Advances of the Location Based Context-Aware Mobile Services in the Transport Sector

As computing becomes increasingly mobile today, applications and services need to be able to adapt to dynamic environments. Within a suitable framework, context-aware mobile services constitute a market-oriented technological development that could potentially meet end-user needs. In this framework a “context” can be defined as any set of information and/or status of elements, obtained either explicitly or implicitly, that can be used to characterise a certain aspect of an entity or an event involved in a specific application or network service. The term “entity” can be absTRacT

[1]  Muhammad Usman Improving Knowledge Discovery through the Integration of Data Mining Techniques , 2015 .

[2]  Athanasios V. Vasilakos,et al.  Comparative Study of Incremental Learning Algorithms in Multidimensional Outlier Detection on Data Stream , 2015 .

[3]  Subir Biswas,et al.  Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety , 2006, IEEE Communications Magazine.

[4]  J C Miles,et al.  The potential application of artificial intelligence in transport , 2006 .

[5]  Nitin H. Vaidya,et al.  A vehicle-to-vehicle communication protocol for cooperative collision warning , 2004, The First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, 2004. MOBIQUITOUS 2004..

[6]  Chung-Ping Young,et al.  Intelligent data fusion system for predicting vehicle collision warning using vision/GPS sensing , 2010, Expert Syst. Appl..

[7]  Martin Mauve,et al.  Decentralized discovery of free parking places , 2006, VANET '06.

[8]  Sharanjit Kaur,et al.  A Parameterized Framework for Clustering Streams , 2009, Int. J. Data Warehous. Min..

[9]  Eliamani Sedoyeka,et al.  WiMAX Networks: Operations and QoS in Developing Countries , 2012, Int. J. Handheld Comput. Res..

[10]  H. Suzuki,et al.  Wireless communications for vehicle safety: Radio link performance and wireless connectivity methods , 2006, IEEE Vehicular Technology Magazine.

[11]  Abigail L. Bristow,et al.  Developing an Enhanced Weight-Based Topological Map-Matching Algorithm for Intelligent Transport Systems , 2009 .

[12]  S. Karthika,et al.  SpyNetMiner: An Outlier Analysis to Tag Elites in Clandestine Social Networks , 2014, Int. J. Data Warehous. Min..

[13]  David Taniar,et al.  Integrations of Data Warehousing, Data Mining and Database Technologies - Innovative Approaches , 2011 .

[14]  Herbert Baum,et al.  The Assessment of the Socio-economic Impact of the Introduction of Intelligent Safety Systems in Road Vehicles — Findings of the EU Funded Project SEiSS , 2005 .

[15]  Hao Wu,et al.  Simulation-Based Operations Planning for Regional Transportation Systems , 2003, DG.O.

[16]  Christie I. Ezeife,et al.  Towards Comparative Mining of Web Document Objects with NFA: WebOMiner System , 2012, Int. J. Data Warehous. Min..

[17]  Narushige Shiode,et al.  Urban Planning, Information Technology, and Cyberspace , 2000 .

[18]  Marco Roccetti,et al.  Communities on the road: fast triggering of interactive multimedia services , 2009, Multimedia Tools and Applications.

[19]  Hakikur Rahman Data Mining Algorithms for Measuring Performance Impact of Social Development Processes: Ethical Implications , 2013 .

[20]  Isabel Ramos,et al.  Ethical Data Mining Applications for Socio-Economic Development , 2013 .