Intelligent street lighting

 

 

Using geostatistics to adapt street light to actual needs

A solution for adapting street lighting to peak and off-peak time, along with a web app for the visualization of energy savings.

 

 

 

// OUTCOMES & KEY RESULTS

The solution was based on data aggregation and modelization, then allowed for street lighting adaptation and data visualization. The technology used anonymized and aggregated data from SFR mobile network, and urban streets and travel data coming from the open database of Paris city.

 

The experimentation took place in Paris 13th district

 

// PARTNERS INVOLVED

Partners provided the following data sets: street lighting facilities data as well as  anonymized geo-located data from mobile devices.

Two startups teamed up to tackle this challenge, Quantmetry - a data science consulting company and  Dataiku provides a collaborative data science platform to prototype and deploy solutions.

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// PAIN POINT & OPPORTUNITY

In Paris and other cities, street lights stay on at night even though they could be dimmed when there are fewer people about or brightened for specific events.

 

 

 

 

This solution will be of interest for any company operating urban infrastructure and willing to sharpen its competitive edge by providing a wider choice of urban services and connected objects, including upgradable dynamic lighting.

 

 

 

 

 

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A program designed by NUMA in partnership with the City of Paris