Disruption as a Catalyst for Innovation
RUNWITHIT (RWI) Synthetics moves beyond the static, built environments of digital twins into the next logical step forward.
Progressing beyond the built environment involves integrating twin technology with agentic and heterogeneous modelled environments, creating a six-dimensional space that includes time, context, and people.
We are not simply looking at the future of place but at the emergent future behaviour of people in their environment, encompassing economic, psychological, social, and physical contexts, which opens up innumerable applications.
For example, we’ve recently applied our Synthetic Twin technology to analyze electrification in the face of climate change and other regional conditions.
Synthetic Twins are valuable for decision-makers, leaders, and stakeholders due to the unprecedented nature of the immediate and long-term future.
Tomorrow is Not Like Yesterday
Understanding context and incorporating the human element is vital to all decisions, from calculating infrastructure investments to designing engineering projects to community building and social health initiatives. We can make things previously invisible within these systems visible, allowing them to be quantified, measured, and considered.
Moreover, having a “third space” where decision-makers and stakeholders can collaborate, de-silo specialized knowledge, and engage with one another in a converged data environment is critical to facilitating resilience building in the face of highly complex problems.
A Synthetic Twin or Synthetic City begins with a geospatial and object-oriented perspective of the Earth and its regions, with dimensions of time, context, and people added in.
We accomplish this by including interconnected models that are appropriate and contextual to the entities we include within any given Synthetic Environment. They range from physical systems to statistical or probabilistic models to programmatic models. Connecting these models, ranging from the simple to the complex, enables us not only to system-see but also to system-solve.
That is, we can step back and examine the interplay between data sets, whether anecdotal or research-based, along with adjustable trends and manipulable forecasts, allowing us to make operations visual, configurable, and inflectable.
The Air We Breathe
We’ve generated a Synthetic Twin of Edmonton, Alberta, a city in the prairies of Western Canada, where summer wildfires are considered both acute and chronic climate events and have become a significant part of Albertans' lives.
We know it’s changing their relationship with various services, the environment, and public health.
In previous case studies, we’ve used our Synthetic Twin of the Edmonton Metropolitan Region to examine not only the health and economic impacts of particulate matter (PM2.5)—the tiny, often carcinogenic particles found within wildfire smoke—but also how best to geolocate and utilize mitigation methods to protect vulnerable populations.
However, for this case study, we will demonstrate how acute and chronic summer wildfires are changing the relationship between the population and energy, specifically how households consume energy in response to temperature and air quality.
Manipulatable Scenarios for Dynamic Forecasting
Let’s start by setting the stage for electrification in Synthetic Calgary, a city in Southern Alberta. We have a Synthetic Population and Synthetic Households across 44 Calgary neighbourhoods. We have 27 data points per household, which allow us to view their carbon footprint, income, energy use and consumption through extremely detailed lenses.
We can see whether an individual household is sensitive to time-of-day pricing or whether it is likely to leave its air conditioning on while its members are away at work.
We’ve created an inflectable world and can now sandbox scenarios within it. We can adjust knobs and levers and, through our synthetic modelling, see how households would react to factors such as electric vehicle or solar adoption rates, outside temperature, and the city’s base load curve. We can even include psychographics for the members of a household, integrating attitudes towards solar energy or EV adoption. These Synthetic People can adapt in response to the situations and environmental changes we might introduce.
This is highly significant. How people perceive energy influences their consumption of it, and individual psychographics may vary significantly depending on where grid impacts are felt or how technology adoption evolves.
Unveiling the Toxic Evolution of Wildfire Smoke
By converging this model of Synthetic Calgary with our work on wildfire and PM 2.5, we can begin to systematize and examine the interplay between electrification and wildfire smoke.
Wildfire particulate matter presents an extraordinary air quality issue, meaning that indoor air quality becomes increasingly valuable as smoke particles outdoors become increasingly threatening to both short-term and long-term health.
Wildfire smoke is likely to coincide with heat events in the summer, when air-cooling and conditioning use is highest.
We can start to ask important questions within our sandbox that converge these vital subjects: How effective are building envelopes of different ages? What technologies are adding the most to load curves? How does the population, given their demographics and psychographics, consume different technologies?
Dialling forward, we know the number of heat events every summer is projected to increase by three times. While air conditioning hasn’t previously been adopted in a significant way, it has now become a critical measure, with an increased likelihood of individuals confined to their homes during both heat and wildfire smoke events, where opening windows is not an option. This is going to have a significant effect on energy consumption and base load.
Solution Sandboxing for the Unprecedented
Our Synthetic Twin is not limited to electrification scenarios. As mentioned, we’ve used this same approach in these Synthetic Twins to examine where health facilities should be located and how people access them.
Moreover, we’ve demonstrated where air quality sensors, devices, and investments in sensor technology are today and where they need to be to address the community's health impacts.
Beyond regions local to us, we’ve created Synthetic Twins across the globe, having recently launched Synthetic Earth, a living, agentic AI and data model of our planet.
It’s the first of its kind — never before has generative AI, agentic AI, super-scale in-memory data handling and VR visualization been combined.
We’re pushing the boundary of what twins are capable of by moving beyond the static and towards inflectable, 6D twins with applications leading communities, regions, and industries towards a visibly better future.