Special Issue "Computer Modelling for Safer Built Environment and Smart Cities"

Submission Deadline: 01 September 2022
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Guest Editors
Prof. Rita Yi Man Li, Hong Kong Shue Yan University, China
Prof. Ramesh Agarwal, Washington University in St. Louis, USA
Prof. Xiao-Guang Yue, European University Cyprus, Cyprus

Summary

Safer built environment and smart cities have been the goal of many modern cities. The built environment includes 5 stages: urban planning, construction, occupation, demolition and renewal stage. Computer modelling aids safer urban planning by utilizing geographical information, artificial intelligence such as computer vision allows construction industry detects any risks on construction sites and demolition works. In occupation stage, property management allows camera to detect any strangers enter the buildings to enhance safety in buildings. In this special issue, we wish to shed light on the role of computer modelling in safer built environment and smart cities. Papers including but not limited to:


-Artificial intelligence modelling for construction safety
-Artificial neural network for building safety
-TinyML for built environment
-Digital Twins and computer modelling for the construction industry
-Building information modelling for safer built environment
-Smart cities modelling for safer built environment
-Smart urban planning by using computer vision modelling
-Natural Language Modelling for smart and safe cities analysis
-Ways to lower the safety risks at work in different stages of built environment
-Robot safety via computer modelling


Keywords
-Artificial Intelligence
-Built Environment
-Computer Modelling
-Information Technology
-Natural Language Processing
-Safety Science
-Smart Cities

Published Papers
  • Predicting Carpark Prices Indices in Hong Kong Using AutoML
  • Abstract The aims of this study were threefold: 1) study the research gap in carpark and price index via big data and natural language processing, 2) examine the research gap of carpark indices, and 3) construct carpark price indices via repeat sales methods and predict carpark indices via the AutoML. By researching the keyword “carpark” in Google Scholar, the largest electronic academic database that covers Web of Science and Scopus indexed articles, this study obtained 999 articles and book chapters from 1910 to 2019. It confirmed that most carpark research threw light on multi-storey carparks, management and ventilation systems, and reinforced… More
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