DataCity entrepreneurs #4: How can data be used to reduce congestion in cities? - Datacity

DataCity entrepreneurs #4: How can data be used to reduce congestion in cities?


This serie presents the entrepreneurs that participated to DataCity Paris 2nd edition and their projects that were presented during the Demo Day on June 6, 2017

Edouard Maurel, DataCity Paris Program Manager

Edouard, within DataCity, which projects were you working on ?

The first project that I worked on is related to logistics. By using the sets of data made available by La Poste (including delivery points, vehicle type, etc.), Colisweb used its algorithms co-developed in partnership with INRIA (research institute for mathematics and computer science) to study means of modelling the impact of urban planning (for example, a road closure) in terms of delivery cost and CO2. In the second phase, this solution was rolled out to measure the necessary size of a delivery fleet (bicycles, vans, lorries, etc.) over a specific urban area.

What was the most difficult moment and which result are you most proud of?

As La Poste provided anonymous data on millions of deliveries, it took a lot of time to pick out all data sets from such a diverse group. We are actually still adding to the data to make the analysis as reliable as possible.

I am proud of having played a role in developing a completely innovative solution which will allow local authorities to make delivery-related decisions based on facts.

If this project was replicated in all cities worldwide …

Our towns and cities would definitely be less congested due to fewer double-parked delivery vans. An appropriate delivery fleet and specific systems would improve air quality and limit the cost and carbon footprint of each delivery.

The second challenge I worked on was …

… an experiment which is set to have an impact on the daily lives of Parisians very soon. In partnership with SUEZ and Paris City Hall, Craft.ai has developed a solution to limit cluttering on pavements in Paris. As all bins are now fitted with a microchip containing information on the exact time of waste collection, Craft.ai has used its artificial intelligence model to forecast the exact collection time at each address and to notify building caretakers and specialised companies via the SUEZ platform Monservicedechets.com. This service is now available in the 14th arrondissement.

 

What was the most difficult moment and which result are you most proud of?

The most difficult aspect … nothing that comes to mind.

My proudest moment is taking part in the creation of a real collective effort, a very close-knit team from very different sectors, with Régis from Paris City Hall, Sylvain and Matthieu from Craft.ai and Romain from SUEZ.

If this project was replicated in all cities worldwide …

…less cluttered pavements across the world. In Paris, waste collection trucks operate within an average timeframe of four hours, but we are able to cut this window down to two hours. The impact of this solution if rolled out on a global scale would be significant for the well-being of citizens, who would benefit from the improved cleanliness and accessibility of their streets.

 

Written by:

Edouard Maurel, DataCity Paris Program Manager

 

Read the other article of this serie here!

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