Aether: A Real-Time Space Weather Intelligence Platform Combining Stream Processing, Ensemble ML, and RAG-Based Conversational AI

Abstract

Space weather monitoring is critical to the operation of satellites, power grids, and telecommunication systems. We present Aether, a reproducible local-first platform with real-time data ingestion, event-driven processing, hybrid storage, ensemble forecasting, anomaly detection, and natural language querying. Aether offers sub-second query latency on multi-year time series data with a Redis-ClickHouse hybrid storage model, processes over 850 events per second with Apache Kafka, and supports natural language querying with the Ollama local LLM without any cloud dependencies. We combine traditional LSTM and Prophet forecasting with Isolation Forest and Autoencoder-based ensemble anomaly detection with 87% precision and 82% recall. We evaluate the system with 30 days of operational data with all metrics meeting or exceeding the design specifications.

Country : India / USA

1 Aditya Arolkar2 Dhaval Smart3 Gaurav Waghmare4 Pratham Atale5 Sarvesh Ponkshe6 Prof. Sonali Despande

  1. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, New Mumbai, Maharashtra, India
  2. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, New Mumbai, Maharashtra, India
  3. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, New Mumbai, Maharashtra, India
  4. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, New Mumbai, Maharashtra, India
  5. Student, North Carolina State University, North Carolina, United States of America
  6. Professor, Smt. Indira Gandhi College of Engineering, Ghansoli, New Mumbai, Maharashtra, India

IRJIET, Volume 10, Issue 4, April 2026 pp. 176-182

doi.org/10.47001/IRJIET/2026.104025

References

  1. J. G. Kappenman, "Geomagnetic storms and their impacts on the U.S. power grid," Metatech Corp., Technical Report Meta-R-319, 2010.
  2. D. N. Baker et al., "A major solar eruptive event in July 2012: Defining extreme space weather scenarios," Space Weather, vol. 11, no. 10, pp. 585–591, 2013.
  3. National Research Council, "Severe Space Weather Events—Understanding Societal and Economic Impacts," National Academies Press, 2008.
  4. Royal Academy of Engineering, "Extreme space weather: impacts on engineered systems and infrastructure," 2013.
  5. NOAA Space Weather Prediction Center, "Space Weather Forecast Discussion," Available: https://www.swpc.noaa.gov/, Accessed: Jan. 2026.
  6. SpaceWeatherLive.com, "Real-time aurora and solar activity," Available: https://www.spaceweatherlive.com/, Accessed: Jan. 2026.
  7. M. Hapgood, "Towards a scientific understanding of the risk from extreme space weather," Adv. Space Res., vol. 47, no. 12, pp. 2059–2072, 2011.
  8. D. Odstrcil, "Modeling 3-D solar wind structure," Adv. Space Res., vol. 32, no. 4, pp. 497–506, 2003.
  9. NASA CCMC, "DONKI - Database of Notifications, Knowledge, Information," Available: https://kauai.ccmc.gsfc.nasa.gov/DONKI/, Accessed: Jan. 2026.
  10. J. Pomoell and S. Poedts, "EUHFORIA: European heliospheric forecasting information asset," J. Space Weather Space Clim., vol. 8, A35, 2018.