Big data in smart cities : from poisson to human dynamics

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. Historically several of the human-related behaviours have been modelled with Poisson distribution, but a new dimension of understanding about the human behaviours is 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. 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. At the same time, this data presents a burst behaviour (human dynamics), when the data is analysed in sequence, instead of aggregated by temperature bins. Therefore, this work concludes that human-related behaviours can be described with both, Poisson and Human Dynamics distribution, depending on how the data is represented and aggregated.


Keywords:
Conference Type:
full paper
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Publisher:
Gwangju, South Korea, 13-16 May 2015
Date:
Gwangju, South Korea
13-16 May 2015
2014
Pagination:
6 p.
Published in:
Proceedings of the 28th International Conference on Advanced Information Networking and Applications Workshops 2014
DOI:
ISSN:
978-1-4799-2652-7
External resources:
Appears in Collection:



 Record created 2015-11-14, last modified 2019-11-28

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