ENGIE Laborelec uses AI to design public lighting with a focus on biodiversity.
Smart Street Lighting with a Focus on Biodiversity
Smarter and faster public street lighting procurement, with an important role for biodiversity data. With this goal in mind, technology consultant ENGIE Laborelec and geodata specialist GIM developed an AI pilot project that maps ground cover and lighting points.
Towards sustainable street lighting
It is well known that street lighting has an impact on biodiversity. However, when planning new street lighting, the right data to take this into account is often missing. ENGIE Laborelec, an innovation expert in electrical energy, wants to change this. Together with GIM from Merkator Group, its research and innovation department developed a methodology that engineers can use to help lighting providers and public authorities make the transition to more sustainable outdoor lighting, with biodiversity information in mind.
“The use of the AI model has two objectives,” explains Yvan Sacovy, Lighting Expert at ENGIE Laborelec. “On the one hand, we want to systematically take biodiversity and light pollution into account. On the other hand, we aim to speed up the design of high-quality lighting solutions that focus on safety, comfort and minimal energy consumption.”
Paved and unpaved Surfaces
For this pilot project, Merkator Group deployed a GeoAI model that automatically maps ground cover and lighting points.
Yvan Sacovy: “This map classifies, on the one hand, the lighting points and, on the other hand, the ground cover, distinguishing between paved and unpaved surfaces. We then use this output to derive certain parameters about the environment around the lighting poles, such as streets, waterways, land use and so on. This makes it possible to provide lighting that is tailored to the needs of users while at the same time taking the immediate surroundings into account.”
The test concept has already been applied to two different types of imagery: orthophotos and satellite images. Yvan Sacovy: “The initial results are very promising. We are now looking into how we can further translate this methodology into an operational tool.”
The AI tool makes it possible to provide lighting that is safe and comfortable, energy-efficient, biodiversity-friendly and tailored to each specific environment.
Yvan Sacovy, Lighting Expert at ENGIE Laborelec
