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Traffic signal optimisation with Machine Learning on AWS (Level 300 | Advanced)

As cities grow, congestion and traffic safety contribute to city liveability. While traffic signal control is essential for transportation efficiency in road networks, globally optimal solutions are challenging to come by due to the complex nature of traffic dynamics. In this session, we use IoT and ML to deep dive on a dynamic traffic signal optimisation approach, using live transport data processed using computer vision at the edge with AWS Panorama as input to a reinforcement learning model deployed at the edge with AWS IoT Greengrass.

Craig Lawton, Principal Solutions Architect, AWS
Pauline Kelly, Solutions Architect, AWS