Abstract
Air pollution is currently a great concern especially in large cities. To reduce pollution levels, governments are imposing traffic restrictions. However, the decision about which grade of traffic restriction must be applied in a particular city zone is a cumbersome task. This decision depends on the pollution scenario occurred at a time period. To face this issue, we propose an analyzable and flexible intelligent system integrating Complex Event Processing (CEP) technology and Colored Petri Net (CPN) formalism to help domain experts to conduct such a decision-making process. This system uses a CEP engine to automatically analyze and correlate real air sensing data to detect pollutant averages at a particular sensor station. This produced information is then consumed in runtime by a CPN model in charge of obtaining the pollution scenarios, which are the basis to make decisions on the traffic regulations.
This study was funded in part by the Spanish Ministry of Science and Innovation and the European Union FEDER Funds under Grants TIN2015-65845-C3-2-R, TIN2015-65845-C3-3-R and TIN2016-81978-REDT, and also by the JCCM regional projects SBPLY/17/180501/000276/1 and SBPLY/17/180501/000276/2, both of them co-financed by the European Union FEDER Funds.
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
Notes
- 1.
Pt-arcs can also have delays associated, but this feature is not used in this paper.
- 2.
Indicated above the transition, by enclosing them in brackets.
- 3.
Available at: http://www.mambiente.madrid.es/sica/scripts/index.php.
References
CPN Tools, February 2019. http://www.cpntools.org/
Esper, February 2019. http://www.espertech.com/esper/
Event-driven Transaction Logic Inference System, February 2019. https://code.google.com/archive/p/etalis/
Boubeta-Puig, J., Díaz, G., Macià, H., Valero, V., Ortiz, G.: MEdit4CEP-CPN: an approach for complex event processing modeling by prioritized colored Petri nets. Inf. Syst. 81, 267–289 (2019). https://doi.org/10.1016/j.is.2017.11.005
Boubeta-Puig, J., Ortiz, G., Medina-Bulo, I.: MEdit4CEP: a model-driven solution for real-time decision making in SOA 2.0. Knowl.-Based Syst. 89, 97–112 (2015). https://doi.org/10.1016/j.knosys.2015.06.021
Cugola, G., Margara, A.: Processing flows of information: from data stream to complex event processing. ACM Comput. Surv. 44(3), 15:1–15:62 (2012)
Díaz, G., Macià, H., Valero, V., Boubeta-Puig, J., Cuartero, F.: An intelligent transportation system to control air pollution and road traffic in cities integrating CEP and Colored Petri Nets. Neural Comput. Appl. (in press). https://doi.org/10.1007/s00521-018-3850-1
EU Environment: Air quality standards, February 2019. http://ec.europa.eu/environment/air/quality/standards.htm
Etzion, O., Niblett, P.: Event Processing in Action, 1st edn. Manning Publications Co., Greenwich (2010)
Jensen, K., Kristensen, L.M.: Coloured Petri Nets: Modelling and Validation of Concurrent Systems, 1st edn. Springer, Heidelberg (2009). https://doi.org/10.1007/b95112
City Council of Madrid: Madrid protocol for \(NO_2\) pollution episodes, February 2019. https://www.madrid.es/UnidadesDescentralizadas/Sostenibilidad/CalidadAire/Ficheros/ProtocoloNO2AprobFinal_201809.pdf
Offel, M., van der Aa, H., Weidlich, M.: Towards net-based formal methods for complex event processing. In: Proceedings of the Conference “Lernen, Wissen, Daten, Analysen”, LWDA 2018, Mannheim, Germany, 22–24 August 2018, pp. 281–284 (2018)
van der Aalst, W.M., Stahl, C.: Modeling Business Processes - A Petri Net-Oriented Approach. Cooperative Information Systems Series. MIT Press, Cambridge (2011)
Weidlich, M., Mendling, J., Gal, A.: Net-based analysis of event processing networks – the fast flower delivery case. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 270–290. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38697-8_15
WHO: Health risk assessment of air pollution. General principles, February 2019. http://www.euro.who.int/en/health-topics/environment-and-health/air-quality/publications/2016/health-risk-assessment-of-air-pollution.-general-principles-2016
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Díaz, G., Brazález, E., Macià, H., Boubeta-Puig, J., Valero, V. (2019). An Intelligent System Integrating CEP and Colored Petri Nets for Helping in Decision Making About Pollution Scenarios. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2019. Lecture Notes in Computer Science(), vol 11506. Springer, Cham. https://doi.org/10.1007/978-3-030-20521-8_60
Download citation
DOI: https://doi.org/10.1007/978-3-030-20521-8_60
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-20520-1
Online ISBN: 978-3-030-20521-8
eBook Packages: Computer ScienceComputer Science (R0)