Abstract
The detection of vehicles in parking spaces is an important problem for the administration of large-sized parking lots. Economic reasons suggest the use of low cost and low quality magnetic sensors for this purpose. The traditional approach consists in applying thresholds to the signals for the x, y and z axes. Passing these threshold values indicates that a vehicle is located in the corresponding parking space. The literature also includes a straightforward extension of this threshold approach using fuzzy logic. The fuzzy approach described in this paper differs from the aforementioned approaches as well as other ones in the literature since it incorporates additional expert knowledge into a fuzzy rule-based decision system.
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
References
Benefits of In-Ground Vehicle Detection Sensors (n.d.). https://www.smartparking.com/technologies/in-ground-vehicle-detection-sensors
Cogneti-Tec Soluções Cognitivas em Internet das Coisas e Telemetria. http://cogneti-tec.com.br/
Barber, D.: Bayesian Reasoning and Machine Learning. Cambridge University Press, Cambridge (2012)
Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1995)
Abraham, A.: Adaptation of fuzzy inference system using neural learning, fuzzy system engineering: theory and practice. In: Nedjah, N., et al. (eds.) Studies in Fuzziness and Soft Computing, pp. 53–83. Springer, Germany (2005). https://doi.org/10.1007/11339366_3. ISBN 3-540-25322-X
Jian, Z., Hongbing, C., Jie, S., Haitao, L.: Data fusion for magnetic sensor based on fuzzy logic theory. In: 2011 Fourth International Conference on Intelligent Computation Technology and Automation, vol. 1, pp. 87–92 (2011)
Honeywell: Application Note 218 Vehicle Detection Using AMR Sensors
Caruso, M.J., Withanawasam, L.S.: Vehicle Detection and Compass Applications using AMR Magnetic Sensors, Honeywell, SSEC, 12001 State Highway 55, Plymouth, MN USA 55441
Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975)
Markevicius, V., Navikas, D., Daubaras, A., Cepenas, M., Zilys, M., Andriukaitis, D.: Vehicle influence on the earth’s magnetic field changes. Elektronika Ir Elektrotechnika 20(4), 43–48 (2014). ISSN 1392–1212
Schuster, T., Sussner, P.: An adaptive image filter based on the fuzzy transform for impulse noise reduction. Soft. Comput. 21(13), 3659–3672 (2017)
Acknowledgements
The authors would like to thank George Yoshizawa and Érick Ferdinando from the Brazilian company Cogneti-Tec [2] for providing us with this interesting problem including the data used in the experiments. This work was supported in part by CNPq under grant numbers 134611/2017-9 and 313145/2017-2.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Lopes Moura, R., Sussner, P. (2018). A Fuzzy Approach Towards Parking Space Occupancy Detection Using Low-Quality Magnetic Sensors. In: Barreto, G., Coelho, R. (eds) Fuzzy Information Processing. NAFIPS 2018. Communications in Computer and Information Science, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-95312-0_32
Download citation
DOI: https://doi.org/10.1007/978-3-319-95312-0_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-95311-3
Online ISBN: 978-3-319-95312-0
eBook Packages: Computer ScienceComputer Science (R0)