Industry is increasingly deploying machine learning in safety-critical settings such as smart manufacturing, smart cities, smart healthcare, and intelligent transportation. These environments generate distributed, heterogeneous, and privacy-sensitive data that often cannot be centralized.
Federated Learning enables collaborative model training across distributed data silos without sharing raw data. TrustFL-SIS focuses on the next challenge: making federated learning credible, interpretable, reliable, secure, fair, and sustainable in industrial systems.
