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Participatory Sensing, Opinions and Collective Awareness pp 9–19Cite as

Human Sensors on the Move

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Part of the book series: Understanding Complex Systems ((UCS))

Abstract

In this section we provide an extensive summary of human sensors on the move, or mobile systems that are designed to collect data from smartphones that users carry in their everyday life. One can rely on people’s own mobile phones to collect data as they are at their close vicinity 90 % of the time (Dey et al. 2011). These devices have immense potential to collect rich data about people’s behaviour and habits, as well as their environment. In this chapter, we first outline the general idea of human sensor, then dive into some technical challenge before we present a number of systems to generate context on mobile phones.

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References

  • Aharony, N., Pan, W., Ip, C., Khayal, I., Pentland, A.: The social fMRI: measuring, understanding, and designing social mechanisms in the real world. In: UbiComp ‘11: Proceedings of the 13th International Conference on Ubiquitous Computing, pp. 445–454. ACM (2011). doi:10.1145/2030112.2030171

  • Balazinska, M., Castro, P.: Characterizing mobility and network usage in a corporate wireless local-area network. In: MobiSys ‘03: MobiSys, pp. 303–316. ACM (2003). doi:10.1145/1066116.1066127

  • Banerjee, N., Rahmati, A., Corner, M.D., Rollins, S., Zhong, L.: Users and batteries: interactions and adaptive energy management in mobile systems. In: UbiComp ‘07: Proceedings of the 9th International Conference on Ubiquitous Computing, pp. 217–234. Springer, Berlin/Heidelberg (2007)

    Google Scholar 

  • Biegel, G., Cahill, V.: A framework for developing mobile, context-aware applications. In: PerCom, pp. 361–365. IEEE (2004). doi:10.1109/PERCOM.2004.1276875

  • Brunette, W., Sodt, R., Chaudhri, R., Goel, M., Falcone, M., Van Orden, J., Borriello, G.: Open data kit sensors: a sensor integration framework for android at the application-level. In: MobiSys ‘12: Proceedings of Mobisys, pp. 351–364. ACM (2012). doi:10.1145/2307636.2307669

  • Burke, J.A., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., Srivastava, M.B.: Participatory sensing. In: First Workshop on World-Sensor-Web: Mobile Device Centric Sensory Networks and Applications at Sensys ‘06 (2006)

    Google Scholar 

  • Carter, S., Mankoff, J., Heer, J.: Momento: support for situated ubicomp experimentation. In: CHI ‘07: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 125–134. ACM (2007). doi:10.1145/1240624.1240644

  • Chaintreau, A., Hui, P., Crowcroft, J., Diot, C., Gass, R., Scott, J.: Impact of human mobility on opportunistic forwarding algorithms. IEEE Trans. Mob. Comput. 6(6), 606–620 (2007). doi:10.1109/TMC.2007.1060

    Article  Google Scholar 

  • D’Hondt, E., Stevens, M., Jacobs, A.: Participatory noise mapping works! An evaluation of participatory sensing as an alternative to standard techniques for environmental monitoring. Pervasive Mob. Comput. 9(5), 681–694 (2013)

    Article  Google Scholar 

  • Dey, A.K., Abowd, G.D., Salber, D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum. Comput. Interact. 16(2), 97–166 (2001). doi:10.1207/S15327051HCI16234_02

    Article  Google Scholar 

  • Dey, A.K., Wac, K., Ferreira, D., Tassini, K., Hong, J.-H., Ramos, J.: Getting closer: an empirical investigation of the proximity of user to their smart phones. In: UbiComp ‘11: Ubicomp, pp. 163–172. ACM (2011). doi:10.1145/2030112.2030135

  • Dickerson, R.F., Gorlin, E.I., Stankovic, J.A.: Empath: a continuous remote emotional health monitoring system for depressive illness. In: WH ‘11: Proceedings of the 2nd Conference on Wireless Health, pp. 5:1–5:10. ACM (2011). doi:10.1145/2077546.2077552

  • Eagle, N., Pentland, A.: Reality mining: sensing complex social systems. Pers. Ubiquit. Comput. 10(4), 255–268 (2006). doi:10.1007/s00779-005-0046-3

    Article  Google Scholar 

  • Eisenman, S.B., Miluzzo, E., Lane, N.D., Peterson, R.A., Ahn, G.-S., Campbell, A.T.: BikeNet: a mobile sensing system for cyclist experience mapping. ACM Trans. Sen. Netw 6(1), 6:1–6:39 (2010). doi:10.1145/1653760.1653766

    Google Scholar 

  • Falaki, H., Mahajan, R., Estrin, D.: SystemSens: a tool for monitoring usage in smartphone research deployments. In MobiArch ‘11: Proceedings of the Sixth International Workshop on Mobiarch, pp. 25–30. ACM (2011). doi:10.1145/1999916.1999923

  • Ferreira, D.: Aware: a mobile context instrumentation middleware to collaboratively understand human behavior. Doctoral Dissertation, University of Oulu (2013)

    Google Scholar 

  • Froehlich, J., Chen, M.Y., Consolvo, S., Harrison, B., Landay, J.A.: MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones. In: MobiSys ‘07: Proceedings of the 5th International Conference on Mobile Systems, Applications and Services, pp. 57–70. ACM (2007). doi:10.1145/1247660.1247670

  • Ginger.io: Ginger.Io. [Web page] Retrieved from http://ginger.io/ (2012)

  • Hasenfratz, D., Saukh, O., Sturzenegger, S., Thiele, L.: Participatory air pollution monitoring using smartphones. In: 2nd International Workshop on Mobile Sensing. ACM (2012)

    Google Scholar 

  • Kansal, A., Saponas, S., Brush, A.J., McKinley, K.S., Mytkowicz, T., Ziola, R.: The latency, accuracy, and battery (LAB) abstraction: programmer productivity and energy efficiency for continuous mobile context sensing. ACM SIGPLAN Not. 48(10), 661–676 (2013)

    Article  Google Scholar 

  • Khan, W.Z., Xiang, Y., Aalsalem, M.Y., Arshad, Q.: Mobile phone sensing systems: a survey. IEEE Commun. Surv. Tutorials 15(1), 402–427 (2013)

    Article  Google Scholar 

  • Kim, D.H., Kim, Y., Estrin, D., Srivastava, M.B.: SensLoc: sensing everyday places and paths using less energy. In: Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, pp. 43–56. ACM (2010)

    Google Scholar 

  • Kindberg, T., Zhang, K.: Secure spontaneous device association. In: UbiComp 2003: Ubiquitous Computing, pp. 124–131. Springer, Berlin/Heidelberg (2003). doi:10.1007/978-3-540-39653-6_9

  • Korpipää, P., Häkkilä, J., Kela, J., Ronkainen, S., Känsälä, I.: Utilising context ontology in mobile device application personalisation. In: MUM ‘04: Proceedings of the 3rd International Conference on Mobile and Ubiquitous Multimedia, pp. 133–140. ACM (2004). doi:10.1145/1052380.1052399

  • Kostakos, V., O’Neill, E., Penn, A.: Designing urban pervasive systems. Computer 39(9), 52–59 (2006). doi:10.1109/MC.2006.303

    Article  Google Scholar 

  • Kostakos, V., O’Neill, E., Penn, A., Roussos, G., Papadongonas, D.: Brief encounters: sensing, modeling and visualizing urban mobility and copresence networks. ACM TOCHI 17(1), 2 (2010). doi:10.1145/1721831.1721833

    Article  Google Scholar 

  • Lane, N.D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.T.: A survey of mobile phone sensing. IEEE Commun. Mag. 48(9), 140–150 (2010)

    Article  Google Scholar 

  • McNett, M., Voelker, G.M.: Access and mobility of wireless PDA users. Mob. Comput. Commun. Rev. 9(2), 40–55 (2005). doi:10.1145/1072989.1072995

    Article  Google Scholar 

  • Miluzzo, E., Lane, N.D., Fodor, K., Peterson, R., Lu, H., Musolesi, M., … Campbell, A.T.: Sensing meets mobile social networks: the design, implementation and evaluation of the cenceme application. In: SenSys ‘08: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, pp. 337–350. ACM (2008). doi:10.1145/1460412.1460445

  • Nacci, A.A., Trovò, F., Maggi, F., Ferroni, M., Cazzola, A., Sciuto, D., Santambrogio, M.D.: Adaptive and flexible smartphone power modeling. Mob. Netw. Appl. 18(5), 600–609 (2013)

    Article  Google Scholar 

  • Nicolai, T., Yoneki, E., Behrens, N., Kenn, H.: Exploring social context with the wireless rope. In: OTM, pp. 874–883 (2006). doi:10.1007/11915034_112

  • O’Neill, E., Kostakos, V., Kindberg, T., Schiek, A., Penn, A., Fraser, D., Jones, T.: Instrumenting the city: developing methods for observing and understanding the digital cityscape. In: Ubicomp, pp. 315–332. Springer (2006). doi:10.1007/11853565_19

  • Perttunen, M., Kostakos, V., Riekki, J., Ojala, T.: Spatio-temporal patterns link your digital identities. Comput. Environ. Urban Syst., 1–10 (2014). doi:10.1016/j.compenvurbsys.2013.12.004

  • Rachuri, K.K., Musolesi, M., Mascolo, C., Rentfrow, P.J., Longworth, C., Aucinas, A.: EmotionSense: a mobile phones based adaptive platform for experimental social psychology research. In: Ubicomp ‘10: Proceedings of the 12th ACM International Conference on Ubiquitous Computing, pp. 281–290. ACM (2010). doi:10.1145/1864349.1864393

  • Raento, M., Oulasvirta, A., Petit, R., Toivonen, H.: ContextPhone: a prototyping platform for context-aware mobile applications. IEEE Pervasive Comput. 4(2), 51–59 (2005). doi:10.1109/MPRV.2005.29

    Article  Google Scholar 

  • Ramanathan, N., Alquaddoomi, F., Falaki, H., George, D., Hsieh, C., Jenkins, J., Estrin, D.: Ohmage: an open mobile system for activity and experience sampling. In: PervasiveHealth, pp. 203–204. IEEE (2012)

    Google Scholar 

  • Rana, R.K., Chou, C.T., Kanhere, S.S., Bulusu, N., Hu, W.: Ear-phone: an end-to-end participatory urban noise mapping system. In: Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, pp. 105–116. ACM (2010)

    Google Scholar 

  • Rathnayake, U., Petander, H., Ott, M., Seneviratne, A.: EMUNE: architecture for mobile data transfer scheduling with network availability predictions. Mob. Netw. Appl. 17(2), 216–233 (2012)

    Article  Google Scholar 

  • Schweizer, I., Bärtl, R., Schulz, A., Probst, F., Mühläuser, M.: NoiseMap-real-time participatory noise maps. In: Proceedings of the 2nd International Workshop on Sensing Applications on Mobile Phones (PhoneSense’11), pp. 1–5 (2011)

    Google Scholar 

  • Schweizer, I., Bärtl, R., Schmidt, B., Kaup, F., Mühlhäuser, M.: Kraken.me mobile: the energy footprint of mobile tracking. In: Proceedings of the 6th International Conference on Mobile Computing, Applications and Services (MobiCASE), pp. 82–89. IEEE (2014)

    Google Scholar 

  • van Sinderen, M.J., van Halteren, A.T., Wegdam, M., Meeuwissen, H.B., Eertink, E.H.: Supporting context-aware mobile applications: an infrastructure approach. IEEE Commun. Mag. 44(9), 96–104 (2006). doi:10.1109/MCOM.2006.1705985

    Article  Google Scholar 

  • Wagner, D.T., Rice, A., Beresford, A.R.: Device analyzer: understanding smartphone usage. In: Mobile and Ubiquitous Systems: Computing, Networking, and Services, pp. 195–208. Springer (2014)

    Google Scholar 

  • Wang, Y., Lin, J., Annavaram, M., Jacobson, Q.A., Hong, J., Krishnamachari, B., Sadeh, N.: A framework of energy efficient mobile sensing for automatic user state recognition. In: Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services, pp. 179–192. ACM (2009)

    Google Scholar 

  • Weiser, M.: The computer for the 21st century. ACM SIGMOBILE Mob. Comput. Commun. Rev. 3(3), 3–11 (1999). doi:10.1145/329124.329126

    Article  Google Scholar 

  • Zhang, L., Tiwana, B., Qian, Z., Wang, Z., Dick, R.P., Mao, Z.M., Yang, L.: Accurate online power estimation and automatic battery behavior based power model generation for smartphones. In: Proceedings of the Eighth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, pp. 105–114. ACM (2010)

    Google Scholar 

  • Zhuang, Z., Kim, K.H., Singh, J.P.: Improving energy efficiency of location sensing on smartphones. In: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, pp. 315–330. ACM (2010)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Center for Ubiquitous Computing, University of Oulu, Oulu, Finland

    Denzil Ferreira & Vassilis Kostakos

  2. Telecooperation Lab, Department of Computer Science, Technical University, Darmstadt, Germany

    Immanuel Schweizer

Authors
  1. Denzil Ferreira
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  2. Vassilis Kostakos
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  3. Immanuel Schweizer
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Corresponding author

Correspondence to Denzil Ferreira .

Editor information

Editors and Affiliations

  1. Department of Physics, Sapienza University of Rome, Rome, Italy

    Vittorio Loreto

  2. Department of Civil, Environmental and Geomatic Engineering, University College London, London, United Kingdom

    Muki Haklay

  3. Julius-Maximilians-University Würzburg , Würzburg, Germany

    Andreas Hotho

  4. Department of Physics, Sapienza University of Rome, Rome, Italy

    Vito D.P. Servedio

  5. Department of Electrical Engineering and Computer Science, University of Kassel, Kassel, Germany

    Gerd Stumme

  6. VITO—Flemish Institute for Technological Research, Mol, Belgium

    Jan Theunis

  7. Institute for Scientific Interchange Foundation, Torino, Italy

    Francesca Tria

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Ferreira, D., Kostakos, V., Schweizer, I. (2017). Human Sensors on the Move. In: Loreto, V., et al. Participatory Sensing, Opinions and Collective Awareness. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-25658-0_1

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