International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 45 - Issue 15 |
Published: May 2012 |
Authors: K.B. Priya Iyer, V. Shanthi |
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K.B. Priya Iyer, V. Shanthi . Geo-calendar based Predictive Skyline Queries using Fuzzy Inference Engine. International Journal of Computer Applications. 45, 15 (May 2012), 52-58. DOI=10.5120/6859-9489
@article{ 10.5120/6859-9489, author = { K.B. Priya Iyer,V. Shanthi }, title = { Geo-calendar based Predictive Skyline Queries using Fuzzy Inference Engine }, journal = { International Journal of Computer Applications }, year = { 2012 }, volume = { 45 }, number = { 15 }, pages = { 52-58 }, doi = { 10.5120/6859-9489 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2012 %A K.B. Priya Iyer %A V. Shanthi %T Geo-calendar based Predictive Skyline Queries using Fuzzy Inference Engine%T %J International Journal of Computer Applications %V 45 %N 15 %P 52-58 %R 10.5120/6859-9489 %I Foundation of Computer Science (FCS), NY, USA
Embedding Information technology with Transportation system creates a new era in building Intelligent Transportation System (ITS). An effective Intelligent Transportation System reduces traffic congestion, environmental pollution, fuel consumption and driver in-convenience etc. The widespread adoption of GPS-enabled mobile devices has opened new possibilities of developing an ITS. With advancements in Wireless technologies, GIS and sensors, spatial route search are important class of queries under location based services. In this paper, we introduce a new spatial query called Predictive Skyline query (PSQ) on time dependent road networks. The PSQ is a spatial route search query for future journey schedule which are popular apps under Intelligent Transportation Systems. The algorithm consists of five phases namely PSQuery Initiator (QI), Fuzzy Travel Time Forecaster (FTF), PSQuery Executor and Optimizer (QEO), Traffic Fuzzy Controller (TFC), PSQuery Recorder (QR). The FTF predicts the travel time based on historical data using fuzzy inference rules. The TFC predicts the overall traffic congestion in the user specified spatial region on the scheduled journey date. The experimental evaluation reflects the accuracy of travel time prediction in real road networks and efficiency of algorithm in processing PSQ queries.