geoXmart - A Marketplace for Geofence-Based Mobile Services

Bareth, Ulrich; Küpper, Axel; Ruppel, Peter

doi:10.1109/compsac.2010.16

Cited by 28 publications

(15 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Geofencing has been discussed from an application point of view for about a decade, where applications range over a broad variety of different domains, see [3,8,10,13,14,15]. Despite this substantial interest, the topic has only recently started to receive attention in database and algorithms research.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Large Scale Indexing of Geofences

Cirillo¹,

Jacobs²,

Martin³

et al. 2014

2014 Fifth International Conference on Computing for Geospatial Research and Application

View full text Add to dashboard Cite

The modern smart phone and car concepts provide a fertile ground for new location-aware applications, ranging from traffic management to social services. While the functionality is partly implemented at the mobile terminal, there is a rising need for efficient backend processing of high-volume, high update rate location streams. It is in this environment that geofencing, the detection of objects traversing virtual fences, is becoming a universal primitive required by an ever-growing number of applications.To satisfy the functionality and performance requirements of large-scale geofencing applications, we present in this work a backend system for indexing massive quantities of mobile objects and geofences. Our system runs on a cluster of servers, achieving a throughput of location updates that scales linearly with number of machines. The key ingredients to achieve a high performance are a specialized spatial index, a dynamic caching mechanism, and a load-sharing principle that reduces communication overhead to a minimum and enables a shared-nothing architecture. The throughput of the spatial index as well as the performance of the overall system are demonstrated by experiments using simulations of large-scale geofencing applications.

show abstract

Section: Introductionmentioning

confidence: 99%

“…This data is used by a multitude of applications including mobile advertisement, fleet management, traffic control, social networks, and security. Many of the use cases require permanent awareness of the set of objects within certain geofence zones; see [3,8,10,13,14,15] for a number of recent application papers.…”

Section: Introductionmentioning

confidence: 99%

Large Scale Indexing of Geofences

Cirillo¹,

Jacobs²,

Martin³

et al. 2014

2014 Fifth International Conference on Computing for Geospatial Research and Application

View full text Add to dashboard Cite

show abstract

“…Proactive LBS form the next generation of LBS, which persistently keep track of the users' locations in an unobtrusive manner and proactively send a notification about potentially useful information in the vicinity according to presubscribed events [2]. These services require particular consideration of battery consumption for achieving continuous location tracking.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Location Semantics for Realizing Cross-Referencing Proactive Location-Based Services

Uzun

Salem

Küpper

2014

2014 IEEE International Conference on Semantic Computing

Self Cite

View full text Add to dashboard Cite

Location-based Services (LBS) are one of the longest-standing value-added services in the mobile communications industry. The location of a user is the fundamental factor shaping such services and is usually computed solely in terms of the physical location relying on Reverse Geocoding APIs. It does not take into consideration the semantics of the location, but rather only the geographic spatial information, which significantly restricts the intelligibility of the provided LBS. In order to overcome the aforementioned limitations, we have introduced a Semantic Positioning Platform in a previous work being capable of providing semantically enriched self-referencing LBS. In this paper, we extend the platform by enabling crossreferencing proactive LBS (i.e., third-party tracking) based on semantically modeled user-specific location profiles (e.g., school or office) in combination with social relations among users. Furthermore, the independent platforms delivering the Semantic Positioning functionality (i.e., the Positioning Enabler and the OpenMobileNetwork) have been integrated into the Context Data Cloud, which is a context management ecosystem for delivering semantically enriched context-aware services. In addition, the Context Data Cloud for Android application including a Friend Tracker function has been implemented as a proof of concept. The evaluation in terms of battery consumption and positioning accuracy highlights the added value of our approach.

show abstract

“…Bareth, Kupper, and Ruppel conducted a study in 2010 that proposed a new concept to distribute applications with geofence services [9]. It created a marketplace to acquire or subscribe applications.…”

Section: Literature Reviewmentioning

confidence: 99%

Designing Module E-Complaint System Based on Geotagging and Geofencing

Basid

Tolle

Ramdani

2017

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

Abstract-The government initiative in the implementation of smart city concept is an effort in the management of a city. In the governance of a town, public service is one of the most important aspects. Improving public services requires public role because the society is the direct users of public services. One role of the community in improving public service is to provide information or complaint to the government. However, the media where the public reports such information has yet been optimum. Therefore, the researcher assumed that the public needs certain media as well as some support system where they can make complaints related to public service. The support system is in the form of e-complaint system installed on smartphones equipped with geotagging techniques to determine exactly where the complaint is made (location) and geofencing method to determine which territory the complaint belongs to. In this study, the researcher explained the process of designing module for geotagging and geofencing-based e-complaint system. Several experiments were conducted to find out the accuracy of these techniques. With 94% accuracy, geofencing was a suitable technique to apply. In addition, geotagging techniques using EXIF of a digital image was considered the most suitable technique for the e-complaint system rather than other geotagging techniques.

show abstract

geoXmart - A Marketplace for Geofence-Based Mobile Services

Cited by 28 publications

References 12 publications

Large Scale Indexing of Geofences

Large Scale Indexing of Geofences

Exploiting Location Semantics for Realizing Cross-Referencing Proactive Location-Based Services

Designing Module E-Complaint System Based on Geotagging and Geofencing

Contact Info

Product

Resources

About