OrbitalSync utilizes a combination of machine learning algorithms and precise orbital mechanics models to provide operators with a real-time tracking and alignment dashboard.

It integrates data from onboard satellite sensors and ground stations to continuously calculate necessary adjustments to satellite trajectories, leveraging predictive analytics to anticipate and correct potential discrepancies.

The platform offers a centralized interface where operators can monitor satellite positions, predict potential collisions, and optimize orbital paths in real time, ensuring synchronized mission operations regardless of the orbital module.

OrbitalSync drastically reduces the risk of satellite collision and communication breakdowns by offering real-time multi-orbit synchronization.

Its predictive analytics provides an edge in maintaining efficient satellite operations, reducing operational costs, and increasing mission success rates through better data accuracy and reliability.

The technology leverages existing data from satellite telemetry and ground stations, integrating advanced machine learning for prediction accuracy.

The initial development is complex and requires substantial computing resources, but advances in cloud computing make the platform feasible.

Regulatory compliance will be a key focus because space operations strictly require adherence to international regulations, demanding robust risk mitigation strategies in the solution.