RFID-assisted indoor localization and communication for first responders

Guerrieri, Jeffrey R.; Francis, Mathew; Wilson, Perry F.; Kos, Tomislav; Miller, Leonard E.; Bryner, Nelson P.; Stroup, David W; Klein-Berndt, L.

doi:10.1109/eucap.2006.4584714

Cited by 53 publications

(21 citation statements)

References 1 publication

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“…Systems using wifi [1], [2] report a median localization error of more than a meter, and typically involve extensive setup and tuning. Localization error for systems based on GSM [3], IR [4] and RFID [5] also fall in similar range. In order to attain sub-meter accuracy, optical and acoustic based systems have to be used.…”

Section: Related Workmentioning

confidence: 67%

Indoor localization using controlled ambient sounds

Rishabh

Kimber

Adcock

2012

2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

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Abstract-Audio-based receiver localization in indoor environments has multiple applications including indoor navigation, location tagging, and tracking. Public places like shopping malls and consumer stores often have loudspeakers installed to play music for public entertainment. Similarly, office spaces may have sound conditioning speakers installed to soften other environmental noises. We discuss an approach to leverage this infrastructure to perform audio-based localization of devices requesting localization in such environments, by playing barely audible controlled sounds from multiple speakers at known positions. Our approach can be used to localize devices such as smart-phones, tablets and laptops to sub-meter accuracy. The user does not need to carry any specialized hardware. Unlike acoustic approaches which use high-energy ultrasound waves, the use of barely audible (low energy) signals in our approach poses very different challenges. We discuss these challenges, how we addressed those, and experimental results on two prototypical implementations: a request-play-record localizer, and a continuous tracker. We evaluated our approach in a real world meeting room and report promising initial results with localization accuracy within half a meter 94% of the time. The system has been deployed in multiple zones of our office building and is now part of a location service in constant operation in our lab.

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Section: Related Workmentioning

confidence: 67%

Indoor localization using controlled ambient sounds

Rishabh

Kimber

Adcock

2012

2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

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“…Dynamic stride estimation has been explored, but sensors are normally mounted on the foot in order to capture leg swing. Work to compensate for these errors employ the Kalman filter [4,7,11], Weinberg expression [12], or zero-velocity updates (ZUPT) [7,8]. These three techniques minimize inertial drift and can predict actions based on prior event knowledge.…”

Section: Related Workmentioning

confidence: 99%

“…RFID tags are explored [4] as a means for non-GPS localization. RFID tags, statically placed in a building beforehand with precise location knowledge can be used as navigational waypoints.…”

Section: Related Workmentioning

confidence: 99%

An indoor augmented-reality evacuation system for the Smartphone using personalized Pedometry

Ahn¹,

Han²

2012

Hum. Cent. Comput. Inf. Sci.

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There currently exist widely used mobile phone emergency applications for the smartphone and limited mobile emergency applications for indoor environments. However, the outdoor applications only focus primarily on providing accident information to users, and the indoor applications are limited by the unavailability of GPS user-positioning and by WiFi-based access problems. To compensate for these limitations, we propose the RescueMe system, which uses an indoor mobile Augmented Reality application, personalized pedometry, and an optimal exit path algorithm. Together these components comprise a system that can quickly and easily recommend an efficient exit path to mobile phone users in emergency situations. We have developed the mobile-based RescueMe system for use in large-scale buildings that contain complex paths. We show how RescueMe leverages the sensors on a smartphone and utilizes Augmented Reality, cloud information, daily-based user walking patterns, and an adaptive GPS connection method, to deliver critical evacuation information to mobile phone users in indoor emergency situations.

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“…RFID-based localization is another alternative, which relies on initial deployment of some RFID tags over the area. Knowing the location of RFID tags, a mobile device can estimate its location by finding its closest RFID tag(s) [4], [5]. Despite its high accuracy, the high deployment cost is the main drawback of this approach.…”

Section: Introductionmentioning

confidence: 99%

Indoor positioning and distance-aware graph-based semi-supervised learning method

Pourahmadi

Valaee

2012

2012 IEEE Global Communications Conference (GLOBECOM)

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The growing interest for location-based services motivates many researchers to study different localization techniques for indoor environments. The main objective of these studies is to find a balance point between the accuracy of the scheme and its deployment/training cost. RSS-based schemes and in particular Graph-based Semi-Supervised Learning (G-SSL) constitute a group of techniques which has low setup cost and good localization accuracy. In this paper, we analyze the G-SLL scheme and show that, despite its high performance, the G-SSL method (in its original format) is not a very accurate model for a localization problem. Based on this observation and to improve the accuracy of localization, we propose an alternative approach which incorporates our knowledge of wireless signal propagation into the label propagation mechanism. Experimental results are then used to evaluate the performance of the proposed scheme compared to the original G-SSL.

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RFID-assisted indoor localization and communication for first responders

Cited by 53 publications

References 1 publication

Indoor localization using controlled ambient sounds

Indoor localization using controlled ambient sounds

An indoor augmented-reality evacuation system for the Smartphone using personalized Pedometry

Indoor positioning and distance-aware graph-based semi-supervised learning method

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