People as Sensors and Collective Sensing-Contextual Observations Complementing Geo-Sensor Network Measurements

Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Ubiquitous sensor networks and Location-based Services can potentially assist in taking decisions in near real time in a variety of application areas such as public safety, traffic management, environmental monitoring or in public health. Yet, analysing our surroundings in real time is still a major challenge due to sparsely available data sources for real-time monitoring. The innovative concept of People as Sensors defines a measurement model, in which measurements are not only taken by calibrated hardware sensors, but in which also humans can contribute their individual ‘measurements’ such as their subjective sensations, current perceptions or personal observations. This chapter contains a disambiguation between the terms People as Sensors (people contributing subjective observations), Collective Sensing (analysing aggregated anonymised data coming from collective networks) and Citizen Science (exploiting and elevating expertise of citizens and their personal, local experiences). Then, the particular significance of integrating the People as Sensors concept with established LBS, data analysis and visualisation systems is elaborated. Finally, the paper discusses current challenges, points out possible solutions, and pin-points directions for future research areas.

Keywords

People as sensors Human observations Collective sensing Location-based services Privacy 

Notes

Acknowledgments

The author would like to thank all involved researchers and external contributors, from which the publication Resch et al. (2011) originated. This was a strong foundation for the presented research. Furthermore, a particular ‘thanks’ goes to all people at University of Osnabrück, Research Studios Austria, Massachusetts Institute of Technology and Salzburg University of Applied Sciences who offered their valuable thoughts.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.SENSEable City LabMITCambridgeUSA
  2. 2.Institute of Geography–GIScienceUniversity of HeidelbergHeidelbergGermany
  3. 3.Institute for Geoinformatics and Remote SensingUniversity of OsnabrückOsnabrückGermany

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