Abstract
It is an undeniable fact that people want information. Unfortunately, even in today’s highly automated society, a lot of the information we desire is still manually collected. An example is fuel prices where websites providing fuel price information either send their workers out to manually collect the prices or depend on volunteers manually relaying the information. This paper proposes a novel application of wireless sensor networks to automatically collect fuel prices from camera images of road-side price board (billboard) of service (or gas) stations. Our system exploits the ubiquity of mobile phones that have cameras as well as users contributing and sharing data. In our proposed system, cameras of contributing users will be automatically triggered when they get close to a service station. These images will then be processed by computer vision algorithms to extract the fuel prices. In this paper, we will describe the system architecture and present results from our computer vision algorithms. Based on 52 images, our system achieves a hit rate of 92.3% for correctly detecting the fuel price board from the image background and reads the prices correctly in 87.7% of them. To the best of our knowledge, this is the first instance of a sensor network being used for collecting consumer pricing information.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Wark, T., et al.: The design and evaluation of a mobile sensor/actuator network for autonomous animal control. In: Proceedings of Information Processing in Sensor Networks (IPSN 2007/SPOTS 2007) (April 2007)
Kim, S., Pakzad, S., Culler, D., Demmel, J., Fenves, G., Glaser, S., Turon, M.: Health monitoring of civil infrastructures using wireless sensor networks. In: 6th International Symposium on Information Processing in Sensor Networks (IPSN), April 25-27, pp. 254–263 (2007)
Lédeczi, Á., et al.: Countersniper system for urban warfare. ACM Transactions on Sensor Networks 1(2), 153–177 (2005)
Hu, W., Tran, V.N., Bulusu, N., Chou, C.T., Jha, S.: The design and evaluation of a hybrid sensor network for cane-toad monitoring. In: Proceedings of Information Processing in Sensor Networks (IPSN 2005/SPOTS 2005) (April 2005)
Baker, C.R., et al.: Wireless sensor networks for home health care. In: 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW), vol. 2, pp. 832–837 (2007)
Singhvi, V., Krause, A., Guestrin, C., James, H., Garrett, J., Matthews, H.S.: Intelligent light control using sensor networks. In: Proceedings of the 3rd international conference on Embedded networked sensor systems (SenSys), pp. 218–229. ACM, New York (2005)
Baye, M., Morgan, J., Scholten, P.: The value of information in an online consumer electronics market. Journal of Public Policy and Marketings 3, 481–507 (2003)
Brown, J., Goolsbee, A.: Does the internet make markets more competitive? Evidence from the life insurance industry. Journal of Political Economy 1, 17–25 (2002)
Chou, C.T., Bulusu, N., Kanhere, S.: Sensing data market. In: Proceedings of Poster Papers of 3rd IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS 2007) (June 2007), http://www.dcoss.org/dcoss07/dcoss07posterproceedings.pdf
Garcia, M., Sotelo, M., Gorostiza, E.: Traffic sign detection in static images using matlab. In: IEEE Conference on Emerging Technologies and Factory Automation (ETFA), September 16-19, vol. 2, pp. 212–215 (2003)
Paulo, C.F., Correia, P.L.: Automatic detection and classification of traffic signs. In: Eighth International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), June 6-8, pp. 11–11 (2007)
Bahlmann, C., Zhu, Y., Ramesh, V., Pellkofer, M., Koehler, T.: A system for traffic sign detection, tracking, and recognition using color, shape, and motion information. In: Proceedings of Intelligent Vehicles Symposium, June 6-8, pp. 255–260 (2005)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice-Hall, Englewood Cliffs (1992)
Ye, N., Borror, C.M., Parmar, D.: Scalable chi-square distance versus conventional statistical distance for process monitoring with uncorrelated data variables. Quality and Reliability Engineering International 19(6), 505–515 (2003)
Yuan, B., Kwoh, L.K., Tan, C.L.: Finding the best-fit bounding-boxes. Document Analysis Systems VII 3872/2006, 268–279 (2006)
Jenq, J.J., Li, W.: Feedforward backpropagation artificial neural networks on reconfigurable meshes. Future Generation Computer Systems 14(5-6), 313–319 (1998)
Karl, H., Willig, A.: Protocols and Architectures for Wireless Sensor Networks. Wiley, Chichester (2006)
Hull, B., Bychkovsky, V., Zhang, Y., Chen, K., Goraczko, M., Miu, A., Shih, E., Balakrishnan, H., Madden, S.: Cartel: a distributed mobile sensor computing system. In: Proceedings of the 4th international conference on Embedded networked sensor systems (SenSys), pp. 125–138. ACM, New York (2006)
Lee, U., Zhou, B., Gerla, M., Magistretti, E., Bellavista, P., Corradi, A.: Mobeyes: smart mobs for urban monitoring with a vehicular sensor network. IEEE Wireless Communications 13(5), 52–57 (2006)
Burke, J.A., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., Srivastava, M.B.: Participatory sensing. In: WSW 2006 at SenSys 2006. ACM, New York (October 31, 2006)
Paulos, E., Honicky, R., Goodman, E.: Sensing atmosphere. In: Workshop on Sensing on Everyday Mobile Phones in Support of Participatory Research (2007), http://urban.cens.ucla.edu/sensys07/index.php?title=Accepted_Papers_and_Workshop_Agenda
Eisenman, S.B., Miluzzo, E., Lane, N.D., Peterson, R.A., Ahn, G.S., Campbell, A.T.: The bikenet mobile sensing system for cyclist experience mapping. In: Proceedings of the 5th ACM International Conference on Embedded Networked Sensor Systems (SenSys 2007), pp. 87–101 (2007)
Wu, W., Chen, X., Yang, J.: Dtection of text on road signs from video. IEEE Transactions on Intelligent Transportation Systems 6, 378–390 (2005)
Chen, X., Yuille, A.: Detecting and reading text in natural scenes. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 27 June-2 July, vol. 2, pp. 366–373 (2004)
de la Escalera, A., Armingol, J., Mata, M.: Traffic sign recognition and analysis for intelligent vehicles. Image and Vision Computing 21(3), 247–258 (2003)
Jain, A., Yu, B.: Automatic text location in images and video frames. In: Fourteenth International Conference on Pattern Recognition, August 16-20, vol. 2, pp. 1497–1499 (1998)
Chen, X., Yang, J., Zhang, J., Waibel, A.: Automatic detection and recognition of signs from natural scenes. IEEE Transactions on Image Processing 13(1), 87–99 (2004)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dong, Y.F., Kanhere, S., Chou, C.T., Bulusu, N. (2008). Automatic Collection of Fuel Prices from a Network of Mobile Cameras. In: Nikoletseas, S.E., Chlebus, B.S., Johnson, D.B., Krishnamachari, B. (eds) Distributed Computing in Sensor Systems. DCOSS 2008. Lecture Notes in Computer Science, vol 5067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69170-9_10
Download citation
DOI: https://doi.org/10.1007/978-3-540-69170-9_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69169-3
Online ISBN: 978-3-540-69170-9
eBook Packages: Computer ScienceComputer Science (R0)