ComforMap
We propose a mobile application that allows users to travel by alternative modes of transport (walking, cycling, etc.) using the most climate-friendly, least polluting and least allergic routes.
Overview of the project
We propose a mobile application that allows users to travel by alternative modes (walking, cycling, scooter) by the most climatically comfortable, least polluted and least allergic routes, while taking into account the additional distance desired by the user compared to the shortest route. This climatic comfort analysis is based on innovative algorithms and machine learning and artificial intelligence techniques, which take into account the real climatic conditions, the urban morphology and the different characteristics of the territory. In addition, the algorithms have been developed in an environmental research laboratory in Lyon for 4 years.
The mobile application is currently being tested in real life on the territory of the Metropolis of Lyon in order to be able to adjust it according to the feedback of the final users, i.e. the citizens.
We offer a mobile application that allows users to travel by alternative modes via the most comfortable route.
Pilote operation, experimentation
01/04/2021 - project still in progress
We contribute to increasing the number of days of use of alternative transportation for each user and the number of people who use alternative transportation on a daily basis. We contribute to the reduction of carbon emissions in the territories.
We address companies and local authorities who wish to promote alternative modes of transport to reduce their carbon tax, limit parking spaces and increase the physical and mental well-being of their employees or citizens, as well as their sanitary well being on the road.
The project has been financed through equity and grants received due to the innovation of the project and its impact on the health of the inhabitants and the environment.
organisation
We propose a mobile application that allows users to travel by alternative modes (walking, cycling, etc.) using the most climatically comfortable, least polluted and least allergic routes, while taking into account the additional distance desired by the user compared to the shortest route. This climatic comfort analysis is based on an innovative algorithm and machine learning techniques, which take into account the real climatic conditions, urban morphology and the different characteristics of the territory.
in collaboration
We have the support of the European Space Agency, the AURA region and the BPI, in the form of incubation and financing.