Exploration of Intelligent Building Planning for Urban Renewal

Keying Han, Shitai Bao (), Meixuan She, Qixin Pan, Yina Liu and Biao Chen
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Keying Han: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Shitai Bao: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Meixuan She: College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China
Qixin Pan: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Yina Liu: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Biao Chen: Center of R&D, Augur Technology Co., Ltd., Guangzhou 510663, China

Sustainability, 2023, vol. 15, issue 5, 1-17

Abstract: The spatial layout of urban villages seriously affects the living environment and integrated development of urban and rural areas. Using digital means to assist in the reconstruction of urban villages is necessary and urgent. This study built an urban renewal framework for intelligent building planning with a proposed multi-party collaborative pattern. First, villagers’ needs, and relevant standards and regulations were merged into planning requirements, which were formulated into planning goals and criteria. With the quantitative goals and criteria, building planning and design algorithms were developed. Furthermore, the method was verified to achieve an intelligent layout of buildings. Finally, under certain conditions, the average difference between the plot ratio calculated by the program and the actual plot ratio was 0.02, and that between the building intensity calculated by the program and the actual building intensity was 0.02. Within 11.43 hectares, 500 buildings were generated with a total floor area of 27.72 hectares, and the average time taken for scheme generation was 10 s. This method can efficiently generate a plan similar to the actual floor area ratio and building density and optimize the problem of insufficient spacing. Moreover, adjusting the parameters can automatically generate a variety of schemes that can support the layout design of rural buildings.

Keywords: urban village; renewal and reconstruction; intelligent building planning; generative design (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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