A Systematic Review of Urban Design and Computer Modelling Methods to Support Smart City Development in a Post-COVID Era

Abstract

The COVID-19 pandemic emphasised the need for decision-support tools to assist urban designers in building resilient and smart cities. Therefore, a multi-disciplinary systematic review was conducted following the PRISMA guideline to identify papers relevant for selecting appropriate methodologies that can be applied to build decision-support tools for resilient cities. This paper presents a list of 109 key references, selected from 8,737 records found from the searches, and identified major research themes, fundamental design interventions, and computer modelling techniques. We extracted six groups of interventions categorised by different scales of action: from an individual, crowds (social distancing and travel-related interventions), to a building, a neighbourhood/district, and a city. In addition, there are three sorts of computational modelling approaches, i.e., computer simulation, statistical models, and AI algorithms. Most of the studies developed models for predictive purposes, and 28% of the modelling studies built models for descriptive purposes. This work intends to empower urban designers and planners to overcome and get prepared for unpredictable disasters in pursuit of resilient and smart cities, particularly in the post-pandemic world. This review enables them to quickly find relevant papers as well as suitable methodologies and tools for a particular research purpose.