AI & Lighting

LpR 73 Article, page 62: Recently, Artificial Intelligence has emerged as an evolutionary force in almost every industry, demonstrating its potential to radically change existing processes. In common literature, AI is interchangeably used with Machine Learning for which various tools have already become commonplace. Henri Juslén, D.Sc (tech.), Chief Future Illuminator, Omar Nasir, M.Sc (tech.), Data Scientist, and Javad Nouri, M.Sc, Data Scientist at Helvar Oy Ab discuss AI on the context of the lighting industry where the scope of applications of AI is similarly quite broad, impacting the various stages involved in the lighting life-cycle such as design, installation, commissioning and configuration.

The lighting industry commonly employs novel techniques in lighting design and control. Major transformative changes within the industry include the evolution of the light bulb and the introduction of inter-networked lighting components that implement protocols such as DALI. Recently, Artificial Intelligence has emerged as an evolutionary force in almost every industry, demonstrating its potential to radically change existing processes. In common literature, AI is often interchangeably used with Machine Learning for which various tools have already become commonplace. In the context of the Lighting Industry, the scope for applying AI is intriguingly broad, impacting the various stages involved in the lighting life-cycle such as design, installation, commissioning and configuration. For example, a self-learning network of lighting components can communicate and set up itself without requiring human intervention similar to auto commissioning systems used in the IT industry. This will decrease the time needed to commission new lighting installations. By observing and measuring indoor environments, an AI based lighting system can optimize and tune light parameters accordingly to impact user experience and well-being. The utility of such a system is not limited to end users or tenants but extends to other stakeholders, such as building owners and facility managers as well. A data-driven network of lighting components continuously generates data which is collected and stored at a centralized server. AI algorithms can be designed to run at the source component, such as a sensor, for decentralized, real-time decisions, or at a server for making centralized decisions. Furthermore, the collected data can be utilized for other Building Management Systems (BMS) such as Heating, Ventilation and Air Conditioning (HVAC), or access management. However, the technology is not without its caveats. Cameras augmented with AI can detect precise occupancy and movements in a room or space, but the visual feed would require strict adherence to privacy laws. Another significant challenge is the limited human understanding of AI, which impedes its speed of adoption as well. In summary, paying attention to privacy, there are a lot of opportunities for applying AI within the lighting industry with significant impact to improved user experience, comfort, productivity and ultimately profitability.

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