We also understand, if we paid attention in our high school science classes, that the sun’s heat and the wind’s movement are forms of energy. Figuring out how to harvest and distribute that latent energy is the domain of renewable energy companies.

Right now, all these companies, from established large corporations to young start-ups, are in a global race to see who will be the fastest to successfully scale customer access to affordable clean energy, anywhere in the world.

This requires a great deal of exploration because large-scale solar and wind energy projects require a lot of space, whether on land or off-shore.

Accuracy is essential, but to date not always assured.

Publicly available geo-imaging sites do not regularly update images and what images are available are in two dimensions, like a photograph. Anyone who has looked at an aerial photograph knows the limitations; important pieces of information such as land slope, elevation, and the height of buildings and vegetation are impossible to assess.

The end result is people are left planning a multi-million dollar project in a fictional environment – and that costs money.

So yes, we do solve that problem with our three-dimensional imaging but what I’m most excited about is the ability of our technology to fuse a variety of geo-specific data to create an enhanced view that provides clients with something we call situational intelligence, a form of knowledge that marries human understanding and AI analytics.

Let’s illustrate the concept of situational intelligence with a common renewable energy example: the siting of large solar projects.

As I already mentioned, solar farms need a lot of space, but finding the best commercially-viable option requires an analysis of multiple factors, most notably solar irradiance, which is a measurement of the sun’s solar energy at various points on the earth, and the distance of the proposed site from existing electrical transmission grids.

These two measures tell planners how much energy is available and amount of cable needed to connect this power source to a transmission system so it can be sold and delivered to customers.

Both of these data points are readily available, often from publicly available sources. For instance, in 2017 the World Bank created the Global Solar Atlas, which provides real-time visualization of solar irradiance, to assist with the development of solar energy.

Our technology can take this energy siting data, along with other existing geographic information systems (GIS) data such as weather information, streets, topography, buildings, other objects, terrain and spectral changes and layer it over our 3D visualizations, which itself is a fusion of air (aircraft, UAVs), space (satellites) and water (lidar, sonar) imaging sources.

This is the Terris reality.

Over the last few months we’ve been talking with energy companies and we’re about to get to work on a few projects to help lay the groundwork for renewable energy projects here in Canada and elsewhere in the world.

Reach out if you’d like to learn more about situational intelligence and the Terris system.

Not augmented reality.

Not virtual reality.

Just reality.