As smart city and community initiatives are implemented more and more across the country and around the world, many municipalities are embracing the use of digital twins. Digital twins enable the planning, management and optimization of cities across a range of applications, such as mobility and sustainability. Over 500 cities are expected to deploy digital twins by 2025, according to ABI research. This article explores the capabilities digital twins provide for smart cities and the central role of location in digital twins.
How does smart city technology help?
A smart city (or smart town) is a community that uses electronic means to collect data on their infrastructure, processes and operations such as utilities, mobility and infrastructure using tools like Internet of Things (IoT) sensors and IoT analytics platforms. This data is used to better manage resources, assets and services and improve operations. Ultimately, the insights afforded by this data help cities realize specific initiatives and improve the lives of their citizens.
Many cities are focusing their smart city efforts on particular projects rather than taking a general one-size-fits-all approach. As seen below, the winners of Infrastructure Canada’s Smart City Challenge are engaged in a diverse array of programs, each suited to the particular needs of the community.
- The Town of Bridgewater, Nova Scotia aims to reduce energy poverty.
- Associated Nunavut communities are working to implement preventative and protective measures to reduce the risk of suicide.
- The City of Guelph and Wellington County, Ontario’s winning initiative is to enable a circular food economy that eliminates waste and provides every resident is able to access health food.
- The City of Montreal, Quebec’s will implement a smart city initiative to increase access to food and improve mobility.
What is a digital twin?
While digital twins can be used in everything from utilities to engineering and urban planning, all share a number of key characteristics. At its core, a digital twin is a virtual representation of real-world objects, processes, behaviors and relationships—be these natural, built or both. In this way, a digital twin is more than simply a 3D model of a city although it is that as well.
The role of location in digital twins
Digital twins are a critical tool for realizing smarter cities and location is essential to digital twins. To be a faithful representation of reality, a digital twin needs data. Often, the challenge isn’t a lack of data but consolidating large volumes of many different data types, such as those provided by IoT sensors, into context. Location provides this context, threading disparate data types together into a common view.
Smarter, more connected communities provide planners with data that enables them to build scenarios and examine impacts in context and with higher fidelity than possible using traditional methods, such as physical models, spreadsheets and simple digital 3D models. IoT sensors on vehicles, for example, help planners understand how and where traffic flows. This data can be used to improve pedestrian safety along certain routes, optimize traffic flow and encourage alternative transportation in areas where such alternative forms are most viable.
Digital twins also allow planners to examine how proposed developments fit into and impact the area in which they’re situated using real-world data. For example, planners can look at the mix of residential and retail in a neighborhood and evaluate how much particular development might affect that mix and whether it is desirable. In addition, planners might use a digital twin to examine transit times between various areas within a city coupled with socioeconomic data to determine optimal locations for public services to better accommodate currently underserved citizens.
In each of these cases, location provides a context that ties together different data types, delivering a holistic and faithful representation of reality. A GIS integrates all these data into a visual, analytical system to model not only the current scenario but an aspirational one. Below, we explore real-world examples of how communities are using digital twins.
Digital twin examples
Boston – Development impacts and scenarios
In this web scene, we can see the effect that proposed developments in Boston have in terms of the shadows they cast upon a downtown park, Boston Commons. Here, urban planners in Boston are using ArcGIS Urban to incorporate different pieces of information such as building footprint and height and location, explore different scenarios and meet their objectives—in this case, limiting the shadows cast upon the park.
New York City – Vision Zero
This dashboard, put together by New York City for its Vision Zero program, shows key metrics on pedestrian safety, drawing on data provided by sources and IoT sensors such as pedestrian traffic tracking, intelligent cameras and traffic sensors incorporated into a geospatial context. This information helps public safety authorities monitor real-time traffic collisions and use predictive analytics to manage traffic flow and improve pedestrian safety.
Oshkosh, Wisconsin – Securing economic and investment opportunities
In the wake of businesses leaving the city centre, the City of Oshkosh, Wisconsin developed a plan called Imagine Oshkosh to encourage economic activity and secure investment opportunities. To develop, evaluate and communicate the Imagine Oshkosh plan, Oshkosh used ArcGIS solutions such as Business Analyst and CityEngine.
Maracaibo, Venezuela – A digital twin from a bird’s eye view down to specific buildings
Using ArcGIS Urban and related solutions such as Cityworks, Esri Venezuela and partners at the University of Zulia, developed a digital twin of Venezuela’s second largest city, Maracaibo. The digital twin incorporates a diverse array of indicators and variables such as power usage, mobility patterns, the natural physical environment as well as zoning and regulations and information on specific properties and developments. This holistic, location-based view helps to determine the impacts of different scenarios and evaluate how well plans align with public policy objectives. For example, below, we see how different factors such as proximity to medical services and public parks inform the suitability of certain areas over others for development projects.
This post was translated to French and can be viewed here.