Advertisement

Participatory Sensing: Recruiting Bipedal Platforms or Building Issue-centred Projects?

  • Christian NoldEmail author
  • Louise Francis
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

This paper raises questions about the way in which participation and recruitment are framed within participatory sensing. The text outlines a number of assumptions of participatory sensing and using a case study, examines the impacts of these assumptions on the practices of participatory sensing. The case study involves a mobile phone app that monitors ambient sound levels and creates noise maps. The study describes the conceptual and practical challenges of recruiting people and the need for an issue-centred campaign that encases the app inside a wider framework of local environmental issues. Based on observations from the case study, the paper proposes a pragmatic approach to sensing that focuses on designing sensing assemblages that support local issues of public concern. The paper argues that an issue-centred approach enables sensing that allows both machines and humans to participate in an equitable way that maximises their unique sensing abilities.

Keywords

Sound Level Aircraft Noise Sound Meter Community Officer Noise Issue 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Amintoosi, H., Kanhere, S.S.: A trust-based recruitment framework for multi-hop social participatory sensing. In: Proceedings of the 9th IEEE International Conference on Distributed Computing in Sensor Systems (IEEE DCOSS 2013), pp. 266–273. IEEE, Washington, DC, USA (2013)Google Scholar
  2. Angus, A., Papadogkonas, D., Papamarkos, G., Roussos, G., Lane, G., Martin, K., West, N., Thelwall, S., Sujon, Z., Silverstone, R.: Urban social tapestries. Pervasive Comput. 7(4), 44–51 (2008). doi:10.1109/MPRV.2008.84CrossRefGoogle Scholar
  3. Barnett, C., Bridge, G.: Geographies of radical democracy: agonistic pragmatism and the formation of affected interests. Ann. Assoc. Am. Geogr. 103(4), 1022–1040 (2013). doi:10.1080/00045608.2012.660395CrossRefGoogle Scholar
  4. Bhadauria, D., Tekdas, O., Isler, V.: Robotic data mules for collecting data over sparse sensor fields. J. Field Rob. 28(3), 388–404 (2011)CrossRefzbMATHGoogle Scholar
  5. Björgvinsson, E., Ehn, P., Hillgren, P.A.: Agonistic participatory design: working with marginalised social movements. CoDesign 8(2–3), 127–144 (2012)CrossRefGoogle Scholar
  6. Brabham, D.C.: Crowdsourcing as a model for problem solving: an introduction and cases. Convergence Int. J. Res. New Media Technol. 14(1), 75–90 (2008). doi:10.1177/1354856507084420CrossRefGoogle Scholar
  7. Burke, J., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., Srivastava, M.B.: Participatory sensing. In: Workshop on World-Sensor-Web (WSW’06): Mobile Device Centric Sensor Networks and Applications, pp. 117–134. Center for Embedded Network Sensing, UC Los Angeles, ACM (2006)Google Scholar
  8. Campbell, A.T., Eisenman, S.B., Lane, N.D., Miluzzo, E., Peterson, R.A.: People-centric urban sensing. In: Proceedings of the 2nd Annual International Workshop on Wireless Internet - WICON ’06, pp. 18–31. ACM, New York (2006). doi:10.1145/1234161.1234179Google Scholar
  9. Chamberlain, A., Paxton, M., Glover, K., Flintham, M., Price, D., Greenhalgh, C., Benford, S., Tolmie, P., Kanjo, E., Gower, A., Gower, A., Woodgate, D., Fraser, D.S.: Understanding mass participatory pervasive computing systems for environmental campaigns. Pers. Ubiquit. Comput. 18(7), 1775–1792 (2013). doi:10.1007/s00779-013-0756-xCrossRefGoogle Scholar
  10. Chambers, R.: The origins and practice of participatory appraisal. World Dev. 22(7), 953–969 (1994)CrossRefGoogle Scholar
  11. Cohn, J.: Citizen science: can volunteers do real research? BioScience 58(3), 192–197 (2008)CrossRefGoogle Scholar
  12. de Bruyne, P., Gielen, P. (eds.): Community Art. The Politics of Trespassing. Valiz, Amsterdam (2009)Google Scholar
  13. Dewey, J.: The Public and Its Problems. Swallow Press and Ohio University Press, Athens (1927)Google Scholar
  14. 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). doi:10.1016/j.pmcj.2012.09.002CrossRefGoogle Scholar
  15. Dickinson, J.L., Zuckerberg, B., Bonter, D.N.: Citizen science as an ecological research tool: challenges and benefits. Annu. Rev. Ecol. Evol. Syst. 41, 149–172 (2010). doi:10.1146/annurev-ecolsys-102209-144636CrossRefGoogle Scholar
  16. Eisenman, S.B., Lane, N.D., Miluzzo, E., Peterson, R.A., Ahn, G.s., Campbell, A.T.: MetroSense project: people-centric sensing at scale. In: Proceedings of Workshop on World-Sensor-Web (WSW 2006), pp. 6–11. ACM, Boulder, USA (2006)Google Scholar
  17. Ellis, R.: Jizz and the joy of pattern recognition: virtuosity, discipline and the agency of insight in UK naturalists’ arts of seeing. Soc. Stud. Sci. 41(6), 769–790 (2011). doi:10.1177/0306312711423432. http://sss.sagepub.com/cgi/doi/10.1177/0306312711423432 CrossRefGoogle Scholar
  18. Estrin, D.: Reflections on wireless sensing systems: from ecosystems to human systems. In: Radio and Wireless Symposium, 2007 IEEE, pp. 1–4. IEEE, Washington (2007)Google Scholar
  19. EveryAware: EveryAware: enhancing environmental awareness through social information technologies white paper (2011). http://www.everyaware.eu/resources/deliverables/D6_1.pdf
  20. EveryAware: about everyaware and widenoise (2012). http://cs.everyaware.eu/event/widenoise/about
  21. Ganti, R.K., Tsai, Y.E., Abdelzaher, T.F.: SenseWorld: towards cyber-physical social networks. In: IPSN ’08 Proceedings of the 7th International Conference on Information Processing in Sensor Networks, pp. 563–564. IEEE, Washington, DC, USA (2008). doi:10.1109/IPSN.2008.48Google Scholar
  22. HACAN ClearSkies: HACAN ClearSkies. http://www.hacan.org.uk/ (2016)
  23. Hepple, L.W.: Geography and the pragmatic tradition: the threefold engagement. Geoforum 39(4), 1530–1541 (2008). doi:10.1016/j.geoforum.2008.06.002CrossRefGoogle Scholar
  24. Honicky, R.E.: Towards a societal scale, mobile sensing system. Ph.D. thesis, University of California at Berkeley (2011)Google Scholar
  25. Jeremijenko, N.: Feral robotic dogs (2002). http://www.nyu.edu/projects/xdesign/feralrobots/ Google Scholar
  26. Kamel Boulos, M.N., Resch, B., Crowley, D.N., Breslin, J.G., Sohn, G., Burtner, R., Pike, W.A., Jezierski, E., Chuang, K.Y.S.: Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples. Int. J. Health Geogr. 10(67), 1–29 (2011). doi:10.1186/1476-072X-10-67Google Scholar
  27. Kittur, A., Chi, E., Suh, B.: Crowdsourcing user studies with mechanical Turk. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 453–456. ACM, New York, USA (2008). doi:10.1145/1357054.1357127Google Scholar
  28. Krause, A., Horvitz, E., Kansal, A., Zhao, F.: Toward community sensing. In: 2008 International Conference on Information Processing in Sensor Networks (IPSN 2008), pp. 481–492. IEEE, Washington, DC, USA (2008). doi:10.1109/IPSN.2008.37Google Scholar
  29. Lan, K.c., Wang, H.y.: On providing incentives to collect road traffic information. In: International Wireless Communications & Mobile Computing Conference (IWCMC’13). IEEE, Washington, DC, USA (2013)Google Scholar
  30. Letts, P.: The rise of and future of crowdsourcing (2006). http://www.internetworld.co.uk/page.cfm/Link=196/ Google Scholar
  31. Lorimer, J.: Counting corncrakes: the affective science of the UK corncrake census. Soc. Stud. Sci. 38(3), 377–405 (2008). doi:10.1177/0306312707084396. http://sss.sagepub.com/cgi/doi/10.1177/0306312707084396 CrossRefGoogle Scholar
  32. Luo, T., Tham, C.K.: Fairness and social welfare in incentivizing participatory sensing. In: 2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pp. 425–433. IEEE, Washington, DC, USA (2012). doi:10.1109/SECON.2012.6275807Google Scholar
  33. Marres, N.: The issues deserve more credit: pragmatist contributions to the study of public involvement in controversy. Soc. Stud. Sci. 37(5), 759–780 (2007). doi:10.1177/0306312706077367CrossRefGoogle Scholar
  34. Massung, E., Coyle, D., Cater, K.: Using crowdsourcing to support pro-environmental community activism. In: Proceeding CHI ’13 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 371–380. ACM, New York (2013)Google Scholar
  35. Nold, C.: Bio mapping (2004). www.biomapping.net Google Scholar
  36. Nov, O., Arazy, O., Anderson, D.: Technology-mediated citizen science participation: a motivational model. In: Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, pp. 249–256 (2011)Google Scholar
  37. Paulos, E., Honicky, R.J.R., Hooker, B.: Citizen science: enabling participatory urbanism. In: Foth, M. (ed.) Handbook of Research on Urban Informatics: The Practice and Promise of the Real-Time City, pp. 414–436. Idea Group Inc, New York (2009). doi:10.1080/01944360903167661CrossRefGoogle Scholar
  38. Perkins, C.: Community mapping. Cartogr. J. 44(2), 127–137 (2007). doi:10.1179/000870407X213440CrossRefGoogle Scholar
  39. Reason, P., Torbert, W.: The action turn: toward a transformational social science. Concepts Transformation 6(1), 1–37 (2001). doi:10.1075/cat.6.1.02reaCrossRefGoogle Scholar
  40. Reddy, S., Estrin, D., Srivastava, M.: Recruitment Framework for Participatory Sensing Data Collections. In: Floreen, P., Kruger, A., Spasojevic, M. (eds.) 8th International Conference, Pervasive 2010, pp. 138–155. Springer, Berlin (2010)Google Scholar
  41. Reddy, S., Shilton, K., Burke, J., Estrin, D., Hansen, M., Srivastava, M.: Using context annotated mobility profiles to recruit data collectors in participatory sensing. In: Choudhury, T., Quigley, A., Strang, T., Suginuma, K. (eds.) 4th International Symposium on Location and Context Awareness, pp. 52–69. Springer, Berlin (2009)CrossRefGoogle Scholar
  42. Resch, B.: People as sensors and collective sensing-contextual observations complementing geo-sensor network measurements. In: Krisp, J.M. (ed.) Progress in Location-Based Services, Lecture Notes in Geoinformation and Cartography, pp. 391–406. Springer, Berlin (2013). doi:10.1007/978-3-642-34203-5Google Scholar
  43. Rotman, D., Preece, J., Hammock, J., Procita, K., Hansen, D., Parr, C., Lewis, D., Jacobs, D.: Dynamic changes in motivation in collaborative citizen-science projects. In: Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work, pp. 217–226. ACM, New York (2012)Google Scholar
  44. Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes twitter users: real-time event detection by social sensors. In: Proceeding WWW ’10 Proceedings of the 19th International Conference on World Wide Web, pp. 851–860. ACM, New York (2009)Google Scholar
  45. Shah, R.C., Roy, S., Jain, S., Brunette, W.: Data MULEs: modeling and analysis of a three-tier architecture for sparse sensor networks. Ad Hoc Netw. 1(2–3), 215–233 (2003). doi:10.1016/S1570-8705(03)00003-9CrossRefGoogle Scholar
  46. Sheth, A.: Citizen sensing, social signals, and enriching human experience. IEEE Internet Comput. 13(4), 87–92 (2009). doi:10.1109/MIC.2009.77MathSciNetCrossRefGoogle Scholar
  47. Silvertown, J.: A new dawn for citizen science. Trends Ecol. Evol. 24(9), 467–71 (2009). doi:10.1016/j.tree.2009.03.017CrossRefGoogle Scholar
  48. Srivastava, M., Abdelzaher, T., Szymanski, B.: Human-centric sensing. Philos. Trans. R. Soc. 370(1958), 176–197 (2012). doi:10.1098/rsta.2011.0244ADSMathSciNetCrossRefzbMATHGoogle Scholar
  49. Tham, C.k., Luo, T.: Quality of contributed service and market equilibrium for participatory sensing. In: 2013 IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), pp. 133–140. IEEE, Washington (2013)Google Scholar
  50. Tilak, S.: Real-world deployments of participatory sensing applications: current trends and future directions. ISRN Sens. Netw. 2013, Article ID 583165, 8 pp. (2013). doi:10.1155/2013/583165Google Scholar
  51. Tseng, Y.C., Lai, W.T., Huang, C.F., Wu, F.J.: Using mobile mules for collecting data from an isolated wireless sensor network. In: 2010 39th International Conference on Parallel Processing (ICPP), pp. 673–679. IEEE, Washington (2010). doi:10.1109/ICPP.2010.75Google Scholar
  52. Tuncay, G., Benincasa, G., Helmy, A.: Participant recruitment and data collection framework for opportunistic sensing: a comparative analysis. In: CHANTS ’13 Proceedings of the 8th ACM MobiCom Workshop on Challenged Networks, pp. 25–30. ACM, New York (2013)Google Scholar
  53. Wang, D., Abdelzaher, T., Kaplan, L., Aggarwal, C.: On quantifying the accuracy of maximum likelihood estimation of participant reliability in social sensing. In: 8th International Workshop on Data Management for Sensor Networks (DMSN 2011), pp. 7–12. ACM, Seattle (2011)Google Scholar
  54. Wu, F.J., Huang, C.F., Tseng, Y.C.: Data gathering by mobile mules in a spatially separated wireless sensor network. In: 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware, pp. 293–298. IEEE, Washington (2009). doi:10.1109/MDM.2009.43Google Scholar
  55. Wynne, B.: Misunderstood misunderstanding: social identities and public uptake of science. Public Underst. Sci. 1, 281–304 (1992). doi:10.1088/0963-6625/1/3/004CrossRefGoogle Scholar
  56. Yang, H., Zhang, J., Roe, P.: Using reputation management in participatory sensing for data classification. Procedia Comput. Sci. 5, 190–197 (2011). doi:10.1016/j.procs.2011.07.026CrossRefGoogle Scholar
  57. Yang, H., Zhang, J., Roe, P.: Reputation modelling in citizen science for environmental acoustic data analysis. Soc. Netw. Anal. Min. 3(3), 419–435 (2013). doi:10.1007/s13278-012-0087-3CrossRefGoogle Scholar
  58. Yang, S., Adeel, U., Mccann, J.A.: Selfish mules: social profit maximization in sparse sensornets using rationally-selfish human relays. IEEE J. Sel. Areas Commun. 31(6), 1124–1134 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.UCLLondonUK

Personalised recommendations