geofence.pdf - 2016 IEEE International Conference on Mobile Services Reliable Geofencing Assisted Configuration of Proactive Location-based Services

geofence.pdf - 2016 IEEE International Conference on Mobile...

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Reliable Geofencing: Assisted Configuration of Proactive Location-based Services Sandro Rodriguez Garzon and Mustafa Elbehery Service-centric Networking Telekom Innovation Laboratories, TU Berlin Berlin, Germany [email protected] [email protected] Bersant Deva and Axel Küpper Service-centric Networking Telekom Innovation Laboratories, TU Berlin Berlin, Germany [email protected] [email protected] Abstract —Today, proactive location-based services (LBS) are gaining momentum as mobile devices became able to track the users’ position in the background without notable battery drain. They are used in several application areas like location- based marketing or gaming to deliver notifications, e.g. coupons, proactively to the user once a defined geographical area, also known as geofence, is entered. Owning to various reasons like the limited preciseness of positioning techniques for outdoor environments or the strict energy constraints of today’s mobile devices, proactive LBS are still facing reliability issues. Either the user is burdened with non-relevant notifications in case the proactive LBS wrongly assumed the user to be located within a geofence, or notifications are not received at all although the user visited the geofence. This paper investigates how the day-by- day configuration of proactive LBS with geofences may influence the reliability of the service as a whole. Based on the findings, it introduces a web service which quantifies how reliable a proactive LBS will most probably be with respect to a given geofence in order to enable even non-experts to properly set up a proactive LBS with appropriate geofences. I. I NTRODUCTION During the last years, location-based services (LBS) appar- ently became the most popular type of context-aware service used on mobile devices. With the introduction of miniaturized and integrated sensor solutions for continuous and energy- efficient background tracking on mobile devices, they have evolved towards a second generation of LBS that are capable of acting proactively once the user’s location falls into a predefined region, a mechanism better known as Geofencing [1]. Nowadays, various domains take advantage of these perva- sive computing capabilities in order to deliver location-based coupons to potential customers of brick-and-mortar stores, to conduct neighborhood-wide polls [2] or to alert citizens in a smart city if they approach an area of high air pollution [3]. Despite the latest commercial breakthrough of proactive LBS within different application fields, they are still suffering from reliability issues [4], [5]. Owing to different technical limitations, they might miss to detect a user to be within a dedicated area of interest (geofence) or might burden the user with non-relevant information once the user already left the geofence. At first, the accuracy of a position technique comes into focus [6] since the higher the mean accuracy, the higher
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  • Fall '14
  • RNA, Work, Personal digital assistant, geofences, proactive LBS

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