An integrated architecture for future studies in data processing for smart cities

Data processing for Smart Cities become more challenging, facing with different handling steps: data collection from different heterogeneous sources, processing sometimes in real-time and then delivered to high level services or applications used in Smart Cities. Applications used for intelligent tr...

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Bibliographic Details
Published in:Microprocessors and microsystems 2017-07, Vol.52, p.335-342
Main Authors: Chilipirea, Cristian, Petre, Andreea-Cristina, Groza, Loredana-Marsilia, Dobre, Ciprian, Pop, Florin
Format: Article
Language:English
Subjects:
Architecture
Big Data
Crowd dynamics
Crowd sensing
Data acquisition
Data analysis
Data collection
Data processing
Data storage
Decision analysis
Intelligent transportation systems
Noise control
Real time
Scientific visualization
Support systems
Water pollution
Water resources management
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Summary:Data processing for Smart Cities become more challenging, facing with different handling steps: data collection from different heterogeneous sources, processing sometimes in real-time and then delivered to high level services or applications used in Smart Cities. Applications used for intelligent transportation systems, crowd management, water resources management, noise and air pollution management, require different data processing techniques. The main subject of this paper is to propose an architecture for data processing in Smart Cities. The architecture is oriented on the flow of data from the source to the end user. We describe seven steps of data processing: collection of data from heterogeneous sources, data normalization, data brokering, data storage, data analysis, data visualization and decision support systems. We consider two case studies on crowd management in smart cities and on Intelligent Transportation Systems (ITS) and we provide experimental highlights.
ISSN:0141-9331
1872-9436
DOI:10.1016/j.micpro.2017.03.004