Federated learning in smart cities: Privacy and security survey
Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …
data and the internet of things improves the monitoring and integration of different …
[HTML][HTML] Emerging information and communication technologies for smart energy systems and renewable transition
Since the energy sector is the dominant contributor to global greenhouse gas emissions, the
decarbonization of energy systems is crucial for climate change mitigation. Two major …
decarbonization of energy systems is crucial for climate change mitigation. Two major …
A secure federated learning framework for residential short term load forecasting
Smart meter measurements, though critical for accurate demand forecasting, face several
drawbacks including consumers' privacy, data breach issues, to name a few. Recent …
drawbacks including consumers' privacy, data breach issues, to name a few. Recent …
[HTML][HTML] FedForecast: A federated learning framework for short-term probabilistic individual load forecasting in smart grid
Load forecasting plays a crucial role in the power system operation and planning. However,
with people's increased awareness of privacy, consumers may not be willing to share their …
with people's increased awareness of privacy, consumers may not be willing to share their …
Edge AI for Internet of Energy: Challenges and perspectives
The digital landscape of the Internet of Energy (IoE) is on the brink of a revolutionary
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …
A class-imbalanced heterogeneous federated learning model for detecting icing on wind turbine blades
Wind farms are typically located at high latitudes, resulting in a high risk of blade icing. Data-
driven approaches offer promising solutions for blade icing detection, but they rely on a …
driven approaches offer promising solutions for blade icing detection, but they rely on a …
Privacy-preserving regulation capacity evaluation for hvac systems in heterogeneous buildings based on federated learning and transfer learning
Heating, ventilation, and air conditioning (HVAC) systems in buildings have great potential
to provide regulation capacity that is leveraged to maintain the balance of supply and …
to provide regulation capacity that is leveraged to maintain the balance of supply and …
Collaborative policy learning for dynamic scheduling tasks in cloud-edge-terminal IoT networks using federated reinforcement learning
In this article, we examine cloud–edge–terminal Internet of Things (IoT) networks, where
edges undertake a range of typical dynamic scheduling tasks. In these IoT networks, a …
edges undertake a range of typical dynamic scheduling tasks. In these IoT networks, a …
Demand forecasting of e-commerce enterprises based on horizontal federated learning from the perspective of sustainable development
J Li, T Cui, K Yang, R Yuan, L He, M Li - Sustainability, 2021 - mdpi.com
Public health emergencies have brought great challenges to the stability of the e-commerce
supply chain. Demand forecasting is a key driver for the sound development of e-commerce …
supply chain. Demand forecasting is a key driver for the sound development of e-commerce …
Crossing roads of federated learning and smart grids: Overview, challenges, and perspectives
Consumer's privacy is a main concern in Smart Grids (SGs) due to the sensitivity of energy
data, particularly when used to train machine learning models for different services. These …
data, particularly when used to train machine learning models for different services. These …