Speaker
Description
First Name: Srikanth
Last Name: Kodeboyina
Affiliation: Blue Space
All Authors: Srikanth kodeboyina
Abstract: Continuous observation of solar-wind fluctuations and heliospheric magnetic-field variations is central to predicting space-weather impacts on satellites, aviation, and communication systems. Blue Eye Soft Corp (Blue Space) has developed a lightweight, AI-integrated magnetic-field sensor platform designed for micro- and nanosatellite applications. The system combines miniaturized fluxgate technology with onboard machine-learning algorithms for noise suppression and anomaly detection. Ground validation experiments demonstrate a noise floor below 5 pT/√Hz at 1 Hz and stable performance under thermal variations up to ±50 °C. A high-altitude balloon campaign at 30 km altitude successfully captured transient field variations correlated with simulated solar-wind disturbances. The onboard analytics identified over 93 % of these events in real-time, with fewer than 3 % false positives. These findings confirm the feasibility of deploying AI-driven magnetometer payloads for distributed heliospheric monitoring. Integrating such sensors across small-satellite constellations will improve temporal and spatial coverage of magnetic-field dynamics and enhance early-warning capability for space-weather disruptions. This initiative complements missions like Solar Orbiter, IRIS, and Aditya-L1, offering a commercial-ready framework for scalable, low-cost monitoring infrastructure that strengthens operational resilience and supports collaborative solar-physics research.