For the last few years, the most aggressive marketing around lighting has involved digital lighting...Read Article
An MIT Researcher Came Up With A Good Way to Assess Street Lighting. Here’s the Next Step.
When the folks at MIT recognize the issue of poor street lighting, you know it’s moved to the mainstream. A data scientist named Summit Kumar, an MIT grad, came up with a way to map street lights easily. Essentially by mounting cameras, light meters and GPS devices to vehicles already driving the streets, like police cars and garbage trucks, they were able to map which street lights were working and which ones weren’t. This kind of data set eliminates the need to schedule inspections of street lights, since in theory you would already know where outages are.
When I read this story in Citylab, it struck me as a good first step in street light assessment, a way to get a baseline. But this is no way to actually run a city. There is a better way.
Street lights today are typically installed with a photocell in the NEMA receptacle. This triggers the light to come on automatically at night. But today, that NEMA receptacle is capable of so much more.
Today the sensor you install in the NEMA receptacle of an LED street light can:
- Report Fixture Failings
- Track Hours Used
- Dim fixtures for energy savings and to manage citizen complaints about glare.
- React to Emergency situations
So imagine a situation where a street light fails for one reason or another. With a reactive system, an automatic error report would be generated. Then the database could inform you that the drivers for that block are reaching their end of life meaning, so it might be a good idea to replace those drivers while in the area.
That could be the future of street lighting. A connected intelligent system that can react to everything from tropical storms to a resident’s glare complaint.
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