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MobiPulse: AI for Mobility

DATAA, VUB, ULB, STIB, MEC & Espace Mobilité have partnered to develop the MobiPulse Project, that was presented to the Innoviris Call on Artificial Intelligence.

Brussels’ citizens use their cars as the main transportation means despite the fact that 60% of journeys are of less than 5km. Traffic analysis shows that Brussels competes with London for the most congested city in Europe. The average time wasted by Brussels’ drivers in traffic amounts to 171 hrs/year per citizen, increasing by 3% per year. The biggest challenge and opportunity is the integration of all available means of transport: Trains, buses, metro, taxis, bicycles, and carpooling must all become part of a consistent alternative to cars, contributing to improving traffic flow. MobiPulse will address this problem through a novel artificial intelligence (AI) approach. MobiPulse solution will integrate the IT systems of all the players involved, providing real-time information and recommendations to the end-users.

The overall project objective is to build an innovative solution for smart urban mobility, that addresses the above needs, and additionally creates new business opportunities, specifically in the domains of smart cities and smart advertising.
A prime objective of MobiPulse is to enable the collection, filtering and management of diverse traffic-related data. APIs from open traffic data weather feeds, open data repositories will be mined. Moreover, the consortium will process data from key mobility players, including car sharing platforms, bike sharing platforms, parkings, taxi/Uber, charging stations.
The major scientific objective of MobiPulse is to advance the state of the art with respect to mobility analysis and to design a novel mobility recommendation system that integrates heterogeneous data. We identify two key scientific areas of focus: an innovative data foundation solution and a novel data analytics pipeline. The data foundation (a database system) will primarily support the data analytics engine, but it shall also facilitate innovative mobile/web application development. We plan to work on both approaches to creating moving object databases (MOD).
The MobiPulse AI engine will be a powerful tool of optimization with multiple applications ranging from providing information to commuters through mobile apps and media announcements to an integrated service for actors to apply long-term transportation policies. Furthermore, through analyzing commuter patterns and behaviors, the MobiPulse engine will facilitate the delivery of relevant and useful ads to the consumer using smart advertising solutions, thereby leading to a new source of revenues for the owners.
Business Expansion Objectives. This includes efforts during the project that would result in the expansion of the MobiPulse platform. An upward business potential is identified in applying MobiPulse AI to the huge amount of operational data that is collected from mobility partners.
This upward potential can be split into two business opportunities:

  • Optimization of multimodal travel choices for end users. While present tools focus on simple traffic information such as availability and schedules, advanced prediction techniques will go beyond and will offer dynamic optimization of the multimodal travel, including potential incidents and traffic perturbations. This will lead to advanced new features of the MobiPulse AI solution that can be implemented in different third party solutions through licence fees and variable fees depending on the quantity of data treated.
  • Data analysis services for mobility actors. While MobiPulse AI Mobility business model serves the goals of the mobility managers and urban planners, one can expect to develop value from the data analysis, which goes beyond this model, such as, retail companies who want to launch new stores, or insurance companies to assess drivers.
DATAA will integrate MobilPulse as part of it's AI4 platform to provide data analytics service including mobility.
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