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CARBON, ENERGY AND THE
ROLE OF UBICOMP
Adrian Friday
Lancaster University

School of Computing
and Communications

Thursday, 2 December 2010

OUTLINE

• Stimulating behaviour change w.r.t. sustainability and energy
use is a hot topic

• Aim is to explore energy use and GhG externality further

• Present some of the well known exemplars from the
Ubicomp literature

• Stimulate discussion on what might make a difference


FORTHCOMING ARTICLE
IEEE Pervasive Special Issue on Smart Energy Systems


DEMAND MANAGEMENT
http://caniturniton.com/


CHANGING BEHAVIOUR


FEEDBACK DISPLAYS of
Fig. 1 Examples of initial design ideas for visualization
Stringer, 2007
energy consumption in the home.

We then went back to several of the households that had

enviro
tangib
mecha
regard
displays provide the feedback untimely or
to we
is difficult to understand. It requires the u
mental efforts to translate the available in
into appropriate actions. Furthermore, the
PEEM
is not presented in the context where it is
of ene
i.e. when interacting with the home applia
environment. Therefore the feedback lack
enviro
tangible link to the consumers’ behaviour.
when
mechanisms also frequently have shortcom
regard to long-term effectiveness,of fee
as initia
to wear off once the novelty effect is over
3 Examples for ambientno ab
energy feedback: Power
AMBIENT FEEDBACK
PEEM therefore aims at improving achiev
Aware Cord (top), Energy
the com
of energy feedback by seamlessly effect
Orb (middle), Energy
integrat
Gustafsson/ Martinez,2005theClockand providing it w
environment of
AWARE
user
(bottom) expec
when it is most useful and efficient. Such
Broms, 2006 could increase the comfort of
of feedback
no abstract translation and explicit attenti
Thursday, 2 December 2010 The m

sustainable in-the-moment decision-making.

Figure 6: The “Ambient Canvas” kitchen backsplash display.

REWARDING THE RIGHT BEHAVIOUR
Conclusion
While we realize that information and ubiquitous
“Themay play a powerful role in encouraging
technologies
Ambient Canvas”, Bartram, 2010
conservation, the design of these systems for effective
home use faces critical challenges. We are exploring

settings. In addition, the resident can configure energy- Feedback
optimizing “modes” as presets in ALIS controls. For
example, turning off most lights and lowering the
thermostat in “Sleep mode”, or tuning settings and
shutting down standby power in “Away” mode. These
presets can be activated either by one button from any
ALIS control interface (such as the mobile phone or
embedded touch panel — Figure 2) or scheduled for
panel planned activation. For example, in a prototype
currently under development, a smart alarm clock by
ntrol
the bed can wake both the resident and the house (by
d one-
right).
putting the latter into Home mode). Note that these are
re presented as examples: modes are entirely user
configurable, and coexist with individual control
settings for fine-grained control when desired.

Controls differed slightly in North and West House(s).
In North House, we added override controls for the
Figure 3: The ALIS dashboard indicates daily usage statistics
sophisticated internal and external automated shade and provides uncomplicated data visualizations for at-a-glance
systems that tracked the sun, and extra state awareness of resource consumption. It also conveys tips
information to show the house was in “automated” or related to usage data and displays residents’ progress toward
“manual” mode. Visitors to North House were intrigued community challenge goals.

by the efficiency of the automated shading system, but ALIS provides a variety of feedback displays and
uncomfortable with the idea that if they wanted to analytical tools. Detailed information on resource
change the behaviour (for example, to open shades to production and consumption is available in real-time
read a book) they had to suddenly “manage” the house and historical views, categorized in different ways (by
control system. They struggled with a model of how the

RAISING AWARENESS
type of device, by location in house, by time of use).
system worked, with what “optimal” and “non-optimal” We have integrated Pulse Energy™ software for
modes represented, and with how they might balance detailed performance analysis and prediction (Figure
their needs with the apparent state of the system. In a 4). These detailed views complement an Overview

DEHEMS/Bartram, 2010
21


PRODUCT
CurrentCost, DIY Kyoto, Enistic, e.g. http://www.diykyoto.com/


MAKING FEEDBACK WORK
• According to Midden, 1983

• Feedback should be immediate;

• concrete and signiﬁcant (units, money); and,

• meaningful (one use or from comparable situation)

• McCalley, 2002 add

• salience (e.g. feedback integrated with a task, e.g. washing clothes)

• identify goal setting as highly effective (~20% savings)


n 500KHz.
g
d
e
e
h
r
h
f
e

Figure 2: Frequency spectrogram showing device actuation in
a home.
DISAGGREGATION USING SINGLE POINTshowing
Figure 2 shows a frequency domain waterfall plot
SENSING
appliances being turned on andPatel As is evident from the
Electrisense, off. 2010
graph, when the device is turned on we see a narrowband
continuous noise signature that lasts for the duration of the

ally polls the meter’s

gure 1. User interface accessing real-time metering data
MOBILE FEEDBACK
Weiss, 2009


SUSTAINABLE BEHAVIOUR?


CARBON VS. ENERGY
GhG externality is a time varying phenomenon


REAL TIME CARBON
http://realtimecarbon.org/


Fig. 2 The prototype Pollution e-Sign
POLLUTION E-SIGN

• What role for Ubicomp
then?

• To measure, inform, nag,
share, embarass, challenge,
engage in play, stimulate
enquiry?
• Hooker, 2007


MAKING AN IMPACT
Defence,
education and
health and social Other
10%
services Household fuel
11% 13%

Household
Water and Vehicle fuel
Sewage 10%
2%
Construction Household
Electronic / 6% electricity
computers / 9%
appliances
4% Personal air
Textiles and travel
Food and 8%
clothes
drink (from
2% Cars
shops)
Paper and 12% 5% Other Personal
Hotels, pubs
printing and catering transport
1% 4% 3%

• Typical UK person emits 15 tonnes CO2e


HONG KONG RETURN:
4.6 TONNES
!"#$$%&'$("))*+$ 12*34.*$$ ,-./$0%&'$("))*+$
'&5$("))*+$

67")"89$ :-3+($7;4++$


ASPARAGUS (250G PACK):
2KG
!"#$ )4-+5(-$ =*(.$
%&'$($ &$6($ >?'$6($

!"758$9:; )*+$
<-5<":$ ,+-*(./-0$
,+"1$2-+3$


A RED ROSE:
350G
!"#$% 12345%6/$7.% &-4)%
8#$9%:".;0% <=>%?4%

6#$9%;$*#% &$'()$*+",%-.%
40#,".% &$//0.,%


A BURGER:
2.5KG
!"#$ ./012'0$ ()'*$
%&'$ 3,-$&'$ +,-&'$

40'')0$ 7$89$:*00;0$
561'01$ <61'01$


IDENTIFYING TARGETS
• Reduce flights - better communication?

• Change your commute/ cut your mileage/ avoid congestion

• Get an efficient small car next time or ride share

• Cut food waste, seasonal food, food with low carbon miles

• Go vegetarian, eat less meat

• Simple efficiency measures (insulate, cut drafts, boiler, lightbulbs) - use energy
more effectively, cut waste

• Buy less, buy quality, by more locally, look after it, mend it, freecycle it


MORE EFFICIENT BUSINESSES?
• Online sales account for 10% of the total retail sales in the UK

• 65 million online purchases (12%) weren’t delivered ﬁrst time, with 2%
failing to be delivered at all

• £682 million of direct costs will be borne by consumers, retailers and
carriers due to Internet shopping delivery inefﬁciencies (£1.26 per
purchase)

• Can we exploit delivery to one’s social network?

• Can Ubicomp help us be more aware of the downstream impact of our
choices and behaviours?


THANKS TO
Mike Berners-Lee, Small World Consulting
http://bit.ly/9gBwDt

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