COLLABORATIVE FEDERATIVE LEARNING APPROACH FOR INTERNET OF VEHICLES TRAFFIC PREDICTION This invention is to deploy a collaborative federative learning approach for the internet of vehicle traffic prediction. Though there were many traditional and some intelligent technical approaches were deployed in traffic prediction, the concern about privacy and security, where the client is uncomfortable in sharing the information globally, creates the need to deploy a collaborative federative learning approach. In this application, the internet of drones is deployed to gather information regarding the vehicle location, which is configured with the internet of vehicle technology. Continuous image capturing in the area of traffic congestion is monitored. In this method, the training set is modeled in local devices itself. A deferred acceptance algorithm is deployed between local devices to model parameters and its associated device. The desired information or the model parameters alone is then sent to the cloud through the gateway. This is one of the easiest, fast computing methods to enable the prediction of traffic congestion with privacy and less storage consumption. 1| P a g e COLLABORATIVE FEDERATIVE LEARNING APPROACH FOR INTERNET OF VEHICLES TRAFFIC PREDICTION Drawings Collaborative Federative Learning with Matching technique Fig. 1 Collaborative Federative Learning with matching technique with associated drones. 1 P a g e
COLLABORATIVE FEDERATIVE LEARNING APPROACH FOR INTERNET OF VEHICLES TRAFFIC PREDICTION
2020-09-10
Patent
Elektronische Ressource
Englisch
Federative architecture - an approach of a contract-based electric/electronic architecture
Kraftfahrwesen | 2012
|Collaborative Reinforcement Learning for Multi-Service Internet of Vehicles
BASE | 2023
|