Abstract

Moving into the third decade of the 21st century, smart cities are becoming a vital concept of advancement of the quality of life. Without any doubt, cities today can generate data of high velocity which can be used in plethora of applications. The wind flow inside a city is an area of several studies which span from pedestrian comfort and natural ventilation to wind energy yield. We propose a Visual Analytics platform based on a server-client web architecture capable of identifying areas with high wind energy potential by employing 3D technologies and Open Geospatial Consortium (OGC) standards. The assessment of a whole city or sub-regions will be supported by integrating Computational Fluid Dynamics (CFD) outcomes with historical wind sensor readings. The results, in 3D space, of such analysis could be used by a wide audience, including city planners and citizens, for locating installation points of small-scale horizontal or vertical axis wind turbines in an urban area. A case study in an urban quarter of Stuttgart is used to evaluate the interactiveness of the proposed workflow. The results show an adequate performance, although there is a lot of room for improvement in future work.

Highlights

  • A smart city may well benefit from the large amount of data collected within its boundaries

  • Visualization has emerged as a new research discipline during the last two decades [1] with Visual Analytics being the field of visualization that can provide instant and interactive knowledge to individuals by empowering a flexible control of workflow and information

  • Visual analytics can be utilized as a method to visualize the results of a Computational Fluid Dynamics (CFD) simulation or the processing of wind related data to extract meaningful information for the community (Figure 1)

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Summary

Introduction

A smart city may well benefit from the large amount of data collected within its boundaries. Visual analytics can be utilized as a method to visualize the results of a CFD simulation or the processing of wind related data to extract meaningful information for the community (Figure 1). A web-based interactive visual analysis system will enable end users to better understand simulation data and identify locations of high wind potential in a city. Such an interactive workflow can find possible locations in an urban environment where small scale wind turbines could be installed and yield an adequate amount of energy on yearly basis.

State of the Art
Architecture
System Components
Preprocessing of the Historical Wind Data
Server Side Implementation
HTTP Method
Client Side Implementation
Evaluation
Critical Review
Full Text
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