Experiences with smart city traffic pilot
|Author:||Pirttikangas, Susanna1; Gilman, Ekaterina1; Su, Xiang1;|
1Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019042613352
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2019-04-26
The infrastructure built in the City of Oulu provides rich information about the city environment and objects moving in it. We utilize this infrastructure in building an IoT system for data-intensive smart city services; by collecting data from real city environment and developing analysis methods for these data. We are building Smart City Traffic Pilot on top of the infrastructure to provide the functionality to collect the data and perform the analysis. Based on this experience, we present in this article requirements for data-intensive smart city services. Moreover, we describe four implemented use cases for utilizing rich data sources available in the smart city: situational picture, driving coach, real time reasoning, and mobile code. A lively collaboration between a large number of different actors is essential in realizing these use cases. Finally, we discuss how the use cases fulfill the requirements and the lessons we have learnt.
|Pages:||1346 - 1352|
2016 IEEE International Conference on Big Data (Big Data)
IEEE International Conference on Big Data
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported by Tekes as part of the Data to Intelligence Program of DIGILE: Finnish Strategic Centre for Science, Technology and Innovation in the field of ICT and digital business (currently DIMECC). The companies making all this possible include Infotripla (data integration), Mobisoft (moving object data), Tieto (data analytics platform), Driveco (driving data), Noptel (laser measurement data), FMI Services (weather data), Vidamin (parking data) and Dynniq (traffic signaling data). We would also want to thank the City of Oulu, Oulu Energy, Centria, Finnish Meteorological Institute, Aalto University and University of Tampere.
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