Sensing and Data-Driven Control for Smart Building and Smart City Systems

• Published in: Journal of sensors Vol. 2019; pp. 1 - 3
• Main Authors: Stamatescu, Grigore, Făgărăşan, Ioana, Sachenko, Anatoly
• Format: Journal Article
• Language: English
• Published: New York Hindawi 01.01.2019; Hindawi Limited
• Subjects: Accuracy; Actuation; Adaptive systems; Air monitoring; Air pollution; Air quality; Algorithms; Artificial intelligence; Communication; Computer simulation; Data acquisition; Data collection; Data management; Data processing; Detection; Embedded sensors; Embedded systems; Energy efficiency; Energy management; Environmental monitoring; Fourier transforms; Green buildings; Holidays & special occasions; HVAC; Internet of Things; Localization; Machine learning; Methods; Occupancy; Outdoor air quality; Relative humidity; Remote sensors; Roofs; Sensors; Smart cities; Software; Spatial resolution; Systems integration; Traffic congestion; Traffic flow; Urban environments; Ventilation; Wind speed; Wireless networks; Wireless sensor networks
• ISSN: 1687-725X; 1687-7268
• DOI: 10.1155/2019/4528034

The emergence of dense networked embedded sensor systems in monitoring and control applications has enabled the collection of data, information processing, decision, and actuation at previously unseen temporal and spatial resolution and scale. Potential topics that were initially defined include but were not limited to the following: intelligent sensors in smart building applications, for example, environmental, occupancy detection and activity tracking, air quality, safety, and energy efficiency, adaptive and distributed sensing strategies including virtual sensors, large scale monitoring systems for data collection through wireless sensor networks, data management and computational intelligence approaches for knowledge extraction from raw sensor streams, data-driven methods for modelling, simulation, and control of smart building and smart city systems, open hardware and software architectures to support complex sensor systems integration, bridging heterogeneity, and proprietary systems through standardisation. The accepted articles can be broadly grouped in clusters, which identify key current areas of research in line with the special issue topics: (i) Wireless sensor networks, including communication aspects (ii) Smart building modelling through sensor systems (iii) Machine learning algorithms for knowledge extraction from data (iv) IT infrastructure to efficiently support intensive and persistent sensing data flows. In the article titled “Design of a Smart Sensor Network System for Real-Time Air Quality Monitoring on Green Roof” by Z. Zhao et al., the authors present the design and evaluation of an embedded sensor node for PM2.5, wind speed, temperature, and relative humidity monitoring in urban environments.