A new splitting-based displacement prediction approach for location-based services

DAOUD, Mohammad Sh., AYESH, Aladdin, HOPGOOD, Adrian A. and AL-FAYOUMI, Mustafa (2011). A new splitting-based displacement prediction approach for location-based services. In: IEEE international conference on systems, man, and cybernetics 2011. IEEE Xplore, 392-397.

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Official URL: http://dx.doi.org/10.1109/ICSMC.2011.6083697
Link to published version:: https://doi.org/10.1109/ICSMC.2011.6083697


In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Several location prediction models have been proposed to enhance and increase the relevance of the information retrieved by users of mobile information systems, but none of them studied the relationship between accuracy rate of prediction and the performance of the model in terms of consuming resources and constraints of mobile devices. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. One such technique is the Prediction Location Model (PLM), which deals with inner cell structure. The PLM technique suffers from memory usage and poor accuracy. The main goal of this paper is to propose a new path prediction technique for Location-Based Services. The new approach is competitive and more efficient compared to PLM regarding measurements such as accuracy rate of location prediction and memory usage.

Item Type: Book Section
Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Modelling Research Centre > Microsystems and Machine Vision Laboratory
Identification Number: https://doi.org/10.1109/ICSMC.2011.6083697
Page Range: 392-397
Depositing User: Adrian Hopgood
Date Deposited: 31 Aug 2012 14:37
Last Modified: 18 Mar 2021 13:51
URI: https://shura.shu.ac.uk/id/eprint/5645

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