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 …
Artificial intelligence and blockchain technology for secure smart grid and power distribution Automation: A State-of-the-Art Review
Artificial Intelligence (AI) integrated with Blockchain distributed ledger technology (BDLT)
has become the most attractive research area in the domain of renewable energy and …
has become the most attractive research area in the domain of renewable energy and …
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …
death cases and affected all sectors of human life. With gradual progression of time, COVID …
[HTML][HTML] New York City taxi trip duration prediction using MLP and XGBoost
M Poongodi, M Malviya, C Kumar, M Hamdi… - International Journal of …, 2022 - Springer
Abstract New York City taxi rides form the core of the traffic in the city of New York. The many
rides taken every day by New Yorkers in the busy city can give us a great idea of traffic …
rides taken every day by New Yorkers in the busy city can give us a great idea of traffic …
Blockchain for edge of things: Applications, opportunities, and challenges
In recent years, blockchain networks have attracted significant attention in many research
areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by …
areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by …
[HTML][HTML] Energy System 4.0: Digitalization of the energy sector with inclination towards sustainability
The United Nations' sustainable development goals have emphasized implementing
sustainability to ensure environmental security for the future. Affordable energy, clean …
sustainability to ensure environmental security for the future. Affordable energy, clean …
A VMD and LSTM based hybrid model of load forecasting for power grid security
As the basis for the static security of the power grid, power load forecasting directly affects
the safety of grid operation, the rationality of grid planning, and the economy of supply …
the safety of grid operation, the rationality of grid planning, and the economy of supply …
Deep learning in smart grid technology: A review of recent advancements and future prospects
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …
a promising landscape for high grid reliability and efficient energy management. This …
Optimal 5G network slicing using machine learning and deep learning concepts
Network slicing is predetermined to hold up the diversity of emerging applications with
enhanced performance and flexibility requirements in the way of splitting the physical …
enhanced performance and flexibility requirements in the way of splitting the physical …
[HTML][HTML] A comprehensive review on smart grids: Challenges and opportunities
JJ Moreno Escobar, O Morales Matamoros… - Sensors, 2021 - mdpi.com
Recently, the operation of distribution systems does not depend on the state or utility based
on centralized procedures, but rather the decentralization of the decisions of the distribution …
on centralized procedures, but rather the decentralization of the decisions of the distribution …