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Spatio-Temporal Analysis for Smart City Data

Bermudez-Edo, M and Barnaghi, Payam (2018) Spatio-Temporal Analysis for Smart City Data In: WebConf 2018, Web Streaming Workshop, 23 - 27 April 2018, Lyon, France.

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Abstract

The data gathered from smart cities can help citizens and city manager planners know where and when they should be aware of the repercussions regarding events happening in different parts of the city. Most of the smart city data analysis solutions are focused on the events and occurrences of the city as a whole, making it difficult to discern the exact place and time of the consequences of a particular event. We propose a novel method to model the events in a city in space and time. We apply our methodology for vehicular traffic data basing our models in (convolutional) neuronal networks.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Bermudez-Edo, M
Barnaghi, PayamP.Barnaghi@surrey.ac.uk
Date : April 2018
Identification Number : 10.1145/3184558.3191649
Copyright Disclaimer : © 2018 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC BY 4.0 License.
Uncontrolled Keywords : Spatio-Temporal analysis; Deep Learning; Smart cities; Internet of Things; Neuronal Networks
Depositing User : Melanie Hughes
Date Deposited : 09 Mar 2018 11:15
Last Modified : 30 May 2018 13:58
URI: http://epubs.surrey.ac.uk/id/eprint/845970

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