Making Smart City More Efficient, Robust and Even Smarter with Digital Twin

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8.45 am to 10.15 am Singapore Standard Time, GMT +8

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Making Smart City Systems More Efficient, Robust and Even Smarter with Digital Twin

As Artificial Intelligent and Machine Learning in the automation process mature, the public sector can bridge the physical and digital with autonomous infrastructure to connect businesses, citizens, and public services together

Smart city developments across the globe are anticipated to increase in the next several years with the pandemic accelerating the need and regulatory bodies becoming hyper-focused on monitoring the health and safety of citizens.

Considered the future of urban living, the digital twin gives smart city planners a tool to help make this safe, clean, sustainable vision into a reality. This virtual replica provides a digital representation of urban networks and systems within a city, such as power grids, roads, traffic and safety monitoring which makes use of real data obtained from the monitoring devices within the city.

Initially developed to aggregate, analyse and visualise complex information for manufacturing and construction industries, digital twins are increasingly being used as a tool by cities. They are simply a more efficient and effective way to plan and manage a city.

The Digital Twin concept is set to play an increasingly important role in the creation of smart cities around the world and in addressing issues related to urban living. Bringing the virtual and physical worlds together allows public sector agencies, businesses and researchers to experiment and simulate different scenarios, and build a more resilient city.

For example, the NSW Department of Customer Service’s Spatial Services division is making the state government’s Digital Twin available to assist emergency services in developing effective emergency management strategies.

Singapore, too, has been proactive in its plans to become a “Smart Nation,” with the government announcing the Smart Nation initiative in 2014 and invested $73 million in “Virtual Singapore” project – a digital three-dimensional city model and collaborative data platform.

Digital Twin as an Enabler to Smart Cities

The digital twin has gained its momentum as Artificial Intelligence (AI) and Machine Learning (ML) revolutionises inference, prediction and decision-making tasks, and also as barriers to collecting and processing massive volumes of data are falling away.

Smart cities are driven by data at their core. Data integration and visualisation from across the urban space are of paramount importance to connect businesses, citizens, and public services with autonomous infrastructure.

In essence, the digital twin has to be the hub for all the real-time data being captured within the smart city - GPS data from public transportation, weather data, the level of air pollution, natural disaster, or even the number of people visiting a tourist hub.

Data flowing from the physical asset to the digital twin can be leveraged using AI and ML to provide the actionable insights and better decision-making results in interventions.

With Machine Learning, virtual models can be created based on observed behaviour and historical data rather than the design information alone. Historical asset data and real-time data readings from multiple assets are utilised to detect anomalies and make failure predictions, preventing unplanned downtime.

Therefore, applying analytics at every step of the data exchange between the physical and digital is the key for digital twin.

Enhanced Delivery of Digital Twin

In order to successfully interact with the built environments and scale-up a digital twin, it is critical to have a centralised point of control and a unified view of all the data sets and processes across the entire digital ecosystem.

A single common data environment (CDE) unlocks new levels of visibility, coordination, and productivity across people and processes as it supports in design, build and operations across the lifecycle and supply chain.

Essentially, to leverage AI, IoT, ML and Analytic into the process and deliver exceptional citizen-centric services, a robust and secure cloud platform is required.

This then begs the question: how can the public sector successfully implement digital twin to improve the efficiency of its smart city developments and services, and also mitigate IT constraints?

OpenGov Asia is pleased to invite you to an exclusive OpenGovLive! Virtual Breakfast Insight aimed at imparting knowledge on smart city adoption at scale with a digital twin in the public sector and best practices to improve data analytics in the automation process, scalability and service delivery levels and security.

This session serves as a great peer-to-peer learning platform to gain insights and practical solutions to implement digital twin to enable more efficient, robust, and smarter infrastructure and smart city systems.

We will be discussing:

  • Key challenges posed by digital twin deployment including legacy compatibility issues, sources of scalability cost, complexity, and strategies to overcome them
  • Different approaches to using AI and ML to efficiently operate and scale based on the current needs and types of operation
  • Mitigating risks through the use of advanced technologies
  • Opportunities for cloud migration and predictive intelligence
  • Building a platform for elastic scalability across decentralised services
  • Strengthening citizen experience through the expanded use of digital twin


  • Chief Digital Officers
  • Chief Data Officers
  • Chief Information Officers
  • Chief Operating Officers
  • Chief Technology Officers
  • Chief Transformation Officers
  • Heads of Application
  • Heads of Transformation
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