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[ BECAUSE ENVIRONMENTAL
SUSTAINABILITY REQUIRES
FINANCIAL SUSTAINABILITY. ]
TerraNexum has been developing efficient computational approaches to data tasks common to solving complex systems challenges. Particularly those requiring the minimization of energy and time.
We have employed AI and quantum optimization for such tasks. Our focus turns now to efficiency in solving problems common to energy dissipative systems.
[ GEOTHERMAL AND WASTE HEAT REUSE ]
We built our cloud-based Quantum Geospatial Optimizer (QGO) platform with the integration of clean energy, carbon sequestration, and ecosystem restoration efforts in mind.
Our goal was to visualize for planners and project developers how these three efforts could be co-located to provide greater benefits together than separately, particularly in support of a high-value information economy. Thereby valorizing sustainability efforts.
Our first data product below: minimal thermal energy networks at building resolution for 14 of 50 US states. These large geospatial graph networks are also suitable for benchmarking more efficient optimization algorithms.
[ NATURE-BASED - BIOMASS - BIOGENIC ADSORPTION ]
We have mapped parallels between graph networks and turbulent flows that we believe are likely to simplify both the representation of such flows and also their simulation.
If AI can model such complexity, it is within reason that there are representations that can do the same. Not with the large energy consumption of large language models, but with the efficient energy and resource use common to NI - our own natural intelligence, that above our shoulders.
Mathematics is a tool, like language and like technology. We can choose how we use these. We can also choose to extend these in ways that help us to better solve our hard problems.
WHO
Who uses QGO?
QGO was designed as a data-driven visualization and optimization platform to identify and co-locate cost-effective sustainable project opportunities. The goal: to display for the following users how resources and costs could be optimized for high-reward, high-impact projects.
Sustainability Professionals: Requiring tools to identify, analyze, and visualize interconnected sustainable projects.
Communities and Local Governments: Seeking to implement sustainable projects and achieve economic growth.
WHAT
QGO is color-coded as follows:
Green: potential commercial locations for clean energy
Yellow: where energy is produced today via combustion.
Red: heights indicate the largest annual emissions.
This color-coding enables a fast visual assessment for the following uses:
Key Features
1. Project Identification: With additional economic, social, and environmental data, the best areas for sustainable projects are those with a high density of green.
2. Resource Mapping: Benefits for both people and nature, considering available assets, infrastructure, and natural areas, can be more readily highlighted.
HOW
We first identify the large networks along which energy and resource flows are needed. Then we can optimize such flows, with the provision of cleaner, more sustainable flows as a future target.
QGO has had 3 objectives in mind:
1) to calculate what is needed to zero out the emissions within an area that also improves the economic, human, and natural value in that area.
2) to highlight the people and resources that would make suggested projects profitable based on a community's economic, social, and environmental needs, and
3) to optimize the layout of projects to maximize the benefits of their co-location.
MISSION
POSSIBLE.
Through our work, we are redefining what is possible.
If it is within the laws of physics and human capability, if knowledge exists somewhere in the world, then "impossible" becomes a logistics problem.
A solvable problem. On its way to being solved.
