Abstract
The increase in urban population translates into denser urban traffic and, in turn, more environmental pollution. By taking advantage of the high level of sensorisation in smart cities, pollution levels can be monitored in real time, thus helping citizens to make informed decisions. In this research, we propose a healthy routing system. For this purpose, we estimate the pollution dispersion in the urban area from traffic intensity data. Then, the fastest walking route for a given trip is calculated. This route is evaluated with respect to the pollution that a pedestrian would be exposed to by completing it at a certain time. Finally, the system proposes alternative routes to avoid streets with a higher accumulation of harmful particles. The results demonstrate the feasibility of our proposal for the creation of healthy routes and, furthermore, the usefulness of the system as a real-time pollution estimator.
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Notes
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Full report can be found at https://unhabitat.org/wcr/.
- 2.
PyKrige documentation https://pykrige.readthedocs.io.
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- 4.
- 5.
Conselleria de Medi Ambient, Infraestructures i Territori. https://mediambient.gva.es/va/web/calidad-ambiental/datos-on-line.
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Acknowledgements
This work is partially funded by the Spanish Ministry of Science and Innovation under the project PID2021-123673OB-C31 and project PID2021-124975OB-I00, project TED2021-131295B-C32 from the State Research Agency, and DIGITAL2022 CLOUDAI02/S8760000 from the European Commission. Jaume Jordán is supported by the IJC2020-045683-I grant funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”.
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Nadal, S., Jordán, J., Sanchez-Anguix, V., Alberola, J.M., Julián, V., Botti, V. (2025). Optimizing Pedestrian Paths to Minimize Exposure to Urban Pollution Through Traffic Data Analysis. In: Julian, V., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2024. IDEAL 2024. Lecture Notes in Computer Science, vol 15347. Springer, Cham. https://doi.org/10.1007/978-3-031-77738-7_17
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