Sensors data fusion for Smart Cities with KNIME : a real experience in the SmartSantander testbed

Jara, Antonio (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Genoud, Dominique (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Bocchi, Yann (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

Big Data is conceived as the powerful tool to exploit all the potential of the Internet of Things and the Smart Cities. A new dimension of understanding about the human behaviours is expected to be reached through all the gathered data in the emerging smart environment. This work analyses the data from the European Project SmartSantander. This work has correlated the traffic behaviour with respect to the temperature in the Santander City. This has been presented as the evolution of both flows present a similar behaviour. Specifically, they present a fine grain correlation of over the 57%. Finally, it has been also presented as the traffic distribution, aggregated by temperature bins, follows up a Poisson distribution model. Thereby, allowing interpolate and predict complex behaviours based on simple measures such as the temperature.


Mots-clés:
Type de conférence:
short paper
Faculté:
Economie et Services
Ecole:
HEG VS HES-SO Valais-Wallis - Haute Ecole de Gestion & Tourisme
Institut:
Institut Informatique de gestion
Classification:
Informatique
Adresse bibliogr.:
Seoul, Korea, 06-08 March 2014
Date:
Seoul, Korea
06-08 March 2014
2014
Pagination:
2 p.
Publié dans
Proceedings of the 1st IEEE World Forum on Internet of Things 2014
DOI:
ISBN:
978-1-4799-3459-1
Le document apparaît dans:

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 Notice créée le 2016-01-11, modifiée le 2018-08-31

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