Federated learning for smart cities: A comprehensive survey
With the advent of new technologies such as the Artificial Intelligence of Things (AIoT), big
data, fog computing, and edge computing, smart city applications have suffered from issues …
data, fog computing, and edge computing, smart city applications have suffered from issues …
Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review
The goal of managing smart cities and societies is to maximize the efficient use of finite
resources while enhancing the quality of life. To establish a sustainable urban existence …
resources while enhancing the quality of life. To establish a sustainable urban existence …
Data-driven predictive control for smart HVAC system in IoT-integrated buildings with time-series forecasting and reinforcement learning
Optimising HVAC operations towards human wellness and energy efficiency is a major
challenge for smart facilities management, especially amid COVID situations. Although IoT …
challenge for smart facilities management, especially amid COVID situations. Although IoT …
Advanced controls on energy reliability, flexibility, resilience, and occupant-centric control for smart and energy-efficient buildings—a state-of-the-art review
Advanced controls have attracted increasing interests due to the high requirement on smart
and energy-efficient (SEE) buildings and decarbonization in the building industry with …
and energy-efficient (SEE) buildings and decarbonization in the building industry with …
[HTML][HTML] Machine learning and remote sensing integration for leveraging urban sustainability: A review and framework
Climate change and rapid urbanisation exacerbated multiple urban issues threatening
urban sustainability. Numerous studies integrated machine learning and remote sensing to …
urban sustainability. Numerous studies integrated machine learning and remote sensing to …
Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects
This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …
renewable energy generation using machine learning (ML) and deep learning (DL) …
[HTML][HTML] Machine learning for forecasting a photovoltaic (PV) generation system
To mitigate the carbon print of buildings, they should have on-site renewable energy
generation systems to supply energy for the buildings without relying on the national grid …
generation systems to supply energy for the buildings without relying on the national grid …
Multi-agent deep reinforcement learning optimization framework for building energy system with renewable energy
R Shen, S Zhong, X Wen, Q An, R Zheng, Y Li, J Zhao - Applied Energy, 2022 - Elsevier
Under the background of high global building energy consumption, meeting the ever-
growing energy consumption demand of building energy system (BES) through renewable …
growing energy consumption demand of building energy system (BES) through renewable …
[HTML][HTML] Power to heat: Opportunity of flexibility services provided by building energy systems
Buildings play a crucial role in global electricity consumption, but their function is evolving.
Rather than merely consuming energy, buildings have the potential to become energy …
Rather than merely consuming energy, buildings have the potential to become energy …
[HTML][HTML] Digital twin technology for thermal comfort and energy efficiency in buildings: A state-of-the-art and future directions
In recent years, the integration of digital technologies has grown rapidly in the field of
thermal comfort and energy efficiency for buildings. The concept of a digital twin …
thermal comfort and energy efficiency for buildings. The concept of a digital twin …