ISSN 2225-7217
ARPN Journal of Science and Technology
©2011-2012. All rights reserved. http://www.ejournalofscience.org Location Based Reminder Using GPS For Mobile (Android)
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Priyanka Shah, 2 Ruta Gadgil, 3 Neha Tamhankar
Department of Computer Engg, Smt. Kashibai Navale, College of Engineering
Pune, Maharashtra India
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priyanka27.in@gmail.com, 2 ruta.gadgil@gmail.com, 3 nehatamhankar.1311@gmail.com
ABSTRACT
Although location-based reminder applications have been widely prototyped, there are few results regarding their impact on people: how are they used, do they change people’s behavior and what features influence usefulness the most. Cell phones provide a compelling platform for the delivery of location-based reminders within a user 's everyday natural context. We present requirements for location-based reminders resulting from a qualitative study performed at small area in the city, and elaborate how these results are influencing ongoing design of a more comprehensive location-based reminder system. In this paper we propose an architecture of location based services which uses GPS. Within the architecture, we discuss the challenges for context management, service trigger mechanism and preference-based services.
Keywords: LDK (Location Distance Keyword), GPS (Global Positioning System), LBS (Location Based Services)
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INTRODUCTION
The main purpose of location-based services is to provide services to customers based on the knowledge of their locations. Examples of these services include real-time traffic information, digital map services which are delivered to mobile terminals according to user’s location to minimize data transmission, providing dynamic guidance services according to the users’ location and current traffic condition; requesting the nearest business or service(e.g., the nearest restaurant or cinema) and location based advertising (like “Send ecoupons to all cars that are
References: Based Services, 2010 International Conference on Electronics and Information Engineering (ICEIE Discretization Technique based on Frequency and K-Nearest Neighbour algorithm, 2009 2nd