Pedestrian Navigation in Difficult Environments: Results of the ESA Project SHADE

Ott, Björn; Wasle, Elmar; Weimann, Franz; Branco, Pedro; Nicole, Riccardo

doi:10.1007/3-540-27468-5_77

Cited by 3 publications

(1 citation statement)

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“…It is difficult to determine specific thresholds for required positioning performance. However, considering reported results in (Ott et al, 2005;Alnabhan et al, 2010), it is possible to define approximate performance levels thresholds, see Table 3. Three factors are used to identify the performance levels, known as accuracy, availability, and PRR.…”

Section: Position Performance Monitoringmentioning

confidence: 99%

Location-Aware Mobile Learning Model: A Case for Positioning Performance Measurements

Alnabhan¹,

Matar²,

Hussain³

et al. 2014

CIS

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This research work explores the use of mobile and positioning technologies stimulating a context adaptive and location-based learning model. The proposed model utilizes a set of context factors for learning service dissemination; described as learning service area, learning service type, and service interaction level. In addition, the new model considers the availability of positioning technology for authoring location-based learning content, and for accurately disseminating learning services. Hence, tolerance to position errors is used to classify learning services into two types; generic and specific. An evaluation experiment was conducted measuring the relationship between the positioning performance and successful implementation of the m-learning model. Results have shown a significant affect of position accuracy towards learners' context understanding and interaction with learning activity.

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Section: Position Performance Monitoringmentioning

confidence: 99%