Abstract
Recent activity in the field of Internet-of-Things experimentation has focused on the federation of discrete testbeds, thus placing less effort in the integration of other related technologies, such as smartphones; also, while it is gradually moving to more application-oriented paths, such as urban settings, it has not dealt in large with applications having social networking features. We argue here that current IoT infrastructure, testbeds and related software technologies should be used in such a context, capturing real-world human mobility and social networking interactions, for use in evaluating and fine-tuning realistic mobility models and designing human-centric applications. We discuss a system for producing traces for a new generation of human-centric applications, utilizing technologies such as Bluetooth and focusing on human interactions. We describe the architecture for this system and the respective implementation details presenting two distinct deployments; one in an office environment and another in an exhibition/conference event with 103 active participants combined, thus covering two popular scenarios for human centric applications. Our system provides online, almost real-time, feedback and statistics and its implementation allows for rapid and robust deployment, utilizing mainstream technologies and components.
Chapter PDF
Similar content being viewed by others
References
Coulson, G., et al.: Flexible experimentation in wireless sensor networks. Communications of the ACM (CACM) 55(1), 82–90 (2012)
SmartSantader project, http://smartsantander.eu
Miluzzo, E., et al.: Darwin Phones: the Evolution of Sensing and Inference on Mobile Phones. In: MobiSys 2010, pp. 5–20 (2010)
Eagle, N., Pentland, A.: Reality Mining: Sensing Complex Social Systems. In: Personal and Ubiquitous Computing, pp. 255–268 (May 2006)
Borovoy, R., et al.: Meme tags and community mirrors: moving from conferences to collaboration. In: CSCW 1998, pp. 159–168 (1998)
Hui, P., et al.: Pocket switched networks and human mobility in conference environments. In: WDTN 2005, pp. 244–251 (2005)
Nordstrom, E., Diot, C., Gass, R., Gunningberg, P.: Experiences from measuring human mobility using Bluetooth inquiring devices. In: MobiEval 2007, pp. 15–20 (2007)
Nicolai, T., Yoneki, E., Behrens, N., Kenn, H.: Exploring Social Context with the Wireless Rope. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM 2006 Workshops, part I. LNCS, vol. 4277, pp. 874–883. Springer, Heidelberg (2006)
Natarajan, A., Motani, M., Srinivasan, V.: Understanding Urban Interactions from Bluetooth Phone Contact Traces. In: Uhlig, S., Papagiannaki, K., Bonaventure, O. (eds.) PAM 2007. LNCS, vol. 4427, pp. 115–124. Springer, Heidelberg (2007)
Chaintreau, A., Hui, P., Crowcroft, J., Diot, C., Gass, R., Scott, J.: Impact of Human Mobility on Opportunistic Forwarding Algorithms. IEEE Transactions on Mobile Computing 6(6), 606–620 (2007)
SocioPatterns, http://www.sociopatterns.org
Brockmann, D., Hufnagel, L., Geisel, T.: The scaling laws of human travel. Nature 439(7075), 462–465 (2006)
Gonzalez, M., Hidalgo, C., Barabasi, A.-L.: Understanding individual human mobility patterns. Nature 453(7196), 779–782 (2008)
Song, C., Koren, T., Wang, P., Barabasi, A.-L.: Modelling the scaling properties of human mobility. Nature Physics (2010)
Eagle, N., Pentland, A.: Eigenbehaviors: Identifying structure in routine. Behavioral Ecology and Sociobiology 63(7), 1057–1066 (2009)
Liben-Nowell, D., Kleinberg, J.M.: The link prediction problem for social networks. In: CIKM 2003, pp. 556–559 (2003)
Wang, D., Pedreschi, D., Song, C., Giannotti, F., Barabasi, A.-L.: Human Mobility. In: Social Ties, and Link Prediction KDD 2011 (2011)
Lambiotte, R., et al.: Geographical dispersal of mobile communication networks. Physica A: Statistical Mechanics and its Applications 387(21), 17 (2008)
Backstrom, L., Sun, E., Marlow, C.: Find Me If You Can: Improving Geographical Prediction with Social and Spatial Proximity. North, pp. 61–70. ACM (2010)
Decker, G., Weske, M.: Interaction-centric modeling of process choreographies. Inf. Syst. 36, 292–312 (2011)
Olguin, D.O., et al.: Sensible Organizations: Technology and Methodology for Automatically Measuring Organizational Behavior. IEEE Transactions on Systems, Man, and Cybernetics 39 (February 2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
This chapter is published under an open access license. Please check the 'Copyright Information' section either on this page or in the PDF for details of this license and what re-use is permitted. If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and re-use information, please contact the Rights and Permissions team.
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Antoniou, A., Theodoridis, E., Chatzigiannakis, I., Mylonas, G. (2012). Using Future Internet Infrastructure and Smartphones for Mobility Trace Acquisition and Social Interactions Monitoring. In: Álvarez, F., et al. The Future Internet. FIA 2012. Lecture Notes in Computer Science, vol 7281. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30241-1_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-30241-1_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30240-4
Online ISBN: 978-3-642-30241-1
eBook Packages: Computer ScienceComputer Science (R0)