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Unlabelled: Thermostats control heating and cooling in homes - representing a major part of domestic energy use - yet, poor ergonomics of these devices has thwarted efforts to reduce energy consumption. Theoretically, programmable thermostats can reduce energy by 5-15%, but in practice little to no savings compared to manual thermostats are found. Several studies have found that programmable thermostats are not installed properly, are generally misunderstood and have poor usability. After conducting a usability study of programmable thermostats, we reviewed several guidelines from ergonomics, general device usability, computer-human interfaces and building control sources. We analysed the characteristics of thermostats that enabled or hindered successfully completing tasks and in a timely manner. Subjects had higher success rates with thermostat displays with positive examples of guidelines, such as visibility of possible actions, consistency and standards, and feedback. We suggested other guidelines that seemed missing, such as navigation cues, clear hierarchy and simple decision paths. Practitioner summary: Our evaluation of a usability test of five residential programmable thermostats led to the development of a comprehensive set of specific guidelines for thermostat design including visibility of possible actions, consistency, standards, simple decision paths and clear hierarchy. Improving the usability of thermostats may facilitate energy savings.
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Facilitating energy savings with programmable
thermostats: evaluation and guidelines for the
thermostat user interface
Therese Peffer a , Daniel Perry b , Marco Pritoni c , Cecilia Aragon b & Alan Meier d
a California Institute for Energy and Environment, University of California Berkeley, 2087
Addison Street, Berkeley, California, USA
b Department of Human Centered Design & Engineering, University of Washington, 407A Sieg
Hall, Seattle, WA, 98195, USA
c Department of Mechanical & Aeronautical Engineering, University of California Davis,
Davis, CA, 95616, USA
d Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
Version of record first published: 25 Sep 2012.
To cite this article: Therese Peffer, Daniel Perry, Marco Pritoni, Cecilia Aragon & Alan Meier (2012): Facilitating energy
savings with programmable thermostats: evaluation and guidelines for the thermostat user interface, Ergonomics,
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Facilitating energy savings with programmable thermostats: evaluation and guidelines for the
thermostat user interface
Therese Peffer
*, Daniel Perry
, Marco Pritoni
, Cecilia Aragon
and Alan Meier
California Institute for Energy and Environment, University of California Berkeley, 2087 Addison Street, Berkeley, California,
Department of Human Centered Design & Engineering, University of Washington, 407A Sieg Hall, Seattle, WA 98195,
Department of Mechanical & Aeronautical Engineering, University of California Davis, Davis, CA 95616, USA;
Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
(Received 30 September 2011; final version received 1 August 2012)
Thermostats control heating and cooling in homes – representing a major part of domestic energy use – yet,
poor ergonomics of these devices has thwarted efforts to reduce energy consumption. Theoretically,
programmable thermostats can reduce energy by 5–15%, but in practice little to no savings compared to
manual thermostats are found. Several studies have found that programmable thermostats are not installed
properly, are generally misunderstood and have poor usability. After conducting a usability study of
programmable thermostats, we reviewed several guidelines from ergonomics, general device usability, computer–
human interfaces and building control sources. We analysed the characteristics of thermostats that enabled or
hindered successfully completing tasks and in a timely manner. Subjects had higher success rates with thermostat
displays with positive examples of guidelines, such as visibility of possible actions, consistency and standards,
and feedback. We suggested other guidelines that seemed missing, such as navigation cues, clear hierarchy and
simple decision paths.
Practitioner Summary: Our evaluation of a usability test of five residential programmable thermostats led to the
development of a comprehensive set of specific guidelines for thermostat design including visibility of possible
actions, consistency, standards, simple decision paths and clear hierarchy. Improving the usability of thermostats
may facilitate energy savings.
Keywords: thermostat; user interface; energy; usability; heuristic evaluation; residential
1. Introduction
Many energy efficient items of equipment or energy reduction measures save energy from the time they are installed,
such as efficient refrigerators or building insulation; however, others require the active participation of an informed
human. Programmable thermostats (that can automatically relax temperatures at night or during unoccupied
periods) have been promoted all over the world to save energy used to heat and/or cool people’s homes. In the US,
where nearly two-thirds (64%) of the residential heating systems use central air, energy for residential heating and
cooling amounts to 9% of the total primary energy use (Energy Information Administration (EIA) 2010, US
Department of Energy (DOE) 2011a,b). A widely used rule of thumb is a savings of 1.8% per degree C (1% per
degree F) for an eight-hour adjustment (Nelson and MacArthur 1978). Yet, programmable thermostats have largely
failed to save energy due to poor ergonomics. A recent literature review (Peffer et al. 2011) uncovered many reasons:
improper installation (e.g. mounted sideways, in dimly lit corridors, too high/too low), poor interface (e.g. buttons
too small, icons/terms not understood) and misunderstanding of how thermostats work in particular and how
heating/cooling systems work in general.
The ergonomics of a thermostat involves understanding its context to analyse the demands placed on the user’s
capabilities during its use. A typical residential thermostat controls the heating and/or cooling equipment, provides
a user interface for the occupant to read current status and adjust the control, and contains at minimum a
temperature sensor to provide control feedback. The thermostat is typically mounted on a wall and wired to the
heating, cooling and/or ventilation system; ideally, this wall is an interior wall insulated from outdoor conditions
and centrally located in the house. The de facto standard in the US for placement of the thermostat on the wall is
1.524 m (60 inches) from the floor. The physical location alone not only affects the functionality of the device (due
*Corresponding author. Email:
2012, 1–17, iFirst article
ISSN 0014-0139 print/ISSN 1366-5847 online
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to the temperature sensor) but several user capabilities, such as reach and vision. In our literature review, we found
examples of programmable thermostats located in inaccessible places (e.g. behind furniture), turned sideways (i.e. to
accommodate the aspect dimensions of the previous thermostat so the users did not have to repaint the wall), too
high or too low to read/access easily, and in dimly lit corridors, precluding visibility.
The human factors of the thermostat also include the user interface, which impacts human vision,
communication, cognition and dexterity. The basic thermostat interface needs to: allow the user to provide a
comfortable temperature (whether heating or cooling), set a schedule for convenience (e.g. heat before getting out of
bed in the morning) and for energy savings (e.g. turn off heat/cool systems when no one is at home or when one is
going out for a few hours or several days; adjust temperatures at night to reduce heating and cooling).
Modern programmable thermostats are following two other consumer electronic trends: from using an analogue
display to digital (and often from graphic to numeric display) and from mechanical operation (e.g. knobs, sliders) to
electronic (e.g. push buttons, touchscreen). In addition, programmable thermostats are increasingly complex,
beyond the base features of setting start and end times for desired temperatures for the day, and days of the week.
Today’s programmable thermostats have more control features and display parameters (e.g. status of filter and
battery, amount of energy consumed).
In general, programmable thermostats do not have much market penetration in the US and have not
conclusively demonstrated energy savings. Although programmable thermostats have been available for more
than 30 years, only 30% of US households have installed them (Energy Information Administration (EIA)
2005c). Several studies indicate that many people do not use programmable thermostats as designed. Only 55–
60% are used to adjust temperatures at night for cooling and heating seasons, respectively (Energy Information
Administration (EIA) 2005b) (Energy Information Administration (EIA) 2005a). Approximately half are in
‘hold’ mode, effectively disabling the programming features (personal correspondence from Raymond Archacki
to Gaymond Yee on the Carrier thermostat mode summary, Summer 2003). Several studies have indicated no
significant savings with programmable thermostats (Cross and Judd 1997, Nevius and Pigg 2000, Haiad et al.
The US Environmental Protection Agency reviewed many field studies and concluded that consumers were not
using programmable thermostats effectively due to programming difficulties and lack of understanding of terms
such as set point (Harris 2008). As a result, the EPA discontinued the EnergyStar programmable thermostat
program in December 2009. Indeed, several recent usability tests with thermostats indicate continued problems
(Karjalainen 2009, Sauer et al. 2009, Combe et al. 2011, Perry et al. 2011), suggesting that the industry in general has
not responded to improve these interfaces nor outlined means of testing them with users. (We note that Consumer
Reports test thermostats in well-lighted rooms with users sitting down.)
While the study of ergonomics specific to thermostats is not new, thermostat manufacturers in general do not
seem to have applied this in their design of thermostats. Thirty years ago, Moore and Dartnall (1982) described
issues such as setting the time on programmable thermostats and Dale and Crawshaw (1983) observed the effect of
font size and controls. A quick review of modern programmable thermostats indicates that not only have the
findings in these early studies been ignored, but also technology has changed dramatically and the functions have
increased in complexity. One hypothesis is that in general, industries have grown from product-driven and
consumer-focused to financially-driven (Foroohar 2011); we can only guess that manufacturers typically balk at the
cost of design of such a mundane device as a thermostat.
We did not find any existing guidelines or heuristics specific to guiding better ergonomics design of residential
programmable thermostats. However, many ergonomics textbooks (e.g. Sanders and McCormick 1993) provide the
basics for visual display, cognition and basic controls. More domain-specific are guidelines on human–computer
interfaces. These are applicable to this study because current programmable thermostats may be described as
embedded devices – having computer systems that are limited in scope and designed to do dedicated functions. The
human–computer interface design realm provides many guidelines, such as on Internet or web interfaces, and even
regarding smart phone interfaces and touchscreens (Nielsen and Molich 1990, Nielsen 1994b, Cooper et al. 2007,
Shneiderman and Plaisant 2009). Two guidelines target commercial building controls (Wyon 1997, Bordass et al.
2007), and one recent guideline was specifically developed for thermostats for offices (Karjalainen 2008). Many of
these latter principles are specific to office buildings and not residential settings.
This study examines several guidelines and uses them to evaluate user mistakes and success performing tasks
on several programmable thermostats in a usability test. We use the guidelines in our analysis of the parameters
of the thermostats that led to errors and confusion as well as those that led to successful completion. In
evaluating what worked and what was missing, we then developed a new set of guidelines for residential
thermostat interface design.
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2. Methods of evaluating interfaces
We reviewed several guidelines for user interfaces to assess their potential for evaluating programmable thermostats.
The first list (Table 1) suggests potentially relevant parameters from a basic ergonomics textbook. These principles
are grouped into those applicable to location, vision, controls and cognitive abilities. While these guidelines may be
generally applied, they are fairly detailed and specific. Many of these guidelines were developed through
measurements, testing and observations of humans.
Table 2 provides guidelines from general device interface usability (Polson and Lewis 1990, Norman 2002), the
computer–human interface realm (Nielsen and Molich 1990, Nielsen 1994b, Shneiderman and Plaisant 2009),
commercial building controls (Bordass et al. 2007) and commercial building thermostats (Karjalainen 2008). These
are grouped horizontally as best as possible to see overlap among the guidelines. These guidelines are fairly
generally applied, and without much detail. The next few paragraphs describe the various guidelines.
The ergonomics guidelines have more specifics regarding the ‘how’ of interface design – where located for best
reach and vision, what kind of display is best for the type of task and the size and type of font. The other guidelines
are more heuristic in nature in providing general design guidance.
Norman, Polson and Lewis provide general device usability guidelines. Norman discusses natural mappings
between the real world and how users think. Polson and Lewis describe attributes of ‘walk-up-and-use’ applications,
which we find particularly appropriate to residential thermostats (Polson and Lewis 1990).
The Shneiderman and Plaisant (2009) and Nielsen and Molich (1990) user interface design guidelines seem
applicable to embedded devices (e.g. visible system status, use of conventions and standards, and minimising errors).
Limitations of embedded devices such as programmable thermostats as compared to general-purpose computers
include limited screen size and dedicated functions (to reach a certain state). This limits the ability of the user to fully
explore or gather data more freely. For example, many programmable thermostats would not be able to support the
help function and wizards typical of most computer software programs.
Bordass et al. (2007) describe end use requirements for more usable controls commonly found in commercial
buildings (such as lighting, fans, windows and thermostats). The Bordass et al. (2007) list provides criteria that are
specific to controls (need for fine control, amount of use), but does not take into account the potential of an
embedded device as a control.
Karjalainen reviewed six different usability guidelines in developing his own guideline for office thermostats
(Karjalainen 2008). He noted in general that the guidelines available do not take into consideration thermal inertia
(e.g. the time delay in reaching the desired temperature), psychological, behavioural and physiological components
of human thermal comfort, the occupant’s lack of knowledge of how the heating/cooling system works, the
occupant’s false idea of comfortable temperatures (e.g. in practice one’s thermal comfort range is much wider than
an occupant often thinks) and the characteristics of heating and cooling systems. Karjalainen provides several
specific guidelines for temperature controls, detailing the type of feedback (both controls and room); he also
suggests providing advice on comfortable room temperatures. Finally, he suggests usability testing as part of the
design process.
Table 1. Relevant parameters from an ergonomics textbook (Sanders and McCormick 1993).
Location Within reach for control and within sight on display, sufficiently lighted.
Visual display Illumination on screen, contrast between content and background, glare, font size and type (segmented
font vs. dot matrix (fewer errors)). Button and switch size and position. Symbol size.
Control interface Fixed scale with moving pointer provides rapid clue of approximate quantity (and relative rate of change)
and set-in quantity (natural relationship between control and display motions).
Compatible/consistent with human expectations (faster learning and reaction time, fewer errors)
Spatial compatibility: physical similarity of displays and controls.
Movement compatibility: (e.g. up arrow or move to right or clockwise indicates increase)
Hierarchy of control (rate/first order vs. higher order control)
Push button for discrete information vs. sliding lever or turning knob for transmitting continuous
Coding controls: shape, texture, size, location, operational method, colour, labels
Push vs. hold down: feel of resistance
Cognitive Alpha-numeric display good for identification and small space, also superior to analogue when a precise
numeric value is required and values are not continually changing.
Symbolic signs preferable if the code symbol has an already fairly universally established association (no
recoding from symbol to words to concept).
Easiest to read straight line scale (vs. curved) with moving pointer and control moves the pointer (Heglin
Ergonomics 3
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Table 2. A compilation of guidelines for more usable interfaces.
Karjalainen (2008)
Shneiderman and
Plaisant (2009)
Nielsen and Molich
(1990), Nielsen 1994b Norman (1990)
Polson and Lewis
(1990) Bordass et al. (2007)
Thermostats in offices Web user interface
Web user interface
General design Walk up and use
Commercial building
control design
Clear and sufficient
feedback after
Offer informative
Give rapid feedback
of intended effect
Visibility, identification
and reachability of
temperature controls
Visibility of system
Make mappings
Make the available
repertoire of
available actions
Give instant, tangible
feedback to
indicate device
Make it easy to see
possible actions
Match between
system and the real
Use both knowledge
in the world and
Keep occupants in the
Make users feel they
are in control
User control and
Be located close to
point of need.
Strive for consistency Consistency and
When all else fails,
Clear way to adjust
room temp.
Tolerate at most one
understand action.
Easy to understand
Acceptable default
Easy to use
Minimise short-term
memory load
Recognition rather
than recall
Get the mappings
Use identity cues
between actions
and user goals.
Not need to be used
too often. Take
into account
occasional use
Adequate and fast effect
on room temperature.
Shared temperature
controls with heating
and cooling systems
Cater to universal
Flexibility and
efficiency of use
Make available
actions easy to
Work effectively
Aesthetic design Design task flow to
yield closure
Aesthetic and
minimalist design
Simplify task
Offer few alternatives. Not require users to
intervene too much
Simplicity of interface Exploit the power of
Require as few
choices as possible.
Prevent errors Error prevention Design for error
Permit easy reversal
of actions
Help recognise,
diagnose, and
recover from
Provide an obvious
way to undo
Informative help Provide help and
Advice on comfortable
room temperatures
Females as test users in
real-life situations
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There is much overlap in these guidelines: easy to use and understand, visibility, need for feedback, aesthetics,
simplicity and not relying on people’s memory in using the device. The latter two guidelines were designed for
commercial buildings, and thus do not consider context and motivation for using the controls from a residential
perspective (e.g. comfort for guests, saving money).
We developed a number of research questions: What can we learn from these guidelines to help evaluate the
usability of programmable thermostats – what is useful and what is missing? Specifically, what element(s) of the
interface renders it easier for the subject to complete the task? What features create frustration and prevent task
3. Research design
In 2010, we conducted a usability study on five commercially-available residential programmable thermostats (three
touchscreen, one web and one button-based – see Table 3), with 31 participants, involving five tasks to evaluate
device usability and effectiveness. Each subject interacted with two thermostats (one at a time) installed at a height
in the lab typically seen in most US houses. The details of the test and usability metrics developed to evaluate the
devices’ usability and the users’ effectiveness at performing common thermostat tasks are described in Perry et al.
(2011). A video recording of each session was used to input numerous categories of data including task completion,
time on task, function path (buttons and function interactions), interaction motions (press, slide, hold, etc.),
interaction errors and experimenter observations regarding users’ confusion during the task.
This study looked at each trial, defined as a subject attempting one of five tasks on a given thermostat, to
determine what parameters led to good versus poor usability. We used the guidelines to categorise these parameters.
We analysed each subject’s actions during successfully completed tasks compared with non-completed tasks
(included tasks not completed or not successfully completed). In addition, we observed the path length to complete
each task and the total time on task, either to complete the task or ending time when the task was not successfully
We developed tasks reflecting the typical functions of programmable thermostats. The most important were:
ability to turn on/off heating or cooling, temporarily turning up or down heating or cooling, checking the current
and target temperatures, setting time (and changing time at the beginning and end of Daylight Savings Time) and
adjusting systems to use less energy when one is away. These tasks were also chosen in consideration of their effect
on residential energy consumption. The five tasks finally selected for this study are in Table 4.
Table 3. Description of thermostats tested.
Device Type Description
BTN Buttons/ Button-based programming; full cover over device; user instructions on cover; 7-day
HYB Buttons with
Hybrid of touchscreen (primary programming), switches under a cover (heating and cooling
controls), and button for lighting; 7-day programming; ability to view past energy usage.
TCH Touchscreen Touchscreen with black/white display; 7-day programming.
SMT Smart with
Smart WiFi enabled device; full-colour LCD touchscreen; 7-day programming; quick save
WEB Web portal Web platform; 7-day programming; synched with wall device.
Table 4. Description of tasks.
Tasks Description
Set heat Set the thermostat to HEAT mode. (Setting was OFF at the start of the task).
Set time and day*# Set the thermostat to the current day and time. (The time settings were programmed to Monday at
12:00 am for the start of the task.)
Current setting Identify and read aloud the temperature that the thermostat was set to reach at that current time.
Future setting Identify and read aloud the temperature that the thermostat was set to reach at a future period
(Thursday at 9 pm). (No need to change any settings).
Vacation/away/hold Set the thermostat to maintain the same temperature during a five-day period when one is away.
Note: *not performed on the WEB because time settings could not be modified. #setting the day not performed for the TCH because this required
a code from the manual.
Ergonomics 5
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4. Analysis of existing designs
This section describes the success rate and time on task for subjects for each thermostat per task. Success refers to
accomplishing the stated goals of the task; time on task marked the ending time for each task, when the subject
stated that he/she was finished (whether successful or not). We note here that there were cases where the subject felt
he/she had completed the task correctly, but in fact were unsuccessful, cases where the subject was not sure whether
he/she had completed the task correctly or not, and cases where the subject clearly gave up, not knowing what else
to do to complete the task. The development of the time and success metric is outlined in Perry et al. (2011); another
complementary study looked at optimal path length – the minimum number of button pushes and other actions
required to complete the task (Pritoni et al. 2011). We also show time for incomplete tasks; this includes subjects
verbally stating he/she was finished with the task (whether or not he/she had completed it) and incorrectly
completing the task. For each task we describe various elements of the interfaces that seem to contribute to success
and timely task completion as well as those that created confusion and difficulties. Figures 1–5 show annotated
pictures of the thermostats.
Figure 1. Button thermostat (BTN).
Figure 2. Hybrid thermostat (both touchscreen and buttons/switches) (HYB).
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4.1. Task 1: Set thermostat to HEAT mode
This was considered to be the easiest task; the optimal path length – the shortest series of actions necessary to
complete the task – ranged from 1 to 4 (see Figure 6). In general, the best performing thermostat interface was the
web interface – 100% of the subjects completed this task, and all under 30 s. However, the worst performing
thermostat only had a 46% success rate.
The two thermostats with the highest success rate had the ‘switch’ visible at the home screen/default level. With
the worst performing interface (HYB), the switch was hidden by a small cover, with no affordance or design features
that hint that it was in fact openable. The BTN interface also had a cover; perhaps because the cover was larger led
Figure 3. Touchscreen thermostat (TCH).
Figure 4. Smart thermostat (touchscreen with Home button) (SMT).
Figure 5. Web portal as a thermostat interface (WEB).
Ergonomics 7
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to better recognition by subjects. For the SMT thermostat, one had to go into the Details menu. Besides not being
able to find the switch, other problems included confusion over the correct switch (between fan (ON-AUTO) switch
and heat switch (OFF-HEAT)
, and confusion over what is the current setting (e.g. the thermostat is currently in
heat mode or off) versus whether system is on (e.g. furnace is currently producing heat).
4.2. Task 2: Set time and day
For task 2, the WEB interface was exempt, since its time and day stamp came from a networked computer. The
Touchscreen (TCH) interface performed the best, with 100% of subjects completing the task, however a few subjects
took more than two minutes to complete the task (see Figure 7).
One major problem was not finding the place (whether button or menu) to change the day/time. The
TCH model had a Clock button at the home/default level. For the HYB, one could either press on the
current time and day display to change or go through the Menu to Set Time/Day; both used up or down
arrows on the touchscreen to change, but the Menu editor required saving by pressing ‘Yes’. However, for the
SMT interface, one had to press the More button, then Settings, then Preferences to get to the clock function,
then eight more button presses to finish the task. The BTN interface had the day/time button under a cover. In
addition, subjects were confused whether they were setting universal time or time/day for a programmed
temperature schedule. In general, subjects found it tedious to set time because each button push only
incremented the time by one minute; if one held the button down, the time would scroll faster, but this was not
4.3. Task 3: Identify current target or ‘set to’ temperature
This task showed a wide disparity among the thermostats with subjects performing well on three thermostats and
poorly on the other two (Figure 8). Three devices showed the current temperature and the target temperature
setpoint in the main screen. The information was presented clearly, with labels indicating ‘set to’ or ‘set temperature’
for the temperature setpoint compared to ‘current’, ‘inside’, ‘room’, or ‘current temperature,’ but some of the labels
used were quite small.
Figure 6. Time on task, success rate, and ideal path length for Task 1: Set to heat.
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Figure 7. Time on task, success rate, and ideal path length for Task 2: Set time and day.
Figure 8. Time on task, success rate, and ideal path length for Task 3: Identify current target temperature.
Ergonomics 9
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A common problem was in navigation: subjects were confused how to get to the temperature setpoint. For the
Button (BTN) thermostat interface, one either immediately grasped the procedure or not at all; the target
temperature was accessed from pressing either one of the up/down arrow push buttons that one would use to change
the setpoint – not an obvious means of control. The Hybrid thermostat allowed one to press the screen where the
current temperature was displayed to access the target temperature – again, not an obvious or natural connection.
One common error was the subject providing the current temperature instead of the set or target temperature,
especially for the devices where only one temperature was shown (BTN and HYB). Another common error was the
subject providing the set or target temperature for the wrong time of day.
4.4. Task 4: Identify future target or ‘set to’ temperature
This task required the subject to identify a target temperature for a time in the future, and thus subjects had to look
at the programmed schedule. The best performance came from using the web interface with a 71% completion rate.
However, subjects had difficulties completing the task with the other thermostat interfaces (Figure 9).
The main problem was that subjects did not know how to access the schedule of time and temperatures. Three of
the five interfaces tested had a means of viewing the schedule; for the others, it was necessary to enter the ‘Edit
Program’ mode. The WEB interface had the schedule on the home screen, so this was the most accessible; the SMT
had a button labelled ‘program’ on the home screen and the TCH had a button labelled ‘Sched’ for Schedule. The
thermostat on which subject performed the worst (BTN) had a panel covering the program button and had serial
access to this data, meaning that one had to scroll through all days of week and all time modes; one couldn’t skip to
the desired time. In addition, only the start time for each period was indicated, and if one passed the setting for the
desired time, one could not go backwards. Access using the HYB thermostat required several steps pressing areas on
the touchscreen: first pressing Menu, and then pressing the Scroll button to find Set/review heat programs and then
selecting Yes, and then pressing the Next button to go through each day’s four time modes (MORN, DAY, EVE,
NITE) until one reached the desired day/time. The best performing thermostats (WEB and SMT) had a two-
dimensional graphic depicting day/time and temperature in a tabular form; the web interface provided information
on single schedules just by hovering with the cursor over the calendar.
Figure 9. Time on task, success rate, and ideal path length for Task 4: Identify future target temperature.
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4.5. Task 5: Set for away/vacation
The final task asked subjects to set the thermostat for the condition that the house would be unoccupied for several
days. Subjects using the WEB interface performed reasonably well, with 75% completion. Subjects using the
Touchscreen (TCH) and Smart (SMT) interfaces were less successful. Less than half of those using the Button
(BTN) interface were able to complete the task, and only one subject using the Hybrid (HYB) interface completed
the task – taking 5 min to do so (Figure 10).
For each thermostat, there were a few different ways of completing this task. Three thermostats (WEB, SMT
and BTN) had a ‘vacation’ or ‘away’ or ‘energy savings’ mode; all five had Hold modes, in which one could change
the temperature setting and ‘hold’ it. Ironically, the thermostat with one of the shortest path lengths (HYB) posed
the most challenge; one had to press on the word Hold on the screen and then the current temperature display to
change the setpoint, but there is no affordance to suggest that Hold is in fact a button and is touch sensitive. Many
subjects tediously changed the setpoints for all days and all time modes in the day. A common error was not saving
properly, so the changes were lost. In general, subjects were confused regarding the terms/functions temporary
override, timed hold, permanent hold, permanent override, away and vacation.
4.6. Application of the guidelines
Some guidelines are meant to be applied in the field, and did not apply to our lab test of the programmable
thermostats, such as location and feedback from the effect of the equipment. Other guidelines we did not
explicitly test, such as glare, font and icon size. As was shown in Table 2, many guidelines were similar. We
attempted to group and summarise the most pertinent and applicable guidelines. Table 5 shows this reduced set
of guidelines and shows how each thermostat fared accordingly. We evaluated the parameters of each
thermostat that seemed to correspond with successful and timely completion or incomplete and longer time on
task. We categorised them according to each guideline. Positive examples of each guideline are labelled with a
plus sign (þ) and shaded in grey; examples that violate the guideline are labelled with a minus sign (7). Blank
cells merely indicate that the thermostat did not clearly provide a positive example nor a violation of the
Figure 10. Time on task, success rate, and ideal path length for Task 5: Set for away/vacation.
Ergonomics 11
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Table 5. Application of the guidelines to each thermostat.
Programmable thermostats
Ergonomics of visual
display and controls
(Sanders and
McCormick 1993)
þþ Slide pointer across
fixed scale to adjust
Touchscreen arrow
‘button’ to adjust time
and temp
þþ Slide pointer across
fixed scale for temp7
Fixed pointer/ moving
scale for time
Push arrow buttons to
adjust temperature or
Touchscreen arrow
‘button’ to adjust
temperature or time.
Visibility of available
(Polson and Lewis 1990)
Norman 2002,
Consider occasional use
(Polson and Lewis
1990, Nielsen 1994,
Norman 2002,
Bordass et al. 2007,
Shneiderman and
Plaisant 2009)
þmultiple windows,
þlarge screen 7Many actions not
available on home
7cover hides system
switches and
programming buttons
7too many modes of
7serial programming
Feedback from controls
(Karjalainen 2008,
2009, Bordass et al.
2007, Shneiderman
and Plaisant 2009)
7Touchscreen not
always responsive
þActual buttons
(responsive feel)
þaudible beep when
Match between system &
real world (Nielsen
Use of natural
mappings. (Norman
Consistency and
standards (Nielsen
1994, Norman 2002,
Shneiderman and
Plaisant 2009)
þDe facto switch standard: heat-cool-off and auto-on for fan.
þþ drag setpoint on
analogue scale
þUp/down arrow
þþ drag pointer to
change setpoint on
analogue scale
þUp/down arrow
Up/down arrow
‘buttons’ only on
selected screens
þtabular format for
visualising day/time/
temp setpoint
7Menu labels not
þtabular format for
visualising day/time/
7Use of abbreviated
words (VACA for
Vacation) and terms
7Scroll ‘button’—scroll
bars more typical
7menu button (not
drop down)
7Not clear what is the
‘button’ on the
touchscreen and
what is merely text.
7Inconsistent: Press
current time to
change but press
current temperature
to see set temp
User control and
(Shneiderman et al.
1988, Nielsen 1994,
Karjalainen; 2008,
þok button 7‘hold/return’ button
is exit and next, no
way to cancel
7yes instead of ok
12 T. Peffer et al.
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Table 5. (Continued).
Programmable thermostats
Error prevention,
recognition, recovery
(Polson and Lewis
1990, Nielsen 1994,
Norman 2002,
Shneiderman and
Plaisant 2009)
7no confirmation 7if one didn’t press yes
to save, the
programming was
lost, with no
Flexibility and efficiency
of use (Norman 2002)
Work effectively
(Bordass et al. 2007)
þpop-up balloons to see
þHold down button to scroll faster (although not
þone touch buttons for
energy use/comfort
mode during day
þTwo means of setting
7some settings require
removing from wall
Aesthetic and minimalist
design (Polson and
Lewis 1990, Nielsen
1994, Norman 2002,
Bordass et al. 2007,
Karjalainen 2008,
2009, Shneiderman
and Plaisant 2009)
þcolour, graphics þcolour, graphics 7switches, a button
and touch screen
7three font types
(segmented, dot
matrix, stroke)
þlarge touch screen
þdifferent sized fonts,
larger for oft-used
þbacklight for easier
Help and documentation
(Nielsen 1994,
Karjalainen, 2008,
þwizard þ/7instructions on
inside cover (but
Ergonomics 13
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5. Discussion
Several of the interfaces were complicated and difficult for users to understand, leading to frustrations and major
barriers for completing the tasks. The data from the usability test (successful completion, time to complete and
ending time for incomplete tests) provided a means of evaluating the devices as well as probing the causes of
problems and keys to success. Another measure that combines efficiency, ease of use, and few errors was actual path
length compared to the ideal path length. In general, we assumed that a successful completion of a task meant the
subject found the interface usable from a strictly functional point of view – in the case of this lab test, perhaps easy
to learn was the key usability attribute.
Subjects performed better with some displays than others, and this varied by task. For example, subjects using
the WEB display in general performed well. However, the WEB display is a special case in that it is not an
embedded device, and has more capability (e.g. larger screen, familiar menu driven display). While more and more
thermostats include control by smart phone and tablets, we anticipate that some sectors of the population will
always require a stand-alone, simple, non-networked device. Some of the elements of the WEB display can be
developed in embedded devices, such as the tabular display of temperature, time and day. We found all thermostats
provided attributes that supported guidelines; even the least usable device had positive qualities, such as a
responsive touchscreen that provided feedback and hierarchy of display. The variability in performance in general
across thermostats and tasks indicates a variety of solutions for usability; we do not develop these guidelines
towards a ‘one size fits all’ solution.
Many of the guidelines were quite useful in understanding the ease or difficulty with which subject completed
each task. One of the most important guidelines appeared to be the visibility of available options, associated with
walk-up-and-use applications. For example, the cover or door on two thermostats seemed to reduce performance in
hiding a few of the available options. Users got lost when the action choice was not available on the home screen,
and the terminology of the choices was not clear (e.g. setting the time on the Smart thermostat). Arguably, a cover
may make the thermostat more aesthetically pleasing with a more simplified appearance; however, in this case, the
manufacturers could certainly provide better affordances to indicate that a panel or door is openable and how to
open it.
Another pertinent guideline was consistency and standards. Both the Touchscreen and Hybrid thermostats had
touchscreens; however, with the Hybrid thermostat, the ‘buttons’ did not look like buttons. For example, only one
subject was able to figure out the Hold function with the Hybrid; this may also reflect the lack of familiarity with
this term. This also seemed to affect setting the day and time using the Hybrid (73% completion vs. 100% for the
Touchscreen). In general, the terminology was neither standardised across thermostats nor natural or familiar;
terms such as settings or setpoint, current, and hold seemed to create confusion. The Hybrid also was inconsistent in
operation. For example, one could press on the time or day to set the time or day, but pressing on the current
temperature provided the target temperature. It was difficult to know which words were touch-sensitive or not.
Lack of feedback was another common issue. Many users made errors when they failed to save changes. There
was no confirmation prompt (e.g. do you want to save?) as is so common in computer interfaces. Previous studies
have shown feedback on user behaviour is vital to performance as well as satisfaction (Sauer et al. 2007).
Several issues were not addressed by the guidelines. More important than the path length (i.e. number of total
actions) was a broad and shallow decision tree (Shneiderman 1988), that is, having many options available at first
glance, and not very many ‘layers’ or levels of choices (e.g. a menu (level 1) with xchoices, each of which (level 2)
have ychoices, each of which (level 3) have zchoices and so on). Each decision point represented a chance to get
lost. Of course, the ‘width’ of the decision tree at the first level is not infinite; further studies may suggest a practical
limit of the number of choices to keep the interfaces simple. For example, many web designers state that it takes
longer to make a decision when presented the option within a large set of options versus a smaller set (attributed
erroneously as Hick’s Law) (Seow 2005, Johnson 2010).
One issue not fully addressed by the guidelines was in navigation, or knowing where one was. A common
example was when the subject was confused between whether he was in edit mode and actually making changes to
the scheduled program, or just viewing the scheduled program.
With respect to improving visual aesthetics and reducing cognitive load, another issue is the development of a
clear hierarchy, so that the most often used functions are the most prominently displayed, such as having the largest
font; less often used or perhaps functions for expert use might be buried but accessible down a level or two.
Both navigation cues and a clear hierarchy would complement the wide and shallow decision tree. These
attributes would help prevent the user from getting lost, and thus develop more confidence about the interface.
The unique challenge of embedded devices such as programmable thermostats is that they are not full-fledged
computers (with all the attention given to human–computer interfaces), but they have more functions than ‘dumb’
14 T. Peffer et al.
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controls. As programmable thermostats evolve, we see larger screens and touchscreens, but this study shows that
these do not ensure usability. Compounding the issue is that the number of functions seems to be increasing (an
example of feature creep), which aggravates usability issues.
However, a positive development one author notes is the return of the moving pointer-fixed analogue display as
a more intuitive mode of understanding the difference between the setpoint and current temperature (Peffer 2009).
Thermal comfort is subjective and relative (de Dear and Brager 1998, American Society for Heating Refrigerating
and Air-Conditioning Engineers (ASHRAE) 2004), so an analogue display output suits this purpose; a temperature
setpoint is a discrete number, which suggests a digital input.
The categorisation of thermostat attributes according to each guideline was qualitative and arguably subjective;
a related analysis showed that the combined quantitative measure of time to complete and success rate was a good
proxy for usability of the thermostat per task (Perry et al. 2011). While a usability test and single metric can provide
feedback to manufacturers on existing and prototyped thermostat designs, a new set of guidelines specifically for
residential thermostat interfaces can inform these designs to begin with, as a proactive approach rather than
6. Recommendations
Our general recommendations include visibility of available options on the home screen, a wide and shallow
decision tree, navigation cues, clear hierarchy of display, consistency and standards, natural mappings, error
prevention and recovery, and feedback. We recommend that usability testing be part of the design process. More
specific recommendations include the following:
.Include all important and often used actions at the home level; consider no covers or clearly provide
.Use a graphic tabular form to view the temperature setpoints for the time of day and day of week.
.When possible, include confirmation prompts (e.g. do you want to save?), or some other means of confirming
when something is edited or changed.
.Use plain English wherever possible (no abbreviations) and standard icons.
.Use clear affordances
For touchscreens, buttons should look like and act like buttons
If required, covers should be clearly marked so they look ‘openable’.
Specific recommendations by Karjalainen include providing a clear way to adjust room temperature and
detailing the type of feedback: there should be an adequate and fast effect on room temperature, and clear and
sufficient feedback to the user after the temperature adjustment. He suggests acceptable default settings and
providing advice on comfortable room temperatures. Finally, he suggests usability testing as part of the design
process, especially including females.
7. Conclusion
While programmable thermostats are theoretically capable of saving 5–15% of energy to supply heating and cooling
for residences, in practice, they save little to no energy due primarily to human factors issues. We reviewed several
design guidelines intended to improve ergonomics and usability from various fields. Many of the guidelines
converged, promoting visibility, feedback, consistency and standards, natural mappings, and recovery from errors.
After conducting a usability study with 31 subjects with five programmable thermostats in a lab setting, we used
the converged guidelines to analyse the usability attributes of the thermostats. We answered several research
questions. Some guidelines seemed more important to task completion than others. Both positive examples and
violations of guidelines were critical to examine with respect to thermostat display usability. Finally, we developed
guidelines to describe some issues not covered by the set of guidelines we used. Several guidelines proved vital to
usability such as visibility of available actions, feedback, and consistency and standards; subjects had the highest
success rate of task completion with the thermostats that embraced these guidelines. Missing guidelines included
navigation cues, clear hierarchy, and wide and shallow decision trees; these are useful in completing desired actions
with confidence and preventing users from getting ‘lost.’
Improving the usability of thermostats must draw upon traditional proven ergonomics principles, with emphasis
on quantitative measurements, detailed specifics on types of suitable controls and analysis in developing a more
Ergonomics 15
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holistic and quantifiable approach to design heuristics. As such, we embrace both qualitative proactive approaches,
such as developing specific heuristic guidelines for residential programmable thermostats, as well as quantitative
approaches, such as our previous work in developing usability metrics to provide a single quantitative measure of
usability. At the same time, new techniques are needed to both assess and solve the unique problems related to
embedded controls. We recognise that improving the usability of programmable thermostats may only represent one
step towards facilitating energy savings, but it is a vital one. Finally, we anticipate these heuristic guidelines may be
applied to other devices to facilitate energy savings, such as dishwashers, audio–visual equipment and water heaters.
We wish to thank Jessica Granderson, Dhawal Mujumdar, Becky Hurwitz and Margarita Kloss for their contributions.
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... Thermostats that control HVAC systems are employed in about 85% of households; thus, they represent an opportunity for saving energy at home. Initial approaches for saving energy through connected thermostats are presented with gamification techniques [18,19], data analysis [20], behavior analysis [21], and usability of interfaces [22][23][24]. ...
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Rental properties make up approximately 37% of the US residential building stock and are responsible for 23% of the total energy consumption in this sector. Although this market has great potential for energy efficiency, the implementation of energy savings measures in this market faces numerous challenges. In particular, one of the main challenges cited is the split incentive, limiting the potential motivation of rental property owners and tenants to invest in energy-efficient technologies. Smart thermostats have gained substantial interest and adoption in the past decade and have been the subject of numerous studies. However, their adoption and use in the context of the rental housing market has not been considered. In this study, reviews posted on an online retailer's website (Amazon) were used as an unstructured source of information to evaluate the attitudes of landlords and tenants toward smart thermostats. In total, 31,790 reviews were collected for 14 commercially available smart thermostats; from these, 173 reviews were identified as directly associated with rental units. These selected reviews were then analyzed and categorized based on the unique opportunities and challenges that were expressed. The majority of reviewers focused on usability aspects and expressed an interest in the advanced remote-control functions of their purchased devices. Furthermore, our findings indicated that occupancy pattern learning capabilities were not of particular interest among this user group. These findings can inform product manufacturers and policy makers in their future interactions with stakeholders in the rental housing market and potentially increase adoption and hence energy efficiency.
Smart thermostats differ significantly from traditional devices and are quickly becoming commonplace in homes. Literature demonstrates that thermostat interfaces greatly influence user interaction and related energy outcomes. Moreover, how users imagine their device to work appears to have a greater impact on usage than how the system functions. Previous work investigated manual and programmable thermostats in this context, employing user mental models (UMMs) to analyse user understanding. Since then, thermostats have developed significantly. This paper presents a novel investigation of smart thermostat UMMs. It employs contemporary methods to construct ten UMM diagrams, and three detailed case studies, contextualized with previous findings. All participants demonstrated feedback theory. Case studies highlight common misconceptions. Overall, smart thermostat UMMs appear to enable effective usage; however, some users are overwhelmed by the complexity, limiting engagement and use of features (e.g. programming).
Smart plugs are attracting attention as smart devices that enable energy savings by providing functions such as standby power cut-off, energy usage monitoring, and remote power control. The majority of research on smart plugs has applied a technology-focused approach to improve efficiency and performance, but a user-centered approach is also required. Regardless of the method used to apply advanced technologies, energy savings cannot be expected if users are reluctant to use smart plugs owing to difficulties in use. Therefore, it is essential to improve the usability of smart plugs through the application of user-friendly design to promote energy-saving behaviors. This study aims to suggest methods to improve the usability by facilitating affordance perception and actualization of smart plugs. To achieve this, we first examined the concept of affordance and presented the role of informational and physical elements in perceiving and actualizing affordances. Thereafter, we constructed a checklist for facilitating affordance perception and actualization of smart plugs after reviewing several guidelines and design principles for usability improvement. Subsequently, we conducted in-depth interviews with 26 smart plug users to explore user experience (UX) for the checklist items. Finally, based on the interview results, we suggested a design direction for smart plugs that facilitates the perception and actualization of affordances.
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U.S. residential thermostats control approximately 9% of the nation's energy use. Many building codes now require programmable thermostats (PTs) because of their assumed energy savings. However, several recent field studies have shown no significant savings or even higher energy use in households using PTs compared to those using non-PTs. These studies point to usability problems that lead to incorrect use and wasted energy. However, the lack of clear, consistent metrics has hampered the acceptance of usability concerns by thermostat manufacturers. Thus there is a need for metrics specific to PTs that manufacturers can use to evaluate their products. In this paper, we report on the results of a usability study conducted on five commercially available PTs and the development of four new metrics suitable for use in evaluating thermostat usability. Our study confirmed usability deficits in the current generation of PTs and showed the metrics are correlated with each other as well as agreeing with the qualitative results of the study.
Technical Report
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The adaptive hypothesis predicts that contextual factors and past thermal history modify building occupants' thermal expectations and preferences. One of the predictions of the adaptive hypothesis is that people in warm climate zones prefer warmer indoor temperatures than people living in cold climate zones. This is contrary to the static assumptions underlying the current ASHRAE comfort standard 55-92. To examine the adaptive hypothesis and its implications for Standard 55-92, the ASHRAE RP-884 project assembled a quality-controlled database from thermal comfort field experiments worldwide (circa 21,000 observations from 160 buildings). Our statistical analysis examined the semantics of thermal comfort in terms of thermal sensation, acceptability, and preference, as a function of both indoor and outdoor temperature. Optimum indoor temperatures tracked both prevailing indoor and outdoor temperatures, as predicted by the adaptive hypothesis. The static predicted mean vote (PMV) model was shown to be partially adaptive by accounting for behavioral adjustments, and fully explained adaptation occurring in HVAC buildings. Occupants in naturally ventilated buildings were tolerant of a significantly wider range of temperatures, explained by a combination of both behavioral adjustment and psychological adaptation. These results formed the basis of a proposal for a variable indoor temperature standard.
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Electrical utilities worldwide are exploring "demand response" programs to reduce electricity consumption during peak periods. Californian electrical utilities would like to pass the higher cost of peak demand to customers to offset costs, increase reliability, and reduce peak consumption. Variable pricing strategies require technology to communicate a dynamic price to customers and respond to that price. However, evidence from thermostat and energy display studies as well as research regarding energy-saving behaviors suggests that devices cannot effect residential demand response without the sanction and participation of people. This study developed several technologies to promote or enable residential demand response. First, along with a team of students and professors, I designed and tested the Demand Response Electrical Appliance Manager (DREAM). This wireless network of sensors, actuators, and controller with a user interface provides information to intelligently control a residential heating and cooling system and to inform people of their energy usage. We tested the system with computer simulation and in the laboratory and field. Secondly, as part of my contribution to the team, I evaluated machine-learning to predict a person's seasonal temperature preferences by analyzing existing data from office workers. The third part of the research involved developing an algorithm that generated temperature setpoints based on outdoor temperature. My study compared the simulated energy use using these setpoints to that using the setpoints of a programmable thermostat. Finally, I developed and tested a user interface for a thermostat and in-home energy display. This research tested the effects of both energy versus price information and the context of sponsorship on the behavior of subjects. I also surveyed subjects on the usefulness of various displays. The wireless network succeeded in providing detailed data to enable an intelligent controller and provide feedback to the users. The learning algorithm showed mixed results. The adaptive temperature setpoints saved energy in both annual and summertime simulations. The context in which I introduced the DREAM interface affected behavior, but the type of information displayed did not. The subjects responded that appliance-level feedback and tools that provided choices would be useful in a dynamic tariff environment.
Overview of Energy Production and Consumption Energy can be defined as primary energy or secondary energy depending on the intensity of use and type of fuel source. Primary energy includes forms obtained from four types of conventional energy resources: (1) crude oil and natural gas; (2) coal; (3) nuclear energy (from fission of radioactive elements); and (4) hydropower.
This paper describes the results related to space heating and thermostat use from a study of owner-occupied, single-family residential housing in Wisconsin conducted by the Energy Center of Wisconsin in 1999. We find that the average self-reported winter thermostat setting does not vary substantially by type of thermostat used, is predictive of heating energy intensity in a way that is consistent with expectations, and appears to be a good indicator of actual thermostat-setting behavior, assuming that the goal is to compare the behavior of households rather than to gather an accurate report of their actual thermostat settings. We also find that attitude toward energy conservation appears to have an indirect effect on household heating energy intensity by way of thermostat-setting behavior. The results offer further evidence in support of including social and behavioral variables in traditional engineering-based studies.