Imagine a giant digital brain for a city that can watch every bus, car, and train in real-time without crashing from too much information. It sorts through massive piles of movement data to predict traffic jams or crowd risks before they happen. It's like having a high-tech weather forecast, but for how people move through streets instead of rain.
Cities struggle to process massive, fast-moving mobility data from various sources in real-time. This leads to inefficient traffic management, poor crowd safety at events, and a lack of actionable insights for urban planning.
A Mobility Analytics as a Service (MAaaS) toolset including a reference architecture, real-time AI/ML algorithms for traffic prediction, and interactive dashboards for risk assessment and traffic flow.
If you are a transit authority dealing with unpredictable passenger flows and congestion — this project developed a MAaaS toolset that enables real-time control and prediction on multi-modal integrated traffic management to improve decision making.
If you are a venue operator dealing with dangerous crowd densities during major events — this project developed a prototype demonstrator on risk-assessment and forecasting that improves performance in managing crowded areas.
If you are a consultancy dealing with fragmented data on how citizens move — this project developed a data-driven analytics tool for traveller trip characteristics inference and traffic flow studies to optimize city layouts.
Based on available project data, the specific pricing is not listed, but the system is designed as 'Analytics as a Service' (MAaaS), suggesting a subscription or usage-based cloud model.
Yes, the project specifically targets 'extreme-scale' urban mobility data, utilizing a distributed computing environment across edge and cloud processing to handle high-volume, velocity, and variety.
Based on available project data, the IP details are not specified, though the project involves 22 partners including 12 industry entities and 9 SMEs.
The toolset is designed to be integrated into existing systems to improve commercial offerings, specifically targeting TRL 6 applications for early adopters.
The project period runs from 2023-01-01 to 2025-12-31, with deliverables moving from prototypes to final releases of analytics tools.
The consortium is heavily weighted toward commercial application, with 12 industry partners (55% ratio) and 9 SMEs. This high industrial presence, spanning 10 countries, suggests the project is driven by market needs rather than pure academic research, focusing on the practical deployment of the MAaaS toolset.
Contact INLECOM INNOVATION ASTIKI MI KERDOSKOPIKI ETAIREIA in Greece
Contact us to connect with the EMERALDS consortium for early adoption of the MAaaS toolset.
