via Switched-Beam Antennas

Zhang

Psounis

2020

IEEE Trans. on Mobile Comput.

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Location-based services have become extremely popular. As a result, indoor localization has received a lot of attention from both industry and academia. Despite the plethora of existing approaches, no method can achieve high accuracy without major, expensive changes to existing systems. For example, to achieve good accuracy, fingerprinting methods require many APs within range of a client, time-of-arrival methods require tight synchronization, client hardware changes and line-of-sight, and direction-of-arrival methods require expensive antenna front ends and line-of-sight. In this paper we take advantage of inexpensive, off-the-shelf switched-beam antennas (SBAs) to increase the diversity of measurements used for fingerprint-based localization. We show using experiments that a single AP equipped with n SBAs may infer equally rich localization information as n APs equipped with n omnidirectional antennas each, as long as the SBAs are properly configured. We then establish via extensive experiments that a single packet reception from a commodity client at a single AP equipped with a handful of SBAs (e.g. 8 SBAs costing a couple of dollars more than omni antennas) achieves localization accuracy in the order of half a meter with or without line-of-sight, in any indoor environment, with zero airtime overhead and zero client support. !

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Section: Espite Its Huge Market Potential Indoor Localizationmentioning

confidence: 99%

Section: Prior Workmentioning

confidence: 99%

Efficient Indoor Localization via Switched-Beam Antennas

Zhang

Psounis

2020

IEEE Trans. on Mobile Comput.

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“…In this analysis it is assumed that an exhibition, like CES 1 , has already been organized and an application for the specific event was developed for every mobile operating system. In addition to usual exhibition applications that typically provide a map, an exhibitors list, scheduled events, and other common features, this app provides new proximity services that can be divided into 3 different categories, detailed below.…”

Section: Scenariomentioning

confidence: 99%

“…Location Based Services (LBS) are usually defined as a general class of software services that use location information to provide and control different useful features. They are currently used in many different contexts providing always new and useful facilities: Gao et al [1], for instance, show how much accuracy is achievable through the use of LBS for location-based access control; Aloudat et al [2], instead, discuss about the possibility of using LBS for sophisticated location-based emergency services in Australia.…”

Section: Introductionmentioning

confidence: 99%

IoT Meets Exhibition Areas: A Modular Architecture to Improve Proximity Interactions

Corno

Russis

Montanaro

et al. 2015

2015 3rd International Conference on Future Internet of Things and Cloud

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The concept of proximity has been recently adopted in various fields of interest, with different meanings and implementations. In the Information Technology area, for example, proximity was used for analyzing user location and nearness to objects/people, and has already changed the way people interact with each other and with technology itself. In this field, the concept is becoming more important with the diffusion of IoT, the network of "things" connected to each other to share services and features. This paper aims at analyzing how the IoT can improve proximity interactions by developing a case study in an exhibition area (tradeshow), with the goal of enhancing participants' and exhibitors' experience. Starting from the analysis of existing works, we designed a scenario to identify IoT-enabled application features for both participants and exhibitors. We propose a modular architecture able to provide different services to all stakeholders: it offers a baseline for exhibitors who want to provide new interactive services to participants (e.g., to control some exhibited device) and some social services to participants for interacting among themselves and with exhibitors. Finally, we validate our architecture implementing the initial scenario on top of the AllJoyn TM framework, an emerging proximity based software framework.

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“…The offline phase of the statistical indoor localization method, described in , is based on a local regression fitting method to build a large RSSI database (called radio map) containing the distribution of the signal strength received at each known location. Local regression divides the independent statistical RSSI variable in small intervals and performs a regression on these binned data intervals.…”

Section: Related Workmentioning

confidence: 99%

Pseudo‐3D RSSI‐based WSN localization algorithm using linear regression

Vanheel

Verhaevert

Laermans

et al. 2013

Wireless Communications

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Receiver Strength Signal Indication based Wireless Sensor Networks offer a cheap solution for location-aware applications. For a final breakthrough these systems need fast deployment and easy auto-configuration. In this study, we use the real-life iMinds test bed to expand a two-dimensional localization algorithm to the pseudo third dimension with very low additional computational time. Our experiments show that this fast three-dimensional algorithm has no outliers and avoids manual calibration. Our algorithm has lower position errors than a maximum likelihood algorithm with a mean square error cost function. Furthermore, with non-parametric statistical tests, we show that our previously designed twodimensional preprocessing performs equally well in pseudo-three dimensions: the preprocessing reduces the position error in a statistically significant way.

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A statistical indoor localization method for supporting location-based access control

Cited by 4 publications

References 10 publications

Efficient Indoor Localization via Switched-Beam Antennas

Efficient Indoor Localization via Switched-Beam Antennas

IoT Meets Exhibition Areas: A Modular Architecture to Improve Proximity Interactions

Pseudo‐3D RSSI‐based WSN localization algorithm using linear regression

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