Developing Quantum Solutions for a More Sustainable, Secure, and Resilient World

The Demand for Near Real-Time Imagery Analytics Has Never Been Greater.

As a geospatial image analytics provider, this year might just be the worst possible year in history for your customers, especially if they are insurance companies. Or federal agencies responsible for spending hundreds of billions of taxpayer dollars because extreme weather events are on the rise. Or energy companies and utilities needing to meet demand cleanly and reliably.

Extreme weather events, as well as conflicts triggered by climate change and resource security concerns, are only expected to continue to rise. Disruptions to critical infrastructure can have cascading effects through a multitude of supply chains, ultimately affecting your customers who need timely and accurate information to decide their best plan of action.

Make Better Data-Driven Decisions

So spending counts when and where it is needed most

According to data from the Federal Emergency Management Agency (FEMA), hundreds of billions of dollars were spent since 2017 to recover from extreme events. Such spending has ballooned in response to climate change-linked extreme weather events and other disruptions.

When such events happen and money must be spent, these are opportunities to rebuild with greater sustainability, security, and resilience firmly in mind. That saves more money and resources for the communities that really need it, when they need it. And when later events and needs arise, the receipt of timely and accurate imagery to aid with decisions can speed up both evacuation and response times, leading to a more positive outcome.

Introducing Quantum Modules

Containerized quantum algorithms to accelerate data processing

TerraNexum is presently seeking investment and partnering opportunities to extend our previous work toward a plug-and-play product offering for government agencies and their contractors. Our patent-pending solution: the Quantum Module (Q-Module).

Our first Q-Modules, Q-Ortho, Q-Join, and Q-Class, will be specifically designed to enhance the speed and accuracy of corresponding image processing steps that require the use of feature selection in a typical workflow. At present, these steps are bottlenecks that delay the receipt of timely, actionable information from satellite or aerial flyovers. Future Q-Modules could be mass-produced and configured for a variety of different tasks.

The quality of critical decisions that rely on timely and accurate imagery and analytics should never take a back seat to processing time and costs.

The Rewards of Quantum Advantage

WIth Q-Modules, the timeliness of returned solutions can be improved without negatively impacting quality. These are two examples from the Denver, Colorado area where Q-Modules can help you deliver on your customers' needs.

Near Real-Time Evacuation Directions

A wildfire has started in one of the riskiest areas for wildfires in the US. Might your company be able to monitor the fire in near real-time to help route evacuating traffic safely and quickly? Could you quickly find and relay safer travel options when neighborhood roads become impassable?

Your company's service offering to public safety agencies not only here, but anywhere with high wildfire risks would go a long way toward saving lives not if, but when, this happens.

Achieving Faster Emissions Reductions

What might be the most favorable mixes of sustainability, renewable energy engagements, and potential carbon capture and utilization projects needed for the City of Denver to achieve 40% emissions reduction by 2025?

This is an optimization problem. As such, it can be solved with a Q-Module designed to perform quantum optimization.

It's Time.

To learn more about Q-Modules and how your federal agency or geospatial imagery analytics company can use these to save time, money, and quite possibly even lives, contact us. We can recommend the best type of Q-Module for your particular application, and provide you with more information on when these will become available.

Patent Pending, Application #63/380,752