@article{becker2013human,
  abstract = {Anonymous location data from cellular phone networks sheds light on how people move around on a large scale.},
  acmid = {2398375},
  address = {New York, NY, USA},
  author = {Becker, Richard and C\'{a}ceres, Ram\'{o}n and Hanson, Karrie and Isaacman, Sibren and Loh, Ji Meng and Martonosi, Margaret and Rowland, James and Urbanek, Simon and Varshavsky, Alexander and Volinsky, Chris},
  doi = {10.1145/2398356.2398375},
  interhash = {a12186255089937b97b17bd46c1dc689},
  intrahash = {98da3ee109ea87bdb735cbda1fd202a7},
  issn = {0001-0782},
  issue_date = {January 2013},
  journal = {Communications of the ACM},
  month = jan,
  number = 1,
  numpages = {9},
  pages = {74--82},
  publisher = {ACM},
  title = {Human mobility characterization from cellular network data},
  url = {http://doi.acm.org/10.1145/2398356.2398375},
  volume = 56,
  year = 2013
}

@article{maisonneuve2010participatory,
  abstract = {Noise pollution is a major problem in cities around the world. The current methods to assess it neglect to represent the real exposure experienced by the citizens themselves, and therefore could lead to wrong conclusions and a biased representations. In this paper we present a novel approach to monitor noise pollution involving the general public. Using their mobile phones as noise sensors, we provide a low cost solution for the citizens to measure their personal exposure to noise in their everyday environment and participate in the creation of collective noise maps by sharing their geo-localized and annotated measurements with the community. Our prototype, called NoiseTube, can be found online [1].},
  author = {Maisonneuve, Nicolas and Stevens, Matthias and Ochab, Bartek},
  doi = {10.3233/IP-2010-0200},
  interhash = {75f1760b3c55de573fffd69fcc10548e},
  intrahash = {4dbb1ce355b7249bc2f66ed4b2126bab},
  journal = {Information Polity},
  month = jan,
  number = 1,
  pages = {51--71},
  publisher = {IOS Press},
  title = {Participatory noise pollution monitoring using mobile phones},
  url = {http://dx.doi.org/10.3233/IP-2010-0200},
  volume = 15,
  year = 2010
}

@article{kanjo2010noisespy,
  abstract = {In this paper we present the design, implementation, evaluation, and user experiences of the NoiseSpy application, our sound sensing system that turns the mobile phone into a low-cost data logger for monitoring environmental noise. It allows users to explore a city area while collaboratively visualizing noise levels in real-time. The software combines the sound levels with GPS data in order to generate a map of sound levels that were encountered during a journey. We report early findings from the trials which have been carried out by cycling couriers who were given Nokia mobile phones equipped with the NoiseSpy software to collect noise data around Cambridge city. Indications are that, not only is the functionality of this personal environmental sensing tool engaging for users, but aspects such as personalization of data, contextual information, and reflection upon both the data and its collection, are important factors in obtaining and retaining their interest.},
  acmid = {1831011},
  address = {Hingham, MA, USA},
  author = {Kanjo, Eiman},
  doi = {10.1007/s11036-009-0217-y},
  interhash = {12b29df257d71dfd37193d6b4665004e},
  intrahash = {387ebc6472794f598d07256a45f3d9b7},
  issn = {1383-469X},
  issue_date = {August    2010},
  journal = {Mobile Networks and Applications},
  month = aug,
  number = 4,
  numpages = {13},
  pages = {562--574},
  publisher = {Kluwer Academic Publishers},
  title = {NoiseSPY: A Real-Time Mobile Phone Platform for Urban Noise Monitoring and Mapping},
  url = {http://dx.doi.org/10.1007/s11036-009-0217-y},
  volume = 15,
  year = 2010
}

@article{luther2008situational,
  abstract = {We study the case of integrating situational reasoning into a mobile service recommendation system. Since mobile Internet services are rapidly proliferating, finding and using appropriate services require profound service descriptions. As a consequence, for average mobile users it is nowadays virtually impossible to find the most appropriate service among the many offered. To overcome these difficulties, task navigation systems have been proposed to guide users towards best-fitting services. Our goal is to improve the user experience of such task navigation systems making them context-aware (i.e. to optimize service navigation by taking the user's situation into account). We propose the integration of a situational reasoning engine that applies classification-based inference to qualitative context elements, gathered from multiple sources and represented using ontologies. The extended task navigator enables the delivery of situation-aware recommendations in a proactive way. Initial experiments with the extended system indicate a considerable improvement of the navigator's usability. },
  author = {Luther, Marko and Fukazawa, Yusuke and Wagner, Matthias and Kurakake, Shoji},
  doi = {10.1017/S0269888907001300},
  eprint = {http://journals.cambridge.org/article_S0269888907001300},
  interhash = {c71d15a53708c45d5911e4d9c940cd99},
  intrahash = {35ebbce0abbe9bbef462e5479cb419ed},
  issn = {1469-8005},
  journal = {The Knowledge Engineering Review},
  month = feb,
  number = {Special Issue 01},
  numpages = {13},
  pages = {7--19},
  title = {Situational reasoning for task-oriented mobile service recommendation},
  url = {http://dx.doi.org/10.1017/S0269888907001300},
  volume = 23,
  year = 2008
}

@article{song2010limits,
  abstract = {A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.
},
  author = {Song, Chaoming and Qu, Zehui and Blumm, Nicholas and Barabási, Albert-László},
  doi = {10.1126/science.1177170},
  eprint = {http://www.sciencemag.org/cgi/reprint/327/5968/1018.pdf},
  interhash = {f2611a08bf6db54f86e884c05f3cb5fb},
  intrahash = {a89330f8eb32ce62b5f5c9a2b4909f25},
  journal = {Science},
  number = 5968,
  pages = {1018--1021},
  title = {Limits of Predictability in Human Mobility},
  url = {http://www.sciencemag.org/cgi/content/abstract/327/5968/1018},
  volume = 327,
  year = 2010
}

@article{naaman2008zonetag,
  abstract = {We describe ZoneTag, a camera phone application that allows users to capture, annotate, and share photos directly from their phone.},
  address = {Los Alamitos, CA, USA},
  author = {Naaman, Mor and Nair, Rahul},
  doi = {http://doi.ieeecomputersociety.org/10.1109/MMUL.2008.69},
  editor = {Panchanathan, Sethuraman},
  interhash = {0eaa336bc425a2710aefe9b2a4f3711d},
  intrahash = {3a6067d3abc1cfdb9b59aa8e222ea664},
  issn = {1070-986X},
  journal = {IEEE MultiMedia},
  number = 3,
  pages = {34-40},
  publisher = {IEEE Computer Society},
  title = {ZoneTag's Collaborative Tag Suggestions: What is This Person Doing in My Phone?},
  volume = 15,
  year = 2008
}

@misc{candia-2007,
  abstract = { Novel aspects of human dynamics and social interactions are investigated by means of mobile phone data. Using extensive phone records resolved in both time and space, we study the mean collective behavior at large scales and focus on the occurrence of anomalous events. We discuss how these spatiotemporal anomalies can be described using standard percolation theory tools. We also investigate patterns of calling activity at the individual level and show that the interevent time of consecutive calls is heavy-tailed. This finding, which has implications for dynamics of spreading phenomena in social networks, agrees with results previously reported on other human activities.},
  author = {Candia, J. and Gonzalez, M. C. and Wang, P. and Schoenharl, T. and Madey, G. and Barabasi, A. L.},
  interhash = {16dacb08d5f7c4e2b9876ecba8a99a41},
  intrahash = {ea8b6a4442ccc0cb7dd222f6bd1d992a},
  title = {Uncovering individual and collective human dynamics from mobile phone records},
  url = {http://www.citebase.org/abstract?id=oai:arXiv.org:0710.2939},
  year = 2007
}

@techreport{ieKey,
  author = {Groh, Georg},
  institution = {TU München},
  interhash = {7507ea3706a7cc5aaae769370f0671b1},
  intrahash = {87835f6fce05f443a4956673662734d2},
  month = {March},
  title = {Ortsbezug in kontext-sensitiven Diensten für mobile Communities},
  type = {8. Münchner Fortbildungsseminar Geoinformationssysteme},
  year = 2003
}