Abstract
Participatory sensing applications have gained popularity due to the increased use of mobile phones with embedded sensors. One of the main issues in participatory sensing applications is the uneven coverage of areas, i.e., some areas might be covered by multiple participants while there is no data for other areas. In this paper, we design mobile and web-based infrastructure to enable domain scientists to effectively acquire crowd-sensed data from specific areas of interest (AOIs) to support the goal of even coverage for data collection. Scientists can mark the AOIs on a web-portal, then volunteers will be proactively informed about the participatory sensing opportunities near their current location. We presented a caching algorithm to increase the performance of our proposed system and studied the performance of the caching algorithm for different real-world scenarios on different mobile phones. We observed that prefetching data improves the performance to some extent; however, it starts to degrade after a certain point depending upon the number of nearby AOIs.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Christin, D., Reinhardt, A., Kanhere, S.S., Hollick, M.: A survey on privacy in mobile participatory sensing applications. J. Syst. Softw. 84(11), 1928–1946 (2011)
Shilton, K., Estrin, D.: Participatory sensing and new challenges to US privacy policy
Guo, B., Yu, Z., Zhou, X., Zhang, D.: From participatory sensing to mobile crowd sensing. In: 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), pp. 593–598. IEEE (2014)
Tonekaboni, N.H., Kulkarni, S., Ramaswamy, L.: Edge-based anomalous sensor placement detection for participatory sensing of urban heat islands. In: 2018 IEEE International Smart Cities Conference (ISC2), pp. 1–8. IEEE (2018)
Ganti, R.K., Ye, F., Lei, H.: Mobile crowdsensing: current state and future challenges. IEEE Commun. Mag. 49(11), 32–39 (2011)
Kapadia, A., Kotz, D., Triandopoulos, N.: Opportunistic sensing: security challenges for the new paradigm. In: 2009 First International Communication Systems and Networks and Workshops, pp. 1–10. IEEE (2009)
Kanhere, S.S.: Participatory sensing: crowdsourcing data from mobile smartphones in urban spaces. In: Hota, C., Srimani, Pradip K. (eds.) ICDCIT 2013. LNCS, vol. 7753, pp. 19–26. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-36071-8_2
Mathur, S., et al.: Parknet: drive-by sensing of road-side parking statistics. In: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, pp. 123–136. ACM (2010)
Mohan, P., Padmanabhan, V.N., Ramjee, R.: Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, pp. 323–336. ACM (2008)
Deng, L., Cox, L.P.: Livecompare: grocery bargain hunting through participatory sensing. In: Proceedings of the 10th Workshop on Mobile Computing Systems and Applications, p. 4. ACM (2009)
Youdale, N.: Haze watch: database server and mobile applications for measuring and evaluating air pollution exposure. Electrical Engineering and Telecommunication School, University of New South Wales, Sydney, NSW, Australia, Technical report (2010)
Von Kaenel, M., Sommer, P., Wattenhofer, R.: Ikarus: large-scale participatory sensing at high altitudes. In: Proceedings of the 12th Workshop on Mobile Computing Systems and Applications, pp. 63–68. ACM (2011)
Maisonneuve, N., Stevens, M., Niessen, M.E., Steels, L.: NoiseTube: measuring and mapping noise pollution with mobile phones. In: Athanasiadis, I.N., Rizzoli, A.E., Mitkas, P.A., Gómez, J.M. (eds.) Information Technologies in Environmental Engineering. Environmental Science and Engineering. Springer, Berlin (2009). https://doi.org/10.1007/978-3-540-88351-7_16
Kanjo, E.: NoiseSPY: a real-time mobile phone platform for urban noise monitoring and mapping. Mob. Netw. Appl. 15(4), 562–574 (2010)
Kim, S., Robson, C., Zimmerman, T., Pierce, J., Haber, E.M.: Creek watch: pairing usefulness and usability for successful citizen science. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2125–2134. ACM (2011)
Ganti, R.K., Pham, N., Ahmadi, H., Nangia, S., Abdelzaher, T.F.: GreenGPS: a participatory sensing fuel-efficient maps application. In: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, pp. 151–164. ACM (2010)
Reddy, S., Parker, A., Hyman, J., Burke, J., Estrin, D., Hansen, M.: Image browsing, processing, and clustering for participatory sensing: lessons from a DietSense prototype. In: Proceedings of the 4th Workshop on Embedded Networked Sensors, pp. 13–17. ACM (2007)
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. Sens. Netw. (TOSN) 6(1), 6 (2009)
Zheng, B., Xu, J., Lee, D.L.: Cache invalidation and replacement strategies for location-dependent data in mobile environments. IEEE Trans. Comput. 51(10), 1141–1153 (2002)
Ren, Q., Dunham, M.H.: Using semantic caching to manage location dependent data in mobile computing. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, pp. 210–221. ACM (2000)
Kanjo, E., Bacon, J., Roberts, D., Landshoff, P.: MobSens: making smart phones smarter. IEEE Pervasive Comput. 8(4), 50–57 (2009)
Xu, J., Tang, X., Lee, D.L., Hu, Q.: Cache coherency in location-dependent information services for mobile environment. In: Leong, H.V., Lee, W.-C., Li, B., Yin, L. (eds.) MDA 1999. LNCS, vol. 1748, pp. 182–193. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-46669-X_16
Acknowledgment
This research has been partially funded by the National Science Foundation (NSF) under grants CCF-1442672 and SCC-1637277 and gifts from Accenture Research Labs. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF or other funding agencies and companies mentioned above.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Tonekaboni, N.H., Ramaswamy, L., Sachdev, S. (2019). A Mobile and Web-Based Approach for Targeted and Proactive Participatory Sensing. In: Wang, X., Gao, H., Iqbal, M., Min, G. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 292. Springer, Cham. https://doi.org/10.1007/978-3-030-30146-0_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-30146-0_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30145-3
Online ISBN: 978-3-030-30146-0
eBook Packages: Computer ScienceComputer Science (R0)