How to monitor and analyse in real time citizens’ voices to ensure that this data drives urban planning?
The way we think about community life is evolving, family units are changing, the ways we work, consume, travel and enjoy time out are shifting, and all this is reshaping the way we relate to cities, individually and collectively. For a city such as Paris, urban innovation is a sine-qua-non to constantly enhance its appeal and accommodate its people’s evolving lifestyles. Paris City Council introduced its Réinventer Paris project to do precisely that.
This project’s partners are hoping this challenge will provide new insights to shed light on Parisians’ behaviour patterns and emerging trends. A solution to analyse data from a variety of sources on a neighbourhood scale could help planners to understand the various ways in which people relate to their surroundings, predict the impact of future developments and strengthen a neighbourhood’s case to attract businesses.
Use cases and experiment field
The discussions and experiments in this challenge will broach the issues from three angles:
Enlightening decisions on neighbourhood planning
The goal, here, is to understand how people living in a given neighbourhood interact with the area. This will involve analysing the existing situation in light of studies based on macroeconomic data and then factoring in dynamic data (residents’ habits, local lifestyles, social interconnections), to inform decisions on how to develop unused space (e.g. with shops, day-care centres, offices, etc.)
The experiment field could be a neighbourhood in the midst of widespread redevelopment, such as Clichy-Batignolles
Attracting new businesses
This will involve furnishing data analysis to help new shops (e.g. bakeries) or other businesses (e.g. day-care centres or office buildings) to fine-tune their approach. The goal is to home in on the type of business that will thrive by analysing accurate and consistent data to map out a business’ precise catchment area
This experiment could target an area embarking on an upswing, such as the 18th, 19th and 20th arrondissements in Paris, or cities skirting it such as Saint Ouen, Montreuil and Asnières sur Seine
Understanding and assessing the impact of permanent or temporary facilities on travel patterns (walking, cycling, etc.) and traffic
The goal, here, is to analyse data reflecting motor-vehicle, bicycle and pedestrian flows to inform decisions that will encourage soft mobility (cycling, walking) and ease motor-vehicle flows
This experiment will take place in Place de la Nation, where Cisco installed movement, presence, pollution and noise sensors in 2015
The partners will supply the following data to conduct the experiment in this challenge:
SFR: travel-related data from mobile devices (technical data from GSM antennas) for a representative sample (approx. 30% of the population), covering uninterrupted periods (24/7) in France (locals and foreigners)
MasterCard: anonymised data from its transaction records, i.e. transaction amounts, user profiles, payment methods (contactless, smartphone or touchpad), geolocations (merchant codes), times and average purchases
Apur: the Paris trade database (BDCom, http://www.apur.org/en/article/database-businesses-and-shops-paris-bdcom) and open-source data ( http://cassini.apur.opendata.arcgis.com/)
Cisco: data from the sensors it installed in Place de la Nation in September 2015 to assess the impact of future developments. It has since gathered a substantial amount of data and will share it with the startups working on this challenge
INSEE: data on its IRIS statistical information clusters, in this case macroeconomic data that may complete the other available data sets
Nexity: complete existing studies with studies leveraging available data to guide its decisions regarding development and planning in new neighbourhoods
Paris City Council: provide businesses with an additional service to help them fine-tune their strategies
La Poste: understand trade flows on a local level and improve its post and parcel delivery network
SFR: extract value from mobile data in an urban-planning use case
The startup: develop technology that urban planners may use to leverage the data from the partners listed above
The selected startup, ZenCity, adapted its product for it to be implemented in France in collaboration with Nexity, as well as with the Paris City Hall, SEMAEST and Apur.
The solution consists of an interface that enables the user to monitor opinions expressed by citizens on all feedback channels, including social networks (Facebook, Twitter), DansMaRue and other sources.
The main dashboard presents the aggregated citizens’ opinion expressed on sourced networks, classified into categories of urban management (such as security, education, public spaces, environment etc.) and specifying if this opinion is positive, neutral or negative. In addition, any user can drill down to actual trends and keywords people use and create alerts on specific categories and/or topics.
More than 300 000 data points collected, including posts, tweet, comments, likes and retweets
171 data sources analyzed for both the 11th arrondissement of Paris and the city of Trappes
13 categories have been added to ZenCity’s product
Creation of a visual dashboard enabling RATP Dev to analyze bus frequentation and sales depending on routes used by the buses.