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Air pollution is routinely measured by a network of urban monitors at fixed locations across Scotland.
We considered several alternatives to the use of the Roxbury central site monitor concentrations for temporal correction, including using the other available urban monitors individually, the average concentration from all urban monitors available during each sampling period, and the mean concentration at a background monitor south of Boston (available for summer months only).
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A wide range of appealing applications can be developed with VANETs, from driving safety [2] to urban monitoring [3].
We describe three projects with different scales and purposes in the context of urban monitoring and planning, and tourism valorisation.
Data from an entire year of measurements at an urban monitoring station are analyzed, which show a large amount of scattering for seemingly identical cases.
Some examples include interdevice communication in home automation, building automation and query and control in industrial, structural, and urban monitoring [3, 8, 9].
In order to overcome these shortcomings, the United Nations has established a project of urban monitoring throughout the Global Network of Urban Observatories; Mexico joined the project in 2005.
Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies.
The model results have been compared to measurements from the Danish rural and urban monitoring networks in the paper "Performance evaluation of regional and urban air pollution forecasts" (Brandt, this issue).
In our past work, we have designed and implemented MobEyes, a middleware solution to support VSN-based urban monitoring, where agent vehicles (e.g., police cars) move around and harvest meta-data about sensed information from regular VSN-enabled vehicles.
Validation of the model results, based on the measurement dates within the urban monitoring network, confirmed that the MUKLIMO_3 micro-scale model had the capacity to simulate the main spatiotemporal patterns of thermal comfort in an urban area and its vicinity.
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