Smart City Mobility with AI
This system utilizes Artificial Intelligence to optimize urban mobility by forecasting demand, planning routes and managing traffic flow.
Demand Routing Pricing Multimodal Incidents
Travel Time, Occupancy & CO₂e Emissions
The system calculates Estimated Travel Times (ETAs) with a focus on accuracy and identifies potential incidents or complaints.
Data sources include validated mobility data alongside traffic and weather information.
LLMs? Assistants, Directories & Q&A
The platform scales to encompass large datasets of events and AI models, facilitating a comprehensive understanding of urban mobility.
AI plays a crucial role in optimizing city-based transportation.
Frequently asked questions
What is meant by occupancy and schedule accuracy when considering route planning?
Occupancy and schedule accuracy refer to the degree to which routes align with actual passenger demand and predicted travel times, accounting for potential delays or disruptions.
How does the system address incidents and emergencies, ensuring compliance with regulations?
The system monitors for incidents and emergencies, validating that all responses meet established safety standards and regulatory requirements.
What data is used to assess CO₂e emissions, noise levels, and user satisfaction?
CO₂e emissions, noise levels, and user satisfaction are assessed using a combination of data from sensors, cameras, telematics devices, and passenger feedback applications.
What types of data sources contribute to the system's functionality – including sensor data, camera feeds, and telematics?
The system leverages a diverse range of data sources, encompassing information from sensors, cameras, telematics devices, and passenger-facing applications to provide a holistic view of urban mobility.
▶ Try it live
Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.