Measuring the Value of Occupancy Analytics
One of the best methods for smart buildings to regulate themselves, from lighting to climate control, is to track occupancy levels, to identify how your building is used. Important variables to report on include what rooms and areas are used and when, as well as how many people are using those spaces.
This practice, known as occupancy analytics, will prove to be essential for smart building programs. Understanding how your building is being used enables your programs to optimize many facets of building operations based on the use.
Use & Disuse
One of the core offerings of smart buildings is enhanced energy efficiency and heating and cooling are some of the most energy-consuming building processes. According to a factsheet from Australia’s Department of the Environment and Energy, a typical HVAC system accounts for 40% of a building’s energy consumption and 70% of base building consumption.
Managing for energy expenditures is one of the primary value propositions of smart buildings and the best method for doing so is by tracking occupancy. Understanding what rooms are used and when enable your smart building to much more effectively heat or cool different areas.
Just as occupancy tracking informs climate control, it can also inform lighting programs. According to Regency Lighting, energy expenditures account for 77% of overall lighting costs. Understanding the flow of people throughout a building can help optimize lighting and drive down that cost center.
As well, occupancy analytics can enable better office layouts that allow more exposure to natural light, which has well-documented positive effects on worker productivity.
If your office employs hot-desking, measuring occupancy can inform optimized layouts and expeditious desk assignments on a daily basis. End users of hot desk programs waste less time finding an open desk and more time being productive.
When cleaning crews arrive at the end (or beginning) of the work-day, their routes can be optimized on across the long-term or on a daily basis. There’s no sense in loud vacuum cleaners disrupting any teams working late and clean out the empty offices first.
Concerns Worth Tracking
Occupancy analytics offers a host of benefits, real and potential, but also incurs some downside risks to manage.
The obvious problem to running such a smart building program is the energy costs necessary to operate sensors, sometimes in an always-on capacity. A barrage of sensors monitoring a space on a near-constant basis is surely not a desirable line item, sure to run up the power bill.
Identifying and deploying sensor arrays that don’t consume a lot of energy would solve for the energy issues, as would optimizing the timing and triggers for the more energy-intensive components.
The thornier issue surrounding occupancy analytics is privacy. It’s to be expected that the standard employee or visitor doesn’t want to be tracked throughout the entire day. Storing any sort of identifiable occupancy data also poses additional headaches to manage for security teams since regulation on this data is likely murky.
Designing a robust occupancy analytics requires a careful eye to the notion of privacy. Deploying Bluetooth or NFC check-in procedures would probably not be the best option, nor would actual cameras. Observing router use to determine network usage by location could be more anonymous, but still holds privacy concerns and risks gross inaccuracy because different tasks require different bandwidth and the strategy leaves out offline work.
Instead, smart building designers might want to consider a new rig coming from researchers at Purdue University. They’re developing a sensor for carbon dioxide that can calculate the amount of people in a room.
Operating on microelectromechanical technology, the sensor consists of two parts. The first piece measures the presence of CO2 by film-coated plates changing their vibration frequency when the film absorbs the gas. These changes then trigger the second component, which actually calculates the amount of people present.
This bifurcated sensor system requires very little energy to operate, while also protecting against serious privacy intrusion.
It’s worth evaluating the costs and benefits of occupancy analytics and finding a system that optimizes the gains against the concerns, especially as more and more smart buildings enter the market.