Multimodal Transport Data Analytics Platform
Dr. HMND Bandara
- To develop a scalable, multimodal transport data aggregation and analytics platform which is capable of identifying emerging behaviors of passenger interests and demands, scheduling practices, driving behavior and habits, and monitoring and tracking fleets
- To support multiple real-time and long-term use cases as required by different stakeholders for scheduling fleets, route suggestions, traffic estimation and prediction, planning transportation infrastructure, and implementing intelligent transportation systems
- To define a common data exchange format that can capture diversity in data formats, volume, and arrival rates to enable seamless data exchange across for multiple stakeholders and systems