The Art and Science in Determining Occupancy

Posted by Dalkia Solutions on Oct 18, 2015 6:26:42 AM

Four years ago Nest introduced one of the biggest home energy efficiency devices since the on/off switch.  And while many think the rounded iPhone-like thermostat with a Wifi-connection was the invention, its revolutionary feature was really the integrated motion sensor.

Yes, Nest’s easy-to-use interface mocks earlier un-programmable “programmable” thermostats.  And its cloud algorithms make your home’s HVAC smarter, learning as you turn the dial to set points that compete with outside air temperatures.

But the motion sensor creates the most value.

As a proxy for occupancy, it allows the thermostat to become a set and forget system.  Occupancy data, connected to the cloud, enables trained decision making, for comfortable settings when you’re home.  But the bulk of energy and dollar savings come when the sensor says you’re not home, and it dials down HVAC, only turning on again when you return.

And this leaves homeowners to do what they do best:  Nothing.

Motion sensors are typically based on one of two technology types, Infrared or Ultrasonic.

Infrared uses a signal like your line-of-sight, point and click TV remote.  To determine occupancy the sensor watches for when its signal gets interrupted.  Gaming platforms like xBox use this as well.  Historically infrared has been lower cost and flexible, allowing the use of different lenses for aiming these signals.  Narrow beam lenses capture activity at the entranceway to a store while wider beam lenses scan open warehouse floors.

Ultrasonic sends out high frequency sound signals, like bats using echolocation, studying the reflected signals for changes as a sign of occupancy.  Your car’s parking assistance sensors are ultrasonic.  The technology works well where line of sight is challenging, like bathroom stalls, but the signals fade in rooms bigger than 3000 cubic feet.  To get more reliable coverage, manufacturers also offer products that combine both Ultrasonic and Infrared in one device.

Today’s commercial and industrial building operators are more frequently relying on sensors for determining occupancy.  They’re making a gradual transition from older, time-based schedules that were configured into building management systems, but didn’t adapt to the dynamic activity levels within a hotel, office, store, warehouse or manufacturing site.

But sensing networks aren’t foolproof either.  Their designs must fit that particular business, in that particular facility and work reliably for its operators and occupants.  Its both art and science.

The science says to layout a facility’s network design, put sensing where it will observe activity and watch as lower occupancy driving higher energy savings.  The art says false negatives are bad (occupants caught in the cold or dark) while false positives are more acceptable (running when no one is there.)  But false positives use more energy.

Like Nest works for homeowners, our engineer’s goal is a set and forget system.

Recently we performed an occupancy study in a 200 room Embassy Suites hotel.  The owners were interested in actual room occupancy compared to how many guests had checked in.

Our team first installed motion-based data loggers recording guest activity in several sample two-room suites.  The results showed checked-in guests were actually in their rooms only 65% of the time.  The energy savings opportunity from adding Nest-like HVAC and lighting control would be significant.

But as interested as the owners were in savings, they needed to know that sound-sleeping hotel guests wouldn’t wake up in a sweat because their air conditioner had shut off.

For the installation we used the wireless system from Telkonet, leveraging their motion sensing thermostat linked to its network for tracking rooms across the whole site.  This allows hotel managers to pre-cool or heat rooms on check in, remotely change sensor timeout settings or get ahead of HVAC maintenance issues where a system is never turning off.  The room sensors were located in places where they could “see” the bathroom, bedroom and living areas, assuring complete coverage within the suite of rooms.

Another hotel room approach involves using contact sensors on the door, coupled to motion sensing in the room.  If the door opens first, then trips the room sensor, the guest must have entered the room.  In the reverse, the guest has left.  The problem comes when your wife goes for a run while you’re still sleeping.

In warehousing our engineers have learned that site managers have their own requirements for how LED upgrades leveraging occupancy detection will work best for their operation.

Some don’t want the PacMan effect, where LED lights turn on one-by-one following forklift drivers as they navigate warehouse aisles.  They may prefer us to configure zones, where lights operate as a group, or leave unoccupied areas to slowly dim to 10% levels, never going completely dark.  The effect produces a more pleasing nightlight glow across the facility, at the expense of additional kilowatt hours..  Our teams re-run their savings models for managers to choose configurations knowing the tradeoff costs up front.

At one facility we studied the performance of our Digital Lumen’s LED upgrade one year after it had gone live, drawing occupancy data from their LightRules wireless control system.  The scatter plot showed over a million points of data, and enabled our team to visually display additional savings to be extracted if the system was reconfigured from 15 minute to 2 minute timeouts.  With forklift drivers hitting aisles on average 4 times an hour the lighting in certain areas never shut off.  But with a change to 2 minute timeouts the lighting would remain on only 8 minutes of every hour.

Beyond motion, our team has applied other sensing technologies to address varying occupancy.

In retail and grocery stores, ventilation systems are often designed assuming every day is Black Friday, running high volume fresh air changes even when the store is unoccupied.  Obviously shoppers have peak and down times, producing more CO2 in busier periods which then needs to be ventilated.

Our team adds a grid of sensors to measure actual CO2, controlling ventilation for optimal fresh air management, hence the name, demand control ventilation or DCV.  These sensor additions are low cost, but have the potential to produce significant energy savings, especially for larger stores.

As sensing technologies continue to get smaller, cheaper and more sophisticated it will only get easier for our team to weave together solutions that sit in the background, do their job and make decisions based on a 99.9% confidence of true occupancy.  The goal continues to be matching energy consumption to occupancy, going up and down together, but minimizing negative impacts to the business.

And we’ve come a long way.

Remember the Clapper?  We can all laugh thinking back to the 1980’s TV commercial with a women sitting in her bed, clapping her hands to sound activate turning the lights off and on.  But the patented gadget has survived the test of time, still selling on Amazon.

And the technology even does a pretty reliable job with just the clap of your hands.  Unfortunately it also activates when your dog barks.

Topics: Measurement and Verification, Occupancy