Privacy-preserving blockchain-based federated learning for traffic flow prediction
Y Qi, MS Hossain, J Nie, X Li - Future Generation Computer Systems, 2021 - Elsevier
As accurate and timely traffic flow information is extremely important for traffic management,
traffic flow prediction has become a vital component of intelligent transportation systems …
traffic flow prediction has become a vital component of intelligent transportation systems …
An efficient and reliable asynchronous federated learning scheme for smart public transportation
Since the traffic conditions change over time, machine learning models that predict traffic
flows must be updated continuously and efficiently in smart public transportation. Federated …
flows must be updated continuously and efficiently in smart public transportation. Federated …
[HTML][HTML] A blockchain based privacy-preserving federated learning scheme for Internet of Vehicles
The application of artificial intelligence technology in Internet of Vehicles (IoV) has attracted
great research interests with the goal of enabling smart transportation and traffic …
great research interests with the goal of enabling smart transportation and traffic …
Privacy-preserving blockchain-enabled federated learning for B5G-Driven edge computing
The arrival of the fifth-generation technology standard for broadband cellular networks (5G)
and beyond 5G networks (B5G) rises the speed and robustness ceiling of communicating …
and beyond 5G networks (B5G) rises the speed and robustness ceiling of communicating …
Multilevel federated learning-based intelligent traffic flow forecasting for transportation network management
Accurate traffic flow forecasting is crucial to improving traffic safety and alleviating road
congestion for intelligent transportation network management. Recently, spatial-temporal …
congestion for intelligent transportation network management. Recently, spatial-temporal …
Blockchain empowered asynchronous federated learning for secure data sharing in internet of vehicles
Y Lu, X Huang, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In Internet of Vehicles (IoV), data sharing among vehicles for collaborative analysis can
improve the driving experience and service quality. However, the bandwidth, security and …
improve the driving experience and service quality. However, the bandwidth, security and …
Bift: A blockchain-based federated learning system for connected and autonomous vehicles
Machine learning (ML) algorithms are essential components in autonomous driving. In most
existing connected and autonomous vehicles (CAVs), a large amount of driving data …
existing connected and autonomous vehicles (CAVs), a large amount of driving data …
Privacy-preserving traffic flow prediction: A federated learning approach
Existing traffic flow forecasting approaches by deep learning models achieve excellent
success based on a large volume of data sets gathered by governments and organizations …
success based on a large volume of data sets gathered by governments and organizations …
FASTGNN: A topological information protected federated learning approach for traffic speed forecasting
Federated learning has been applied to various tasks in intelligent transportation systems to
protect data privacy through decentralized training schemes. The majority of the state-of-the …
protect data privacy through decentralized training schemes. The majority of the state-of-the …
Federated deep learning for smart city edge-based applications
Y Djenouri, TP Michalak, JCW Lin - Future Generation Computer Systems, 2023 - Elsevier
The growing quantities of data allow for advanced analysis. A prime example of it are smart
city applications with forecasting urban traffic flow as a key application. However, data …
city applications with forecasting urban traffic flow as a key application. However, data …