Introduction / Tom Lovett and Eamonn O'Neill -- Modeling Success, Failure, and Intent of Multi-Agent Activities Under Severe Noise / Adam Sadilek and Henry Kautz -- Energy-Accuracy Trade-offs of Sensor Sampling in Smart Phone Based Sensing Systems / Kiran K. Rachuri, Cecilia Mascolo and Mirco Musolesi -- Acceleration Noise Correction for Transfer Inference Using Accelerometers on Mobile Devices / Hisao Setoguchi, Yuzo Okamoto, Naoki Iketani, Kenta Cho and Masanori Hattori, et al. -- Mobile Sensing of User's Motion and Position Context for Automatic Check-in Suggestion and Validation / Cristina Frà, Massimo Valla, Alessio Agneessens, Igor Bisio and Fabio Lavagetto -- The Case for Context-Aware Resources Management in Mobile Operating Systems / Narseo Vallina-Rodriguez and Jon Crowcroft -- A Scalable Sensor Middleware for Social End-User Programming / Salvador Faria and Vassilis Kostakos -- Mobile Context-Aware Support for Public Transportation Users / Esben von Buchwald, Jakob Eg Larsen and Roderick Murray-Smith -- Quality Sensitive Web Service Profiling and Discovery: In Support of Mobile and Pervasive Applications / Sherif G. Aly and Ahmed M. Hamza -- A Middleware Supporting Adaptive and Context-Aware Mobile Applications / Lincoln David, José Viterbo, Marcelo Malcher, Hubert Fonseca and Gustavo Baptista, et al.
CITATION STYLE
von Buchwald, E., Eg Larsen, J., & Murray-Smith, R. (2012). Mobile Context-Aware Support for Public Transportation Users. In Mobile Context Awareness (pp. 133–142). Springer London. https://doi.org/10.1007/978-0-85729-625-2_8
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