Asteroids and Solar Storms, One Dashboard: AI-Powered Tracking and Real-Time Space Weather Could Save Satellites and Billions
It’s another busy week in near‑Earth space. NASA’s asteroid tracking feed lists 87 near‑Earth objects (NEOs) approaching between August 17–24. The closest: small object 2025 PY1 passing at ≈0.00197 AU—about 0.77 lunar distances—safely clear but operationally noteworthy. In parallel, Earth rode out a moderate geomagnetic storm (Kp 6) on August 9, and NASA’s space weather alerts catalogued a burst of coronal mass ejections (CMEs) from August 3–14. For operators of satellites, power grids, GNSS services, and polar aviation, these aren’t separate stories. They are coupled risks that can be managed better with faster detection, quantified uncertainty, and coordinated actions. Recent technical work points to a software‑led edge. According to Deep learning-assisted near-Earth asteroid tracking in astronomical images, neural pipelines accelerate moving‑object discovery and suppress false positives. According to Deep operator neural network applied to efficient computation of asteroid surface temperature and the Yarkovsky effect, neural operators can speed Yarkovsky modeling that nudges asteroid orbits over years. On the decision side, A Markov Decision Process Framework for Early Maneuver Decisions in Satellite Collision Avoidance formalizes fuel‑versus‑risk trade‑offs for satellite maneuvers. And on the solar front, Prediction of Solar Energetic Events Impacting Space Weather Conditions describes forecasting methods for radiation and geomagnetic disturbances. Together with NASA’s live feeds—CNEOS for asteroids and DONKI for space weather—the building blocks exist for one fused dashboard that translates minutes into money saved.