GammaSense: Infrastructureless Positioning Using Background Radioactivity

Bucur, Doina; Kjærgaard, Mikkel Baun

doi:10.1007/978-3-540-88793-5_6

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…Although the monetary cost of the sensor modules is relatively low, this system incurs a relatively high computational cost during the scene analysis. Another system, known as Gammasense, is based on harvesting background radioactivity for localization using a radioactivity sensor [7]. Gamma levels are measured and stored in a database; a user's position is then estimated by comparing the measured radioactivity level to the stored fingerprinted values.…”

Section: Summary Of Prior Workmentioning

confidence: 99%

Inertial-vision sensor fusion for pedestrian localization

Chdid

Oueis

Khoury

et al. 2011

2011 IEEE International Conference on Robotics and Biomimetics

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The localization of an ambulatory individual, a.k.a. a pedestrian, is a quickly-developing domain with the potential to permeate into a variety of applications, as knowledge of an individual's location within an environment becomes ever-more useful. In order to automate the localization task, positioning modules are prime candidates for inclusion in a system. Such modules are expected to reduce both the effort and time incurred during the localization process while improving the accuracy and organization of the exchanged data. Building on and combining recent developments in the fields of step detection using inertial measurement units and structure from motion using a camera rig, the work presented in this paper is an implementation of a pedestrian localization system targeted specifically at infrastructure-less indoor localization. The inertial measurement unit and camera rigs are respectively attached to the mobile user's foot and waist, and the collected data is processed by the localization module to obtain a current position. The focus of this paper is the implementation and preliminary testing of this localization module's components.

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Section: Summary Of Prior Workmentioning

confidence: 99%

Inertial-vision sensor fusion for pedestrian localization

Chdid

Oueis

Khoury

et al. 2011

2011 IEEE International Conference on Robotics and Biomimetics

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ZiFind: Exploiting cross-technology interference signatures for energy-efficient indoor localization

Gao

Niu

Zhou

et al. 2013

2013 Proceedings IEEE INFOCOM

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LocateMe

Subbu

Gozick

Dantu

2013

ACM Trans. Intell. Syst. Technol.

168

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Fine-grained localization is extremely important to accurately locate a user indoors. Although innovative solutions have already been proposed, there is no solution that is universally accepted, easily implemented, user centric, and, most importantly, works in the absence of GSM coverage or WiFi availability. The advent of sensor rich smartphones has paved a way to develop a solution that can cater to these requirements. By employing a smartphone's built-in magnetic field sensor, magnetic signatures were collected inside buildings. These signatures displayed a uniqueness in their patterns due to the presence of different kinds of pillars, doors, elevators, etc., that consist of ferromagnetic materials like steel or iron. We theoretically analyze the cause of this uniqueness and then present an indoor localization solution by classifying signatures based on their patterns. However, to account for user walking speed variations so as to provide an application usable to a variety of users, we follow a dynamic time-warping-based approach that is known to work on similar signals irrespective of their variations in the time axis. Our approach resulted in localization distances of approximately 2m--6m with accuracies between 80--100% implying that it is sufficient to walk short distances across hallways to be located by the smartphone. The implementation of the application on different smartphones yielded response times of less than five secs, thereby validating the feasibility of our approach and making it a viable solution.

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GammaSense: Infrastructureless Positioning Using Background Radioactivity

Cited by 3 publications

References 9 publications

Inertial-vision sensor fusion for pedestrian localization

Inertial-vision sensor fusion for pedestrian localization

ZiFind: Exploiting cross-technology interference signatures for energy-efficient indoor localization

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