The digital twin concept and the urban modelling paradigm, more generally, are transforming how cities are designed, monitored, and managed.
They allow optimising the holistic performance of cities across verticals in terms of energy management, mobility, resilience, sustainability, and economic growth. Digital twins combine spatial modelling of the urban built environment, modelling of electrical and mechanical systems based on mathematical descriptions or deep learning informed training, and real-time sensor data derived from IoT platform solutions. The installed base of deployments is expected to grow from just a handful of early implementations in 2019 to more than 500 by 2025, according to global tech market advisory firm, ABI Research.
“Originally developed for industrial systems, the digital twin concept is now spreading to the smart cities environment,” says Dominique Bonte, vice president end markets at ABI Research. “However, it won’t be a single Uber-like digital twin for an entire city but rather an aggregation and integration of domain-specific digital twins for systems like smart buildings, traffic infrastructure, energy grids, and water management.”
Key use cases across verticals include the simulation of people movements and emergency evacuations, modelling of flooding risks, smart building design and energy management via occupancy tracking, road traffic modelling and simulation, air quality monitoring and prediction, modelling of green infrastructure and circular urban economies, and cyber threat analysis.
The benefits of modelling are numerous and range from preventive maintenance to operational efficiencies and cost savings, improved services for citizens, increased safety and security and the inherent possibility of automated generative design, for example allowing maximising solar energy exposure of entire neighbourhoods.
Technology suppliers of urban modelling solutions include the big 3 – Microsoft, Siemens, and Dassault Systemes – next to smaller providers like IES, Bentley Systems, and CityZenith. Cities having deployed digital twins to date include Newcastle, Rotterdam, Boston, New York, Singapore, Stockholm, Helsinki, Jaipur, and Amaravati.
However, challenges for adoption remain, mainly related to the complexity of city-wide modelling and the lack of standards supporting cross-vertical data exchange. Other inhibitors include the little awareness about benefits and ROI, commercialisation challenges related to the siloed organisation structure of city governments, and concerns about consumer privacy and cyber threats.
Despite the challenges, it is quite clear urban modelling and digital twins, in particular, form the end game of the smart cities journey to optimised design and the ultra-efficient operation of entire cities. “Just adding a thin layer of IoT tech on top of legacy infrastructure will no longer suffice to address the multiple challenges cities will face in the future,” Bonte concludes.
These findings are from ABI Research’s Digital Twins in Smart Cities and Urban Modelling application analysis report. This report is part of the company’s Smart Cities and Smart Spaces research service, which includes research, data, and analyst insights. Based on extensive primary interviews, application analysis reports present in-depth analysis on key market trends and factors for a specific technology.
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