How Can Lighting System Data Add Value?

lighting data

The talk of data informing design still feels a bit dissonant—perhaps because it conjures images of buildings and spaces that look otherworldly or of a monotonous environment devoid of natural variations.

However, it is important to recognize that the concept of data informing design is already affecting our daily lives, probably more than we realize. How many times have you opted in or out of allowing software to gather information to improve your user experience? Pick up a basket or push around a cart at a big-box store and you may be providing data regarding your path in the store, including how long you stare at the shelves trying to select a loaf of bread among the abundance of options. This data is then used to optimize product layout.

Analyzing the control data for this hospital behavioral health unit demonstrated that the multiple layers of light provided by the different luminaires in different zones were actively used by the occupants, along with dimming.

If software developers and retailers are leveraging data from actual users to improve design, it seems the building industry is missing out on an important opportunity. Although the COVID-19 pandemic did highlight some opportunities to leverage occupancy data for targeted cleaning and ventilation, there are many potential avenues to explore.

Lighting System Data

In the lighting industry, there has been much talk of intelligent, connected lighting systems with limitless possibilities, but given we are still in the early days, these systems likely feel unintelligent and have many limitations. The collection of data by manufacturers is an opportunity to speed the maturing of lighting systems and add value to systems by providing this data to end-users. This initially sounds like a great idea to many end-users, but without the ability to easily use the data, often it just sits on a server somewhere, waiting.

Data detailing the state of the lighting system is increasingly available, either directly from the lighting system or fed from the lighting system to the building automation system. For a recent neonatal intensive care unit (NICU) project, lighting system data was acquired from the building automation system, requiring no additional equipment or hardware. Meanwhile, in a project in a hospital behavioral health unit (BHU), the lighting control system did require a server that was installed onsite for storing the data. These datasets provided insight into how the occupants interacted with tunable lighting systems over days, weeks and months, identifying opportunities for system optimization.

Optimize for the Occupant

Analyzing the control data for both projects demonstrated that the multiple layers of light provided by the different luminaires in different zones were actively used by the occupants, along with dimming. The color of light varied automatically throughout the day in both projects’ patient rooms with occupants having control over intensity but not the color.

Comparison of Button-press Data by BHU Patient Room for the Entire Monitoring Period: Each button pressed is summed by room, ranging from approximately 800 button presses. The data were not normalized by occupancy, and some rooms were less occupied than others.

Although lighting preference is often thought to be random, the data from both projects revealed the patterns of preference in these spaces. For BHU, the security-guard room had the most overrides overall, but these overrides mostly occurred after one of the seven daily transitions, indicating that this particular transition was not acceptable. This nuanced issue, which was clear when analyzing the data, likely would not have been identified otherwise. The data also provide robust feedback over time compared to more traditional methods, such as a survey at one point in time taken by only a subset of occupants.

Optimize for Energy Savings

Data collected in NICU patient rooms revealed opportunities for energy savings by minimizing the extended periods of time when the lights were left on without need. For example, a linear luminaire above each patient bed was the primary light source throughout daytime hours, automatically turning on at 7 a.m. and off at 9 p.m. Six downlights were available in the room for additional light, and selecting the exam mode on the lighting control keypad would turn on these downlights to full brightness. Although the exam mode was specifically intended for patient examinations and procedures, it was often left on for extended periods. Across the six months analyzed, giving occupants control over the lighting system did not result in a considerable increase in energy use. Limiting the duration of exam mode would save additional energy by adding a time-out to the programming of the control system.

Feedback for Best Practice

Lighting control system data provides feedback that is valuable not just for manufacturers and facility managers. Lighting specifiers and designers benefit by learning how the lighting systems are used by the actual occupants of the space, which is particularly important when adopting new technology.

During the design process there are countless decisions made based on what lighting system might get installed and how occupants might respond, yet often after the building is occupied there is no time for actually understanding how well the lighting system supported occupants. Learning how occupants interact with the lighting system allows for continuous improvement, and these lessons learned are essential for strengthening industry best practice documents.

Hourly Lighting Mode Use: Linear Only and Exam Mode ENERGY SAVINGS for the NICU’s five rooms is calculated by identifying extended instances of the exam mode during daytime and nighttime hours (frequency indicated by the bars) and calculating the difference in energy resulting from a switch to the primary linear luminaire only.

As choices and features continue to increase, data help designers and manufacturers clarify what lighting features are valuable, what lighting features are too much and what is the right level of choice for occupants in varying applications.

A Look Toward the Future

The flexibility of advanced control systems is often touted as a benefit, and using data to identify ways to improve system performance takes advantage of this flexibility. Data can help with refinement during commissioning, providing opportunities to ensure that the lighting system is operating as intended. These refinements will be unique to each space, based on the day-to-day activities of occupants. In the case of the NICU and BHU projects, the data revealed opportunities to save energy and adjust to the automatic lighting transitions to better serve the occupants.

Currently, those benefiting from access to actionable lighting system data is limited and more work is needed to expand the perceived value of data to a broader group of end-users. In January 2022, a major U.S. lighting company announced a collaboration with Microsoft to expand its lighting and building controls capabilities. With these types of collaborations likely to increase, it is easy to imagine that the substantial time required to analyze, understand and apply building system data will soon be a remnant of the past.

About the Author

Andrea Wilkerson, Ph.D., LC, Sarah Safranek
Andrea Wilkerson, Ph.D., LC, is a senior lighting research engineer at Pacific Northwest National Laboratory (PNNL), supporting the U.S. Department of Energy Lighting R&D Program. Sarah Safranek is a lighting research engineer at PNNL.

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