Today’s cities are facing a challenge: populations are on the rise. According to Demographia, 34 urban areas now have over 10 million people. Too many of these city dwellers make their homes in slums without access to clean water, basic sanitation and other infrastructure necessities.
Cities are hard-pressed to keep up with population increases. Governments and agencies find themselves in a pinch trying to find ways to improve infrastructure, but that can be difficult without a clear idea of the issues.
Smart cities, connected by information and data, offer a solution for designers and engineers plagued by aging infrastructure—but it’s not often that entire cities are created using building information modeling (BIM).
The Virtual Singapore Project
This is precisely the type of ambitious endeavor taken on in the case of Virtual Singapore. The project, part of the Singaporean government’s “Smart Nation” initiative, will see the entire capital city of Singapore modeled in 3D.
Have a look at how it works:
The model is designed to be a collaborative platform that enables citizens, businesses, government agencies and researchers to access dynamic city data and information. The hope is that this access will facilitate the development of new tools and services to assist with current and future infrastructure issues.
Understandably, the amounts of data generated by this effort are massive. How will all of this information be stored?
Storing a Smart City’s Data
The Virtual Singapore project will see the entire city as a 3D model like the one pictured here. (Image courtesy of TODAYonline/YouTube.)
In order to store all of the information, Singapore’s National Research Foundation
decided to use the 3DEXPERIENCity platform from Dassault Systèmes
Built on the company’s 3DEXPERIENCE software, 3DEXPERIENCity is a project designed to store the 3D model of Singapore—and to incorporate various features of the habitation into a sustainable city model. This includes architecture, infrastructure, planning, resources and inhabitant patterns.
The project extends these features by using data analytics and simulations to test potential improvements and how they will affect the city and its inhabitants, much in the way a designer would test on a regular building model.
It generates this 3D model using a combination of images and data collected from various public agencies, including geometric, geospatial, topological and legacy data.
Singapore: A Model for Future Cities
In the case of many cities, the existing infrastructure was designed and built decades or even centuries ago for much smaller populations. As this disparity between population and capability increases, it can place a great amount of strain on a city’s resources—including land, water, food, energy and even clean air.
The smart city model will increase the role of digital technologies in solving infrastructure issues, including those of parking and green spaces. (Image courtesy of TODAYonline/YouTube.)
Smart cities like Singapore bring digital technologies into play to help solve urbanization issues. This includes an Internet of Things (IoT) approach, where connected objects help improve mobility, living conditions, governance and overall sustainability.
“Singapore is the most advanced city in the world in terms of leveraging technology to plan and manage its transformation over the next decades,” said Bernard Charles, president and CEO of DS.
“Cities are some of the most complex ‘products’ created by humanity,” Charles continued. “Through more efficient and accurate predictions of future experiences within these cities using state-of-the-art tools and applications, we can better anticipate national resource planning or provision of services and contribute to a more sustainable quality of life.”
“We hope to see other cities echo Singapore’s exciting example,” Charles concluded.
The Future of AEC
DS made a bold announcement at SOLIDWORKS World 2016 that the company intends to become the leader in AEC. For those more familiar with the company’s MCAD solutions, its foray into BIM may have come as something of a surprise. However, if DS’ software can model an entire city, how difficult could single buildings be?
What do you think? Does this capability for large-scale city modeling mean that a software can take the lead in AEC? Comment below.