Welcome to Ray20
Innovation is a requirement to survive challenging times and to come out of those moments with new ideas and opportunities. In light of that, Acubed is still hard at work and we at Ray20 are pleased to introduce the organization’s first project addressing a pertinent challenge in the space industry.
To start, it’s important to know that our team is passionate about Geographic Information Systems (GIS). The current GIS focus is on maximizing the utilization of Earth Observation (EO) imaging assets. However, we believe that a paradigm shift is required in the market that can be brought about by connecting application developers and imagery providers with the information they need.
Ray20’s objective is to create a new layer in the space architecture by placing high resolution cameras on aircraft operated by Airbus customers in North America and Europe once air travel resumes. These cameras will capture very high resolution, high revisit and low cost imagery along their flight routes. We can drive future growth by meeting the market demand for higher temporal and spatial cadence imagery at the lowest price. In doing so, we will remove the barrier to entry for startups with ideas and aspirations to operate in this field.
We envision a future where real time EO imagery and analytics are purchased as a commodity, regardless of which platform it came from (i.e. satellite, drone, HAPS, aircraft, etc). We are working towards this vision by building a system that can offer new levels of availability and reliability of EO and GIS applications over areas with high aircraft population density.
There are very practical applications of this data that may help make this whole idea more tangible for readers. For example, we can offer daily monitoring and mapping of major cities (see figure), improve air traffic management services around cities by providing daily updates on urban developments and changes along flight paths, and enable the evaluation of infrastructure project locations for potential investment. Additionally, we can support disaster response analysis through high frequency sizing of events and their evolution (e.g. evaluating the events surrounding the Edenville Dam collapse in Michigan following days of heavy rains or response to California forest fires), and we can improve weather forecasting models by capturing information on location, type and altitude of clouds, wind speed and direction from factory exhaust plumes. There are so many use cases for which these datasets can provide a material impact on operations and decision-making.
Our near-term goal is to demonstrate that aerial imagery can be acquired via multiple flying platforms, processed on the edge using computer vision and artificial intelligence algorithms, aggregated onto a cloud network for further processing and analysis and delivered to geospatial platforms in a matter of hours, all with no human in the process.
Please continue to follow along as we share more about our progress in the coming months.