SmartLight.ai is bringing the emerging technology of the Embedded Artificial Intelligence (TinyML/AIoT) to public infrastructure to help authorities reach their Net Zero goals. Its first product - currently in development - is a means to autonomously control urban street lighting at the point of illumination, autonomously optimising lighting levels to the surrounding environment though Computer Vision algorithms, then distributing this information over a network. The patent-pending solution takes the form of a device mounted to each streetlight.

This solution will address the five key urban challenges; Energy Usage/Carbon Emission, Running Cost, Light Pollution, Safety, and Night-time Economy by focusing light energy where/when it is required, and dimming in areas/periods of inactivity.

Local authorities have a need to address these five key urban challenges as part of their Net Zero goals. Today, there are few cutting edge solutions which address these challenges utilising any kind of emerging technology.

The market today is dominated by large, slow-moving organisations, providing "smart lighting" through Central Management Systems (CMS), which utilise simple IoT technologies, which represented cutting-edge technology 20 years ago. Firms offering the service include large organisations such Telensa, Engie, and Phillips Lighting/Signify. They are common in large metropolitan areas, which can afford the monitoring overhead.

There exists a strong demand for a new system which utilises emerging technologies such as AIoT.

SmartLight.ai was successful in proving Early Feasibility under "The Sustainable Innovation Fund: SBRI" project. This focused on laboratory-based feasibility.

This project will build on an existing capability by proving Enhanced Feasibility in this project. It will show that the same technologies which worked in a laboratory setting, are now robust enough to work with real world data and inputs.