About a year ago, Kentyou joined the EUHubs4Data program to develop urban mobility solutions using AI and data analytics. Today, we present some of the important results of this collaboration and show how our AI can optimise the localisation of urban mobility solutions.
Optimising the localisation of urban mobility solutions
The need to optimise the localisation of urban mobility infrastructures came as a demand from our interaction with the Paris Saclay Communauté d’agglomération (gathering cities on the Saclay plateau in Essonne, France).
Deploying new mobility infrastructure on a territory requires to solve a multi-parameter optimisation problem. Indeed the solution must consider environmental, social and economic criteria. Indeed, mobility infrastructure is an important investment for a city or region. It is also critical to transform mobility habits and behaviour and transition into a zero-carbon territory.
A deployment must take into account the environmental specificities of the territory: different CO2 footprint of urban and rural areas, local geographical constraints, points of interest, demography, typologies of neighbourhoods, and connection with existing services. The deployment must also ensure algorithmic fairness by accounting social criteria for e.g., disabled, elderlies. And of course, all this without ignoring the budget restrictions of the city.
From Saclay to Barcelona with EUHubs4Data
Working with the EUHubs4Data project was a great opportunity for Kentyou to evaluate how our approach can fit different cities, with different needs and different data sets available.
Indeed, the EUHubs4Data project gave us access not only to efficient data processing infrastructure and geospatial toolkits, but also to local data sets from Barcelona. This allowed to replicate and extend the work initiated with Saclay.
Over 260 new datasets were used and integrated in our analysis thanks to the use of the Eclipse sensiNact platform. The modularity, extensibility, and interoperable capabilities of the sensiNact platform proved a very valuable asset in this task. This allowed us to use demography, professional mobility, environment, culture/leisure, trade and employment datasets to optimize our solution.
Our methodology then focused on the exploration of these data. This allows us to detect key areas in the urban or rural tissue. From then we can extract valuable insights and finally provide recommendations for optimal locations. This approach present an important innovation compared to the state of the art, and even resulted in a scientific publication at IE2022 18th international conference on intelligent Environments : S. Kleisarchaki, L. Gürgen , S.M. Kassa, M. Plociennik and D.G. Vidal. “Optimization of Soft Mobility Localization with Sustainable Policies and Open Data”, IE’2022.
Turning data into actionable recommendation with Kentyou Eye
Indeed, analysing data and providing insight on the current mobility situation and its limitations is nice. But being able to propose solutions is always better.
So we integrated the recommendation engine for optimal localization of mobility infrastructure in the Kentyou Eye hypervisor. The tool allows the city councillors to create a template policy, targeting specific types of populations and areas. They then receive recommendations for the localisation of new stations in the city within the budget they defined.
This tool is highly adaptable, and can easily adapt to new territories, integrating new data sets and taking into account local demands and constraints.
As such, our goal is to make from Kentyou Eye a complete solution for handling the mobility and its impact in a territory. This requires rapid integration of specific local datasets (enabled by Eclipse sensiNact), data analytics capabilities and finally AI solutions that can provide future perspectives and recommendations.
Kentyou will continue to work on this use case and its extensions to other cities and territories. EUHubs4Data was an important milestone in this work. Open innovation is at the heart of our company vision, and we value this type of collaborations.