The PoSIM middleware for translucent and context-aware integrated management of heterogeneous positioning systems

Bellavista, Paolo; Corradi, Antonio; Giannelli, Carlo

doi:10.1016/j.comcom.2008.01.024

Cited by 7 publications

(10 citation statements)

References 19 publications

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“…Furthermore, it would mean that this information is propagated up to highler levels always, even though most middleware uses does not need it. In PoSIM [7] a HDOP info may be specified and a wrapper for the GPS that extracts the information and make it available for higher levels may be written. However, when questioned it will always return the latest HDOP value, which may correspond to a new position.…”

Section: Integrating a Particle Filter Using Channel Featurementioning

confidence: 99%

“…Implementation of the extension of the position format requires access to the code for the middleware. In PoSIM [7] an info could be specified and implemented in the Sensor Wrapper in order to obtain the number of satellites. However, PoSIM does not focus on filtering and it is unclear how a policy that tested the number of satellites would be used to delete an already obtained position from the system.…”

Section: Detecting Unreliable Readings By Adding Component Featurementioning

confidence: 99%

“…The first requirement of adding a new kind of positioning mechanism and using this in the middleware, without changing the interface has been fulfilled by existing positioning middleware: MiddleWhere [5], the Location Stack [6], and PoSIM [7]. Although some architectural issues remain, e.g., in the Location Stack the particle filter may be plugged in as a new kind of sensor.…”

Section: Introductionmentioning

confidence: 99%

“…MiddleWhere [5] and PoSIM [7] do support that new functionality is specified and implemented in sensor wrappers but not that new features are attached to the position information at a higher level or a later stage in the processing. In order to do this, the process that lies behind the construction of a high-level position must be exposed by the middleware as provided by the PerPos middleware.…”

Section: Introductionmentioning

confidence: 99%

“…This means that they do not support accessing information that is not part of the interface or the process behind. PoSIM [7] allows the user to specify control mechanisms and information that the positioning technologies must or may expose. This enables access to low-level information, however, it does not provide the application developer with access to the positioning process.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

PerPos: A Translucent Positioning Middleware Supporting Adaptation of Internal Positioning Processes

Jensen¹,

Schougaard²,

Kjærgaard

et al. 2010

Middleware 2010

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Abstract.A positioning middleware benefits the development of location aware applications. Traditionally, positioning middleware provides position transparency in the sense that it hides low-level details. However, many applications require access to specific details of the usually hidden positioning process. To address this problem this paper proposes a positioning middleware named PerPos that is translucent and adaptable, i.e., it supports both high-and low-level interaction. The PerPos middleware provides translucency with respect to the positioning process and allows programmatic definition of application specific features that can be applied to the internal position processing of the middleware. To evaluate these capabilities we extend the internal position processing of the middleware with functionality supporting probabilistic position tracking and strategies for minimization of the energy consumption. The result of the evaluation is that using only the proposed capabilities we can, in a structured manner, extend the internal positioning processing.

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Section: Integrating a Particle Filter Using Channel Featurementioning

confidence: 99%

Section: Detecting Unreliable Readings By Adding Component Featurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

PerPos: A Translucent Positioning Middleware Supporting Adaptation of Internal Positioning Processes

Jensen¹,

Schougaard²,

Kjærgaard

et al. 2010

Middleware 2010

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Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling

Schougaard

Grønbæk

Scharling

2012

Lecture Notes in Computer Science

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Abstract. This paper introduces methods and services called PerPosNav for development of custom indoor pedestrian navigation applications to be deployed on a variety of platforms. PerPosNav is built on top of the PerPos positioning middleware [8] that fusions GPS, WiFi and inertial tracking into indoor positioning with high accuracy in many types of buildings. The challenges of indoor navigation are discussed and the PerPosNav services are introduced. PerPosNav combines symbolic and geometry based modeling of buildings, and in turn combines graph-based and geometric route computation. The paper argues why these hybrid approaches are necessary to handle the challenges of indoor pedestrian navigation. Furthermore, a fluent navigation is maintained via route tracking and navigation services that generate instructions based on how the user moves in relation to the prescribed route. The viability of PerPosNav has been proven by implementation of support for multiple modes of pedestrian indoor navigation: 1) augmented signs, 2) map based navigation on smartphones, 3) auditory navigation on smartphones solely via earbuds, and 4) augmented reality navigation. Experiences from the use of the PerPosNav services are discussed and compared to other indoor pedestrian navigation approaches.

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Using multi-objective metaheuristics for the optimal selection of positioning systems

Ficco¹,

Pietrantuono

Russo

2015

Soft Comput

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The interworking between cellular and wireless local area networks, as well as the spreading of mobile devices equipped with several positioning technologies pave the ground to new and more favorable indoor/outdoor location-based services (LBSs). Thus, wireless internet service providers are required to take several positioning methods into account at the same time, to leverage the different features of existing technologies. This would allow providing LBSs satisfying the user-required quality of position in terms of accuracy, privacy, power consumption, and often, conflicting features. Therefore, this paper presents GlobalPreLoc, a multi-objective strategy for the dynamic and optimal selection of positioning technologies. The strategy exploits a pattern-mining algorithm for future position prediction combined with conventional multi-objective evolutionary algorithms, for choosing continuously the best location providers, accounting for the user requirements, the terminal capabilities, and the surrounding positioning infrastructures. To practically implement the strategy, we also designed an architecture based on secure user plane location specification to provide indoor and outdoor LBSs in interworking wireless networks exploiting GlobalPreLoc features

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The PoSIM middleware for translucent and context-aware integrated management of heterogeneous positioning systems

Abstract: The

Cited by 7 publications

References 19 publications

PerPos: A Translucent Positioning Middleware Supporting Adaptation of Internal Positioning Processes

PerPos: A Translucent Positioning Middleware Supporting Adaptation of Internal Positioning Processes

Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling

Using multi-objective metaheuristics for the optimal selection of positioning systems

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