Imagine a smart camera in space that doesn't just take pictures, but thinks on the spot to spot heat leaks or forest fires instantly. Instead of sending massive amounts of raw data back to Earth and waiting for a computer to process it, the satellite uses a built-in brain to filter the important bits. It's like having a security guard who only alerts you when they see a fire, rather than sending you a 24-hour video of an empty hallway.
Current Earth Observation is slowed by a trade-off between image resolution and the time it takes to get data to users. This delay prevents real-time response to wildfires and inefficient energy use in cities.
A compact thermal infrared telescope integrated with a GPU-based on-board AI processing system and a modular, serviceable satellite platform.
If you are a farming service provider dealing with crop failure due to heat stress — this project developed a compact thermal infrared telescope that monitors vegetation heat stress. This allows for faster interventions to save crops and improve yields.
If you are a city agency dealing with inefficient building heating and urban heat islands — this project developed on-board AI processing that identifies heat loss at the building level. This helps target energy retrofits to reduce emissions.
If you are a disaster response firm dealing with slow detection of forest fires — this project developed a low-latency alert system using GPU-based on-board processing. This ensures critical data reaches responders faster to mitigate damage.
Based on available project data, the specific price is not listed, but the project aims to create a 'compact and affordable' TIR telescope to transform the economics of imagery.
Yes, the project focuses on a modular and in-orbit serviceable platform design, which supports scalability and maintenance in space.
Based on available project data, licensing details are not provided, but the consortium includes two SMEs and one university across three countries.
The project runs from 2026-09-01 to 2028-08-31, with the goal of reaching flight acceptance by the end of the project.
The system uses GPU-based on-board processing to filter and process data before transmission, reducing the delay in delivering time-critical information to users.
The consortium is lean and industry-heavy, consisting of 3 partners from 3 countries (UK, BG, PT). With a 67% industry ratio and 2 out of 3 partners being SMEs, the project is structured for commercial agility and rapid technology transfer rather than pure academic research.
Contact Super-Sharp Space Systems Limited in the UK
Contact us to explore partnership opportunities with the THEOSCOPE consortium for early access to TIR AI data.
