AI-GOVSATCOM - AI-GOVSATCOM

The project aims to develop an AI-powered predictive model to optimize bandwidth allocation for GOVSATCOM services, ensuring a dynamic and adaptive approach to satellite resource management. Traditional static bandwidth allocation methods are being replaced with a demand-driven, real-time adaptive system, allowing for greater efficiency and responsiveness. By leveraging AI, the model ensures optimal utilization of satellite resources, reducing Operational Expenditures (OPEX) while maintaining high service quality.

A key aspect of the project is its focus on proactive decision-making, where AI-driven traffic forecasting enables the system to anticipate demand surges and mitigate network congestion before it occurs. This predictive approach enhances the overall performance of the network, ensuring reliability and efficiency in critical governmental and humanitarian operations. The model also aims to empower stakeholders by providing satellite operators with actionable insights that improve resource allocation and service reliability.

To achieve these advancements, the project employs cutting-edge AI techniques, including probabilistic forecasting and Kolmogorov-Arnold Networks (KANs), which allow for scalable, efficient, and highly accurate predictions of bandwidth demand. This integration of AI not only improves system efficiency but also ensures that satellite communications can dynamically adapt to changing conditions, ultimately transforming the way satellite resources are managed.