ROBOT
Urban Air Mobility (UAM) offers a potential to create a faster, cleaner, and safer transportation system. However, recent events have shown that modern UAVs are vulnerable to be attacked through bugs or sometimes malicious devices. IFT’s ROBOT with decentralized blockchain microservices is effective in securing avionics data accessing and sharing in a hierarchical edge-fog-cloud computing paradigm, enhancing performance over reliability, resilience, and assurance in UAM networks.
METHOD:
1 – Developed data-driven Machine Learning (ML) Models (e.g., XceptionTime) to detect malicious patterns and distinguish between anomalies and legitimate sensor readings
2- Developed a Lightweight Micro-chained fabric to provide decentralized security and privacy-preserving guarantees for UAM data acquisition, storage and analytic
3- Developed a Federated Learning (FL) method to enable multi-task processing with optimal scheduling at edges
4- Developed a reputation system to evaluate the reliability of sensing nodes in real-time for Energy and Spectrum Efficiency.
KEYWORDS: Urban Air Mobility (UAM), Blockchain, Container-Based Microservices, Edge-Fog-Cloud Computing, Machine Learning, Anomaly Detection
TECHNICAL SPECS: Decentralized Blockchain Network (Microchain), Advanced Machine Learning-based Anomaly Detection (MLAD), Container-based Microservices, Digital Twin Reputation System