Mobile Networks and Applications

, Volume 21, Issue 2, pp 375–385 | Cite as

Intelligent Sensing for Citizen Science

Challenges and Future Directions
  • Michael J. O’Grady
  • Conor Muldoon
  • Dominic Carr
  • Jie Wan
  • Barnard Kroon
  • Gregory M. P. O’Hare


Interest in Citizen Science has grown significantly over the last decade. Much of this interest can be traced to the provision of sophisticated platforms that enable seamless collaboration, cooperation and coordination between professional and amateur scientists. In terms of field research, smart-phones have been widely adopted, automating data collection and enriching observations with photographs, sound recordings and GPS coordinates using embedded sensors hosted on the device itself. Interaction with external sensor platforms such as those normally used in the environmental monitoring domain is practically null-existent. Remedying this deficiency would have positive ramifications for both the professional and citizen science communities. To illustrate the relevant issues, this paper considers a common problem, that of data collection in sparse sensor networks, and proposes a practical solution that would enable citizen scientists act as Human Relays thus facilitating the collection of data from such networks. Broader issues necessary for enabling intelligent sensing using common smart-phones and embedded sensing technologies are then discussed.


Citizen science Mobile sensing Human relays Data mules 



This work is supported by the EU FP7 ENV.2012.6.5-1 programme under grant number 308513. The support of the COBWEB consortium is gratefully acknowledged.


  1. 1.
    Aberer K, Hauswirth M, Salehi A (2006) Global Sensor Networks. In: School Comput. Commun. Sci., Ecole Polytechnique Federale de Lausanne. EPFL, LausanneGoogle Scholar
  2. 2.
    Anastasi G, Conti M, Di Francesco M (2008) Data collection in sensor networks with data mules: An integrated simulation analysis. In: IEEE Symposium on Computers and Communications, 2008. ISCC 2008. IEEE, pp 1096–1102Google Scholar
  3. 3.
    Arnaboldi V, Conti M, Delmastro F, Minutiello G, Ricci L (2013) Sensor mobile enablement (sme): A light-weight standard for opportunistic sensing services. In: 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). IEEE, pp 236–241Google Scholar
  4. 4.
    Bhadauria D, Tekdas O, Isler V (2011) Robotic data mules for collecting data over sparse sensor fields. J Field Rob 28(3):388–404CrossRefMATHGoogle Scholar
  5. 5.
    Bonney R, Shirk JL, Phillips TB, Wiggins A, Ballard HL, Miller-Rushing AJ, Parrish JK (2014) Next steps for citizen science. Science 343(6178):1436–1437CrossRefGoogle Scholar
  6. 6.
    Botts M, Robin A (2007) OpenGIS sensor model language (SensorML) implementation specification. OpenGIS Implementation Specification OGC pp. 07–000Google Scholar
  7. 7.
    Bröring A, Echterhoff J, Jirka S, Simonis I, Everding T, Stasch C, Liang S, Lemmens R (2011) New generation sensor web enablement. Sensors 11(3):2652–2699CrossRefGoogle Scholar
  8. 8.
    Burggraf DS (2006) Geography markup language. Data Sci J 5:178–204CrossRefGoogle Scholar
  9. 9.
    Cañete E, Chen J, Díaz M, Llopis L, Reyna A, Rubio B (2015) Using wireless sensor networks and trains as data mules to monitor slab track infrastructures. Sensors 15(7):15,101–15,126CrossRefGoogle Scholar
  10. 10.
    Carr D, O’Grady MJ, O’Hare GMP, Collier RW (2013) SIXTH: a middleware for supporting ubiquitous sensing in personal health monitoring. In: Godara B, Nikita K (eds) Wireless Mobile Communication and Healthcare, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 61. Springer, Berlin Heidelberg, pp 421–428Google Scholar
  11. 11.
    Catlin-Groves CL (2012) The citizen science landscape: from volunteers to citizen sensors and beyond. International Journal of ZoologyGoogle Scholar
  12. 12.
    Cifelli R, Doesken N, Kennedy P, Carey LD, Rutledge SA, Gimmestad C, Depue T (2005) The community collaborative rain, hail, and snow network: informal education for scientists and citizens. Bull Am Meteorol Soc 86(8):1069–1077CrossRefGoogle Scholar
  13. 13.
    Dalmasso I, Datta SK, Bonnet C, Nikaein N (2013) Survey, comparison and evaluation of cross platform mobile application development tools. In: 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, pp 323–328Google Scholar
  14. 14.
    Di Francesco M, Das SK, Anastasi G (2011) Data collection in wireless sensor networks with mobile elements: A survey. ACM Transactions on Sensor Networks (TOSN) 8(1):7:1–7:31CrossRefGoogle Scholar
  15. 15.
    Gallo DS, Cardonha C, Avegliano P, Carvalho TC (2014) Taxonomy of citizen sensing for intelligent urban infrastructures. IEEE Sensors J 14(12):4154–4164CrossRefGoogle Scholar
  16. 16.
    Ganti RK, Ye F, Lei H (2011) Mobile crowdsensing: current state and future challenges. IEEE Commun Mag 49(11):32–39CrossRefGoogle Scholar
  17. 17.
    Goldman J, Shilton K, Burke J, Estrin D, Hansen M, Ramanathan N, Reddy S, Samanta V, Srivastava M, West R (2009) Participatory sensing: A citizen-powered approach to illuminating the patterns that shape our world. Foresight & Governance Project, White Paper, pp. 1–15Google Scholar
  18. 18.
    Gorgu L, Kroon B, Campbell AG, O’Hare GMP (2013) Enabling a mobile, dynamic and heterogeneous discovery service in a sensor web by using AndroSIXTH. In: Augusto JC, Wichert R, Collier R, Keyson D, Salah AA, Tan AH (eds) Ambient Intelligence, Lecture Notes in Computer Science, vol 8309. Springer International Publishing, pp 287–292Google Scholar
  19. 19.
    Gu Y, Ren F, Ji Y, Li J (2015) The evolution of sink mobility management in wireless sensor networks: A survey. IEEE Commun Surv Tutorials. doi: 10.1109/COMST.2015.2388779 Google Scholar
  20. 20.
    Guo B, Wang Z, Yu Z, Wang Y, Yen NY, Huang R, Zhou X (2015) Mobile crowd sensing and computing: The review of an emerging human-powered sensing paradigm. ACM Comput Surv (CSUR) 48(1):7CrossRefGoogle Scholar
  21. 21.
    Hartung C, Lerer A, Anokwa Y, Tseng C, Brunette W, Borriello G (2010) Open data kit: tools to build information services for developing regions. In: Proceedings of the 4th ACM/IEEE International Conference on Information and Communication Technologies and Development. ACM, p 18Google Scholar
  22. 22.
    Heggen S, Adagale A, Payton J (2014) Lowering the barrier for crowdsensing application development. In: Mobile Computing, Applications, and Services. Springer, pp 1–18Google Scholar
  23. 23.
    Herodotou C, Villasclaras-Fernández E, Sharples M (2014) The Design and Evaluation of a Sensor-Based Mobile Application for Citizen Inquiry Science Investigations. In: Open Learning and Teaching in Educational Communities. Springer, pp 434–439Google Scholar
  24. 24.
    Ho DT, Grøtli EI, Sujit P, Johansen T.A, Sousa JB (2015) Optimization of wireless sensor network and uav data acquisition. J Intell Robot Syst 78(1):159–179CrossRefGoogle Scholar
  25. 25.
    Hosseini M, Shahri A, Phalp K, Taylor J, Ali R (2015) Crowdsourcing: A taxonomy and systematic mapping study. Computer Science Review 17Google Scholar
  26. 26.
    Joy K, Crawford I, Grindrod P, Lintott C, Bamford S, Smith A, Cook A, Zoo M (2011) Moon Zoo: citizen science in lunar exploration. Astron Geophys 52(2):2–10CrossRefGoogle Scholar
  27. 27.
    Khan WZ, Xiang Y, Aalsalem MY, Arshad Q (2013) Mobile phone sensing systems: A survey. IEEE Commun Surv Tutorials 15(1):402–427CrossRefGoogle Scholar
  28. 28.
    Kim J, Lee JW (2014) OpenIoT: An open service framework for the internet of things. In: 2014 IEEE World Forum on Internet of Things (WF-IoT). IEEE, pp 89–93Google Scholar
  29. 29.
    Kim S, Mankoff J, Paulos E (2013) Sensr: evaluating a flexible framework for authoring mobile data-collection tools for citizen science. In: Proceedings of the 2013 conference on Computer supported cooperative work. ACM, pp 1453– 1462Google Scholar
  30. 30.
    Lane ND, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell AT (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140–150CrossRefGoogle Scholar
  31. 31.
    Li Y, Bartos R (2014) A survey of protocols for intermittently connected delay-tolerant wireless sensor networks. J Netw Comput Appl 41:411–423CrossRefGoogle Scholar
  32. 32.
    Liang Q, Cheng X, Chen D (2011) Opportunistic sensing in wireless sensor networks: theory and application. In: 2011 IEEE Global Telecommunications Conference (GLOBECOM 2011). IEEE, pp 1–5Google Scholar
  33. 33.
    Lillis D, Russell SE, Carr D, Collier RW, O’Hare GMP (2013) Intelligent decision-making in the physical environment. In: Augusto JC, Wichert R, Collier R, Keyson D, Salah AA, Tan AH (eds) Ambient Intelligence, Lecture Notes in Computer Science, vol 8309. Springer International Publishing, pp 235– 240Google Scholar
  34. 34.
    Louvel J, Templier T, Boileau T (2012) Restlet in Action: Developing RESTful Web APIs in Java. Manning Publications CoGoogle Scholar
  35. 35.
    Ma H, Zhao D, Yuan P (2014) Opportunities in mobile crowd sensing. IEEE Commun Mag 52(8):29–35CrossRefGoogle Scholar
  36. 36.
    Michael Illingworth S, Louise Muller C, Graves R, Chapman L (2014) Uk citizen rainfall network: a pilot study. Weather 69(8):203–207CrossRefGoogle Scholar
  37. 37.
    Miller-Rushing A, Primack R, Bonney R (2012) The history of public participation in ecological research. Front Ecol Environ 10(6):285–290CrossRefGoogle Scholar
  38. 38.
    Na A, Priest M (2006) OpenGIS sensor observation service implementation specification. Open Geospatial Consortium Implementation Specification 91Google Scholar
  39. 39.
    O’Hare GMP, Muldoon C, O’ Grady MJ, Collier RW, Murdoch O, Carr D (2012) Sensor web interaction. International Journal on Artificial Intelligence Tools 21(2)Google Scholar
  40. 40.
    Park U, Heidemann J (2011) Data muling with mobile phones for sensornets. In: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems. ACM, pp 162– 175Google Scholar
  41. 41.
    Parr CS, Jones T, Songer NB (2002) Cybertracker in biokids: Customization of a pda-based scientific data collection application for inquiry learning. In: Proceedings Fifth International Conference of Learning Sciences (ICLS), pp. 574–575Google Scholar
  42. 42.
    Perera C, Jayaraman PP, Zaslavsky A, Christen P, Georgakopoulos D (2014) MOSDEN: An internet of things middleware for resource constrained mobile devices. In: 2014 47th Hawaii International Conference on System Sciences (HICSS). IEEE, pp 1053–1062Google Scholar
  43. 43.
    Pinto A, Thompson K, Jones C, Clow D (2014) ispot: your place to share nature. In: Carvalho L, Goodyear P (eds) The Architecture of Productive Learning Networks. Routledge, Abingdon, pp 225–238Google Scholar
  44. 44.
    Raddick MJ, Bracey G, Gay PL, Lintott CJ, Murray P, Schawinski K, Szalay AS, Vandenberg J (2010) Galaxy zoo: Exploring the motivations of citizen science volunteers. Astron Educ Rev 9(1)Google Scholar
  45. 45.
    Reed J, Rodriguez W, Rickhoff A (2012) A Framework for Defining and Describing Key Design Features of Virtual Citizen Science Projects. In: Proceedings of the 2012 iConference, iConference ’12. ACM, New York, pp 623–625CrossRefGoogle Scholar
  46. 46.
    Scanlon E, Woods W, Clow D (2014) Informal Participation in Science in the UK: Identification, Location and Mobility with iSpot. Journal of Educational Technology and Society 17(2):58–71Google Scholar
  47. 47.
    Smith AM, Lynn S, Lintott CJ (2013) An introduction to the zooniverse. In: First AAAI Conference on Human Computation and CrowdsourcingGoogle Scholar
  48. 48.
    Soares JM, Franceschinis M, Rocha RM, Zhang W, Spirito MA (2011) Opportunistic data collection in sparse wireless sensor networks. EURASIP J Wirel Commun Netw 2011:6CrossRefGoogle Scholar
  49. 49.
    Tanenbaum AS, Gamage C, Crispo B (2006) Taking sensor networks from the lab to the jungle. IEEE Computer 39(8):98–100CrossRefGoogle Scholar
  50. 50.
    Viani F, Robol F, Polo A, Rocca P, Oliveri G, Massa A (2013) Wireless architectures for heterogeneous sensing in smart home applications: Concepts and real implementation. Proc IEEE 101(11):2381–2396CrossRefGoogle Scholar
  51. 51.
    Vlissides J, Helm R, Johnson R, Gamma E (1995) Design patterns: Elements of reusable object-oriented software, vol 49. Addison-WesleyGoogle Scholar
  52. 52.
    Wang J, Wang Y, Wang H (2014) Psafactory: An end-user programming tool for building participatory sensing applications. In: 2014 IEEE International Conference on Global Software Engineeering Workshops (ICGSEW). IEEE, pp 39–44Google Scholar
  53. 53.
    Wang MM, Cao JN, Li J, Dasi SK (2008) Middleware for wireless sensor networks: A survey. J Comput Sci Technol 23(3):305– 326CrossRefGoogle Scholar
  54. 54.
    Weng YH, Sun FS, Grigsby JD (2012) GeoTools: An Android phone application in Geology. Comput Geol 44:24–30CrossRefGoogle Scholar
  55. 55.
    Wiggins A (2013) Free as in puppies: compensating for ICT constraints in citizen science. In: Proceedings of the 2013 conference on Computer supported cooperative work. ACM, pp 1469– 1480Google Scholar
  56. 56.
    Wiggins A, Crowston K (2014) Surveying the citizen science landscape. First Monday 20(1)Google Scholar
  57. 57.
    Willocx M, Vossaert J, Naessens V (2015) A quantitative assessment of performance in mobile app development tools. In: 2015 IEEE International Conference on Mobile Services (MS). IEEE, pp 454–461Google Scholar
  58. 58.
    Wolber D, Abelson H, Spertus E, Looney L (2011) App Inventor. O’Reilly Media Inc.”Google Scholar
  59. 59.
    Wu X, Brown KN, Sreenan CJ (2013) Analysis of smartphone user mobility traces for opportunistic data collection in wireless sensor networks. Pervasive Mob Comput 9(6):881–891CrossRefGoogle Scholar
  60. 60.
    Yang S, Adeel U, McCann J (2013) Selfish mules: Social profit maximization in sparse sensornets using rationally-selfish human relays. IEEE J Sel Areas Commun 31(6):1124–1134CrossRefGoogle Scholar
  61. 61.
    Zachariah T, Klugman N, Campbell B, Adkins J, Jackson N, Dutta P (2015) The internet of things has a gateway problem. In: Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications. ACM, pp 27– 32Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Michael J. O’Grady
    • 1
  • Conor Muldoon
    • 1
  • Dominic Carr
    • 2
  • Jie Wan
    • 3
  • Barnard Kroon
    • 1
  • Gregory M. P. O’Hare
    • 4
  1. 1.School of Computer ScienceUniversity College DublinDublin 4Ireland
  2. 2.School of ComputingNational College of IrelandDublinIreland
  3. 3.Schools of Computer Science and TechniquesNantong UniversityJiangsuChina
  4. 4.Earth Institute and School of Computer ScienceUniversity College DublinDublin 4Ireland

Personalised recommendations