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

• Published in: Microprocessors and microsystems Vol. 52; pp. 335 - 342
• Main Authors: Chilipirea, Cristian, Petre, Andreea-Cristina, Groza, Loredana-Marsilia, Dobre, Ciprian, Pop, Florin
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 01.07.2017; Elsevier BV
• 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; Crowd dynamics; Data processing; Big data; Architecture; Crowd sensing; Intelligent transportation systems
• ISSN: 0141-9331; 1872-9436
• DOI: 10.1016/j.micpro.2017.03.004

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.