論文

査読有り
2016年

Automatic Generation of 3D House Models with Solar Photovoltaic Generation for Smart City

2016 3RD MEC INTERNATIONAL CONFERENCE ON BIG DATA AND SMART CITY (ICBDSC)
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回数 : 224
  • Kenichi Sugihara
  • ,
  • Zhenjiang Shen

開始ページ
337
終了ページ
343
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/ICBDSC.2016.7460391
出版者・発行元
IEEE

City models by 3D CG (Computer Graphics) are important in promoting public participation for smart city, which will use solar photovoltaic (PV) generation. But, creating city models are labor intensive. In order to automate laborious steps, we proposed new technology by integration of a GIS (Geographic Information System) and CG. The proposed integrated system automatically generates 3D building models, based on building polygons or building footprints on digital maps, which show most building polygons' edges meet at right angles (orthogonal polygon). A complicated orthogonal polygon can be partitioned into a set of rectangles. The proposed integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In this paper, we propose to automatically generate 3D building models topped with double shed roofs attached by PV arrays. The sizes and positions, slopes of roof boards and under roof constructions are made clear by designing the top view and side view of a double shed roof house. For the application example of the developed system, we simulate the solar photovoltaic generation change of a city block by performing land readjustment and changing shape of buildings, that is, ordinary roof house or double shed roof house suitable for greater PV generation. Our simulation reveals that double shed roof houses have greatly improved the solar photovoltaic generation.

リンク情報
DOI
https://doi.org/10.1109/ICBDSC.2016.7460391
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000382689100059&DestApp=WOS_CPL
ID情報
  • DOI : 10.1109/ICBDSC.2016.7460391
  • Web of Science ID : WOS:000382689100059

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