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Whitepaper: “Pollution Predictive Modeling in the Sustainable City”

Recently we have published the whitepaper “Pollution Predictive Modeling in the Sustainable City“, which describes in detail the approach and methodology that we have adopted within the framework of the Ciudad2020 project to perform predictive modeling of environmental pollution levels in the city of the future. Given that the starting point of the analysis is made up of the immense volume of data collected by the network of sensors deployed around the city, both physical sensors and the citizen sensor, this modeling is addressed as a data mining project (data analytics). Therefore, the methodology, techniques and algorithms typical of data mining have been used to process and exploit the information.

crispdmThe term KDD (Knowledge Discovery in Databases) was coined to refer to the (broad) concept of finding knowledge in data and to emphasize the high level application of certain data mining processes. In an attempt at normalizing this process of knowledge discovering, similarly to what it is done in software engineering for standardizing software development, two main methodologies were taken into account: SEMMA and CRISP-DM. Both fix the tasks to perform in each phase described by KDD, assigning specific tasks and defining the expected outcome for each phase. In (Azevedo, A. and Santos, M. F. KDD, SEMMA and CRISP-DM: a parallel overview. In Proceedings of the IADIS European Conference on Data Mining 2008, pp 182-185.), both implementations are compared and the conclusion is that, although you can draw a parallel between them, CRISP-DM is more complete. In fact, it takes into account also the application of outcomes to the business environment, and, for this reason, it has been adopted for modeling in Ciudad2020.

By collecting different documentary references, the whitepaper presents a detailed description of the CRISP-DM methodology, its objectives, essential phases and tasks. Then, it focuses on describing thoroughly the two application scenarios that have been considered in Ciudad2020 and the pollution modeling process carried out following this methodology: air pollution prediction in the city of Santander (Cantabria, Spain) and noise pollution prediction in the city of Madrid (Spain).

SERENA project (Spanish acronym for Neural Network Statistical Prediction System for Madrid’s Air Quality)

You can find the whitepaper, further information, more documentation and demos on our web page: If you have any questions or comments, please do not hesitate to contact us, we will be happy to assist you.

[Translation by Luca de Filippis]

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