Edge Federated Learning: The Merge of Edge Computing and Federated Learning
Edge Federated Learning (EFL) addresses the data silo problem by effectively utilizing the vast data generated on end-user devices, all while preserving user privacy.
While traditional e-governments still rely on centralized control, there's growing interest in merging DAO principles into future governance models, especially in participatory budgeting, transparent grant systems, and decentralized identity & voting.
Edge computing is a decentralized computing model where data processing happens close to the data source like on traffic signals, EV charging stations, or even vehicles themselves instead of relying on centralized cloud data centers.
Learn about communication technologies such as V2V, V2X, IoV, and C-V2X and see how AI and ML are revolutionizing the transportation and traffic control methods.
Learn about IoMT, Telemedicine, and other wearable health tech and see how ML can change the healthcare landscape with all this data.
Learn about BMS, EMS, and other smart building and energy management systems and see how technologies like IoT and Digital Twins are changing the construction industry.
We mostly will discuss the energy crisis for data centers as demand for AI, ML, and Blockchain continues to grow and will explore industry trends.
Edge Federated Learning (EFL) addresses the data silo problem by effectively utilizing the vast data generated on end-user devices, all while preserving user privacy.
Edge computing is an emerging paradigm that brings computation and data storage closer to the sources of data generation, such as sensors and IoT devices.
The Internet of Vehicles (IoV) represents a transformative evolution in transportation, integrating vehicles into the broader Internet of Things (IoT) ecosystem.
1LineCrypto © 2025 All rights reserved
