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Europe · Earth-observation mission with onboard AI

ESA Φsat-2

This project focuses on earth-observation mission with onboard AI.


ESA’s Φsat-2 is a 6U Open Cosmos satellite that runs AI applications on its own Earth-observation imagery. It launched on 16 August 2024 and began delivering science data in 2025 after commissioning. Its applications cover clouds, ships, street maps, image compression, wildfires and marine anomalies.

ESA / Open Cosmos · Reported orbital demonstration

Scope: Mission-specific processing · Its AI applications primarily process imagery acquired by the mission’s own multispectral instrument.

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Technical specifications not disclosed

Figures retain their disclosed units and scope. Launched hardware does not establish demonstrated performance; targets may change. Not disclosed means no figure in the reviewed sources.

PROJECT RELATIONSHIPS

Suppliers & project partners

NEXT MILESTONE

Further mission results and technical disclosures

Manual review with evidence gaps 5 Nov 2026. Launch and science-data delivery are confirmed. Published accounts differ on the current operating timeline and the instrument’s identity. Primary body last observed not available. Source monitoring: unavailable. Source collection and substantive profile review are separate checks. Plans and dates may change.

ESA / Open Cosmos official mission evidence (opens in a new tab)
WHAT REMAINS UNKNOWN
  • Current operating status after ESA’s planned March 2026 end date
  • Mission lifetime descriptions differ across official pages
  • Installed RAM, storage capacity, IT demand and numerical thermal limits
  • WMO’s October 2026 registry names HyperScout-2, while ESA’s mission technical note names Simera MultiScape100

Project updates

Verified announcements and milestones linked to this project, newest first.

ESA research tests a faster image-processing pipeline for Φsat-2 (opens in a new tab)

ESA’s Φ-lab reports a ground benchmark that reconstructs processed Φsat-2 images from raw data in an average of 3.58 minutes per 4096-by-4096 image on a Myriad 2 accelerator. The research estimates a 3.5- to 6.6-fold speed-up over the mission’s traditional CPU preprocessing, depending on the output level.