ENERGY CONSERVATION THROUGH SOCIAL COMPETITIONS

IN BLOCKS OF FLATS

Andreas Kamilaris, Giannis Kitromilides and Andreas Pitsillides

Department of Computer Science, University of Cyprus, Nicosia, Cyprus

Keywords:

Energy Conservation, Social Competition, Energy Awareness, Case Study, Blocks of Flats, Social Inﬂuence,

Smart Metering, Smart Power Outlets.

Abstract:

Buildings are responsible for a large fraction of the world’s total electrical consumption. Energy awareness

of residents, by means of timely electrical consumption feedback through smart metering, aims to reduce the

waste of energy. Further savings can be achieved by leveraging social norms and entertainment to drive sus-

tainable behavior. In this paper, we investigate two important pillars in the energy saving initiatives, which are

the recreational aspect and the social inﬂuence of the neighborhood. We performed a small case study in two

blocks of ﬂats, creating a social competition among the ﬂats, to award those with the best energy management.

Our evaluation results indicate that energy-related social games have the potential to contribute signiﬁcantly

in reducing the electricity footprint of home residents, engaging them in more sustainable lifestyles.

1 INTRODUCTION

Increasing energy demands, depletion of natural re-

sources and rising costs proliferate the concerns about

rational energy management. Buildings consume a

large proportion of the world’s total electrical energy

(Europa Press Release, 2008). More than 30% of all

greenhouse gas emissions can be attributed to houses

and buildings. Predictions denote that by the year

2030, the global energy demand will more than dou-

ble, rising up the energy-related green gas emissions

by 55% (International Energy Agency, 2007).

According to technological and psychological

studies (Darby, 2006), (Seligman et al., 1981), timely

electrical consumption feedback through smart meter-

ing, is believed to reduce electrical consumption by a

fraction of 5-15%. Smart meters are sensor devices

that record consumption of electrical energy in fre-

quent intervals. Enabling residents to monitor their

electricity footprint in real-time using visualization

tools, allows more intelligent energy management.

In general, people are willing and capable to adapt

their behavior to energy-saving lifestyles if given the

necessary feedback, support, and incentives. Even

though energy awareness through real-time feedback

has contributed in more rational utilization of elec-

tricity, we believe there still exists some margin for

further energy conservation.

While detailed usage of energy makes people

more aware about electricity, the inﬂuence of the

community by means of comparisons with other peo-

ple’s consumptions, has the potential to drive resi-

dents towards a more persistent behavioral change

(Cialdini, 2001).

In general, social context can be very inﬂuencial

for people (Allcott, 2011). Social norms can moti-

vate people to question their behavior, if they dis-

cover it is not ”normal”. Residents generally learn

from their neighbors and receive encouragement and

support. Receiving daily feedback and taking energy-

saving actions in a social context can increase peo-

ple’s effectiveness (Ehrhardt-Martinez et al., 2010).

In this paper, we investigate whether a social com-

petition towards efﬁcient energy utilization between

neighboring ﬂats, can help residents increase their en-

ergy awareness and reduce their electricity footprint.

Thus, we explore two relatively new parameters, re-

cently introduced in the energy conservation domain:

entertainment through a social game and the social

inﬂuence of the neighborhood. We aim to study the

effect of the community in affecting people to save

energy, but also recreation as a means to make resi-

dents more interested about their electrical consump-

tion. We believe that commitment by means of a com-

petition can help people ensure that their actions are

consistent with the common beneﬁt.

In the rest of the paper, we describe the social

competition we developed, discussing our ﬁndings

167

Kamilaris A., Kitromilides G. and Pitsillides A..

ENERGY CONSERVATION THROUGH SOCIAL COMPETITIONS IN BLOCKS OF FLATS.

DOI: 10.5220/0003950301670174

In Proceedings of the 1st International Conference on Smart Grids and Green IT Systems (SMARTGREENS-2012), pages 167-174

ISBN: 978-989-8565-09-9

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

from a small case study involving two blocks of ﬂats,

one in an urban area and another at a suburb.

2 RELATED WORK

Energy conservation is a global issue and numerous

techniques have been proposed for saving energy in

houses and buildings. Some of these techniques in-

clude energy awareness through real-time feedback

(Darby, 2006), (Seligman et al., 1981), utilization of

sensors and actuators for energy-efﬁcient home au-

tomation (Barbato et al., 2009) and deployment of

camera networks to obtain occupancy and usage pat-

terns of residents, in order to intelligently control the

lighting and HVAC system (Erickson et al., 2009).

Furthermore, various studies examined the behav-

ior, preferences and habits of residents, to assist them

then towards saving energy. Some of these studies in-

clude understanding the conﬂict in the landlord/tenant

relationship (Dillahunt et al., 2010) and perceiving

how householders manage their consumption of natu-

ral gas, electricity and water (Chetty et al., 2008).

The social inﬂuence of the community was recog-

nized as an important factor in energy saving initia-

tives. People who are forced to cooperate to achieve

a common goal tend to form a trust between them,

inﬂuenced by their actions (Cialdini, 2001).

As an example, OPOWER company exploits so-

cial norms to inﬂuence people conserve energy, by

sending energy report letters to residential utility cus-

tomers, comparing their electricity use to that of their

neighbors (Allcott, 2011). According to the company,

this practice has reduced consumption by 2.0%.

StepGreen.org leverages online social network-

ing sites to promote energy-saving behaviors of users

(Mankoff et al., 2010). SocialElectricity is a Face-

book application that allows people to compare the

electricity footprint of their street with that of their

friends, or their own consumption with that at their

neighborhood/village/town (Kamilaris et al., 2011a).

The ﬁrst social competition for energy conserva-

tion took place at Louisiana State University, through

the UNPLUG project

. This was a competition

among campus communities to see who could reduce

energy consumption the most. Students were edu-

cated and encouraged to conserve energy. Nine cam-

pus communities, housing altogether 4,800 residents

participated in the competition, yielding an average

3.7% reduction in energy consumption over a one-

month period. The reduction translated to a savings

of $2,470.

http://unplug.lsu.edu/

Figure 1: System Infrastructure.

Our work, partly motivated by the UNPLUG

project, targets a social competition in residential

blocks of ﬂats, to investigate also the neighborhood’s

social inﬂuence to the overall energy saving practice.

In contrast to the UNPLUG project, we provided the

residents with continuous electricity-related (indirect)

feedback, giving them incentives to win the competi-

tion, saving energy and money.

3 A SOCIAL COMPETITION FOR

ENERGY CONSERVATION

To motivate people become more aware about energy

and reduce their electrical consumption, we created a

social competition between neighboring ﬂats in large

residential blocks. In the next subsections, we explain

our methodology for realizing this competition.

3.1 Technical Details

For acquiring the electrical consumption of each

ﬂat in real-time, we employed Plogg

smart me-

ters equipped with external current transformers for

loads up to 100 Ampere. Ploggs are high-accuracy,

ZigBee-based wireless metering devices, which mea-

sure whole-home or device-speciﬁc energy consump-

tion. We attached one Plogg to the mains meter of

every ﬂat, which communicated wirelessly the elec-

tricity data in JSON format to a laptop computer that

received them by means of a Telegesis USB stick.

We installed on the computer the Web-based smart

home application framework described in (Kamilaris

et al., 2011b), (Kamilaris et al., 2011c). The frame-

work was responsible to parse the electricity-related

http://www.plogginternational.com/

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data, extract the important information and forward

them to a Web server and a Microsoft SQL Server

database. The Web server was developed in C# and

ASP.NET, tightly coupled to the online database. The

system infrastructure is illustrated in Figure 1.

3.2 Feedback and Services to Residents

Through the Web server, residents could authenticate

themselves and get informed in real-time about their

overall ranking in the competition, according to their

electricity footprint. They could also view their his-

torical electrical consumption at the previous days of

the competition, as well the overall electricity con-

sumed by the block. All information about electricity

is translated to money costs, based on the current tar-

iffs of the electric utility.

Our aim was to motivate tenants to reduce their

own energy consumption, but also to acquire energy

awareness for the whole block, contributing to the

overall reduction of energy. We believe that peo-

ple generally respect the sense of social engagement

and coherence and this helps them keep commitment

over time (Passy and Giugni, 2001). In our case, the

block’s community becomes engaged to the goal of

reducing the total electricity consumed.

We did not want to inform people in real-time

about their own consumption, so as to focus our study

most on the social competition as a way to save en-

ergy.

Our Web site included a forum, where people

could communicate and exchange tips about energy

saving practices and techniques. After some requests

from residents, we also developed a Facebook appli-

cation, showing real-time information about the com-

petition and a Facebook group, in which residents

were encouraged to discuss about the study.

For those residents who were not familiar with the

Web, we updated every day the ranking of the com-

petition, together with brief reports about the energy

performance of the building, in a notice box located at

the main lobby. We anticipate that when activities be-

come pervasive, integrated into daily life, strong par-

ticipation in social actions is more likely (Kuznetsov

and Paulos, 2010).

3.3 Rules and Conditions

We decided to elect the winning ﬂat, as the ﬂat that re-

duced most effectively its electrical consumption. To

mitigate the possibility that residents could consume

much energy in the ﬁrst few days just to reduce it then

and win the competition, we asked them to provide us

with electricity bills from previous months. By ana-

BuildingConsumptionChart1

Page1

100

120

13579111315171921232527

Day of Month

Energy Consumption (kWh)

Temperature (C)

Energy Consumption

Temperature

Figure 2: Everyday Electrical Consumption of the whole

Suburban Block.

lyzing the bills, we obtained a complete report of each

ﬂat’s energy performance.

Our award to the winning ﬂat was a real-time en-

ergy monitor from Current Cost

. These smart meters

are convenient in installation and use.

The duration of the competition was one month

for each block. In the middle of the competition,

in case there were any ﬂats with high electrical con-

sumption, we decided to inform their tenants about

their energy use and discuss possible ways to reduce

it. In this way, they could become more energy-aware.

Finally, to achieve more complete evaluation, we

prepared questionnaires, which we distributed to the

residents after the competition.

4 CASE STUDY IN BLOCKS OF

FLATS

Our case study included two blocks of ﬂats. The ﬁrst

is at a suburb, having 10 ﬂats and the second in an

urban area, having 20 ﬂats. In the following sub-

sections, we present the ﬁndings of our case study in

these blocks.

4.1 A Block of Flats at a Suburban Area

The ﬁrst block had 10 ﬂats and was located at a sub-

urban area, 10 Km from the city. Six ﬂats accepted to

participate in the competition, counting in total 10 res-

idents. Two ﬂats refused to collaborate, an old woman

in another ﬂat could not understand our study, while

in one ﬂat the landlord was absent abroad. The ages

of the participants are listed in the ﬁrst row of Table 1.

The total energy performance of the block, as a sum-

mation of the electrical consumption of all the partic-

ipating ﬂats, is depicted in Figure 2.

http://www.currentcost.com/

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Table 1: Age Distribution of Residents.

No. Block Flats Residents 18-25 26-35 36-45 46-55 56+

1 Suburban 6 10 2 6 2 - -

2 Urban 20 29 10 12 4 3 -

100

200

300

400

500

600

700

101 102 103 202 302 303

Flat Number

Energy Consumption (kWh)

Previous Month

This Month

Figure 3: Electrical Consumption Comparison with the Pre-

vious Month for each Flat at the Suburban Block.

Observing the ﬁgure, we can see the strong corre-

lation of daily temperature to the energy consumption

of the building. This is clear evidence that a consider-

able percentage of consumed electricity is utilized for

heating.

Because of the high dependencies to temperature,

we can not extract safe conclusions about the energy

savings due to the competition. However, we can just

mention, comparing the ﬁrst two weeks of the study

with the last two, that the energy consumption in the

last two weeks is reduced by 260 kWh or 26%. Fur-

thermore, in days with similar temperature (e.g. days

10 and 25), the energy consumption towards the end

of the month is reduced by 22%.

The study at this block was conducted in Febru-

ary, 2010 with average monthly temperature 11.60

◦

Celsius and humidity around 63%. Our ﬁndings show

that there not exist different consumption patterns in

weekends than in weekdays. Comparing with the

electricity bills of the ﬂats in January, 2010, as shown

in Figure 3, most of the ﬂats have reduced effectively

their electricity footprint. Flats located on higher

ﬂoors needed more heating and consumed more elec-

tricity. For better comparisons, we normalized the

energy-related results of February.

Considering that the average monthly tempera-

ture in January was very similar to February, around

11.56

◦

Celsius with humidity 67%, we strongly be-

lieve that the social competition has inﬂuenced the

participating ﬂats to reduce their consumption. Only

one ﬂat had increased its consumption. The average

reduction of energy is 11.90%. For our comparisons,

it would be better if we could had found the electric-

ity bill of the same month last year, however, this was

not possible.

100

150

200

250

300

350

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Day of Month

Energy Consumption (kWh)

-1

Temperature (C)

Energy Consumption

Temperature

Figure 4: Everyday Electrical Consumption of the whole

Urban Block.

In the middle of the competition, we discussed

with the tenant of ﬂat 302 and asked him why he was

consuming so much electricity. He explained to us

that he was not willing to sacriﬁce his comfort to save

energy and money, as he did not encounter ﬁnancial

problems. He was not really motivated to contribute

in protecting the environment.

The winners of the competition were a couple

around 30 years old, living in ﬂat 303, who reduced

their electrical consumption by 41%! They both

found this competition as a ﬁrst-class opportunity to

save money.

4.2 A Block of Flats at an Urban Area

The second block had 20 ﬂats and was located in an

urban area, near the middle of a city. Surprisingly,

all ﬂats, counting 29 residents, accepted to participate

in our study. We estimate that this happened because

most of the residents were young, educated people,

enthusiastic with the idea of a social competition on

their block. The ages of the residents are listed in the

second row of Table 1. The total energy performance

of the block is presented in Figure 4.

Also in this case, energy consumption is strongly

correlated to temperature conditions. Comparing the

ﬁrst two weeks of the study with the last two, the en-

ergy consumption in the last two weeks is reduced by

1091 kWh or 33%. Since in the second week of the

competition there was a signiﬁcant drop in tempera-

ture for 5 days, our conclusions can not be accurate.

We can notice that in days with similar temperature

(e.g. days 7 and 26), the energy consumption towards

the end of the month is considerably reduced, of the

order of 13%.

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200

400

600

800

1000

1200

1400

1600

101 102 103 104 105 106 107 201 202 203 204 205 206 207 301 302 303 304 305 306

Flat Number

Energy Consumption (kWh)

Previous Month

This Month

Figure 5: Electrical Consumption Comparison with the Pre-

vious Month for each Flat at the Urban Block.

This study was conducted in March, 2010 with

average monthly temperature 13.00

◦

Celsius and hu-

midity around 59%. In Figure 5, we compared the

electrical consumption of each ﬂat with the consump-

tion at the previous month (February, 2010), as indi-

cated at their electricity bills.

From the ﬁgure, we can see that all ﬂats have re-

duced their consumption signiﬁcantly. Impressively,

the average energy reduction reaches 27.74%. An im-

portant factor for this reduction is the average increase

of temperature in this month by 2

◦

Celsius. Once

more, residents leaving on the third ﬂoor needed more

heating and consumed more energy.

During the competition, we gave notice to resi-

dents of ﬂats 102, 203, 303 and 305 about their in-

creased consumption. The tenant of 102 was a stu-

dent who had computer equipment working 24/7, and

he could not do much about it. Using more energy-

efﬁcient infrastructure was out of his budget. We dis-

covered that three tenants lived at ﬂat 203, while most

of the other ﬂats had only one tenant. Finally, the ten-

ants of 303 and 305 wanted their ﬂats warm the whole

day and they earned a good salary to afford that. Nev-

ertheless, all reduced their consumption, as we can

conclude from Figure 5.

A 31-years-old woman, staying at ﬂat 303, was

the winner of this competition. She managed to re-

duce her electricity footprint by 43%, and she was re-

ally proud of this, because she believed she helped

protecting the environment.

5 DISCUSSION

Our ﬁndings suggest that social competitions can

inﬂuence residents to reduce remarkably their con-

sumption. We discuss in the following subsections

our general observations and experiences from the

case study.

100

200

300

400

500

600

700

800

900

18-25 26-35 36-45 46-55

Age Distribution

Energy Consumption (kWh)

Previous Month

This Month

Figure 6: Electrical Consumption Vs Age Distribution of

Residents.

5.1 Suburban Vs Urban Block of Flats

Comparing the block at the urban location with that at

the suburb, average energy savings in the urban case

were 2.4 times more. People at the suburban block

consumed in average 11% more energy compared to

the urban block. However, temperature strongly af-

fected this fact. Residents at the urban block were

more excited about the competition and took it more

seriously. Since a large proportion of them were

highly educated students, it was easier for them to un-

derstand and accept the motivation and terms of the

competition, inspiring also the other residents to pay

more attention to it.

5.2 Demographic Analysis

In Figure 6, we can study the residents’ distribution of

ages, in relation to their energy consumption. The re-

sults are normalized according to the number of ﬂats

and residents involved. Examining the ﬁgure, older

people (ages 46-55) consume more electricity

. This

probably happens because they spend most of their

time at home. However, this age group, together with

the age group 26-35, are mostly inﬂuenced by the

competition, reducing their consumption by 32%. It

is more convenient for people that spend much time at

home, to observe and analyze their consumption, tak-

ing countermeasures. For example, students may be

sometimes busy with their studies, not having in these

periods much free time in order to dispose a high pri-

ority for reducing their consumption.

Comparing the sex of the residents, as shown in

Figure 7, females tend to consume more electricity.

This is logical, as they usually spend more time at

home, having energy-demanding habits

(e.g. wash-

We discuss this ﬁnding with some reservation because

of the small sample of older people involved in the study.

To avoid misunderstandings, we note that males also

have energy-demanding habits, even those listed in the ex-

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171

100

150

200

250

300

350

400

450

500

Male Female

Sex

Energy Consumption (kWh)

Previous Month

This Month

Figure 7: Electrical Consumption Vs Sex of Residents.

100

150

200

250

300

350

400

450

500

123

Residents Per Flat

Energy Consumption (kWh)

Previous Month

This Month

Figure 8: Electrical Consumption Vs Number of Residents

Per Flat.

ing and drying their hair, preparing food). Nonethe-

less, women have contributed more in saving energy,

reaching 30% reductions, while men around 20%. In

general, females were more interested in the compe-

tition and in our efforts than males. They found the

perspective of protecting the environment appealing.

We then compared the electrical consumptions,

according to the number of residents at each ﬂat. We

display this comparison in Figure 8. Obviously, more

tenants at each ﬂat implies more consumption. While

this difference is more signiﬁcant when comparing

ﬂats having one or two residents, reaching 44%, it be-

comes very small between ﬂats of two and three res-

idents, around 4%. Concerning energy-savings, ﬂats

with one tenant achieved most savings, nearing 30%.

We believe it is easier for someone living alone to de-

velop his own energy-efﬁcient practices. These obser-

vations indicate that future energy-saving campaigns

should target one-bedroom ﬂats, as the margin of po-

tential savings is much bigger.

Our ﬁnal comparison, presented in Figure 9, was

about the income of the residents, in relation to their

consumption. People with no income are students

who are ﬁnancially-dependent on their families. As

expected, tenants with high income consumed more

energy. We assume that they are not willing to sacri-

amples, probably to a lesser degree.

100

200

300

400

500

600

No Income Below 15000 € Above 15000 €

Yearly Income

Energy Consumption (kWh)

Previous Month

This Month

Figure 9: Electrical Consumption Vs Income of Residents.

ﬁce their comfort just for saving money. On the con-

trary, residents with low income consume less than

half the energy of their high-income neighbors. This

group of people had the least savings in the com-

petition, perhaps because they had already tried to

save energy in the past, in order to reduce their costs.

Even though residents with high income consumed

increased electricity, maintaining high comfort lev-

els, their percentage of energy savings reached 30%.

Most of them were motivated because of environmen-

tal reasons and not because of saving money. This

observation suggests that future practices should try

to inﬂuence people from the upper classes, by giving

them incentives about protecting the environment.

5.3 General Statistics

Generally, 72% of the tenants stated that they were

actively involved with our social competition and that

this competition helped them acquire a more sustain-

able lifestyle. 94% believed that this competition will

inﬂuence them to save energy in the future. 69%

of them consider that the method of comparing con-

sumption with neighbors is a promising way for sav-

ing energy.

48% of people used our Web site for being up-

dated about the competition. All residents also

checked the information placed everyday in their no-

tice boxes. Younger people preferred to use the

Web in order to get informed, however, older people

found much more practical the notice box. Perhaps,

this inconvenience of older people using technology

needs to be considered when researchers design en-

ergy feedback systems in the future.

Unfortunately, our online forum was not utilized

by the residents for exchanging energy-saving tips.

Our Facebook application was used by six residents

or 15% of people, who preferred to be informed about

the competition while amusing through the popular

social networking site. Although these six people ini-

tially used our Facebook group for discussing about

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the competition, they soon stopped doing that. Some

tenants found it somehow weird to discuss online with

the person next door.

Asking the residents whether they wanted to be

informed in real-time about their electricity footprint,

89% were positive. From them, 88% were willing

to buy a product that would show them their energy

consumption in real-time. They would invest at most

70 Euro for such a product. Some of them were sur-

prised when we explained to them that this is possible

at these costs. Some people did not even know that

such products exist.

5.4 Suggestions from Residents

We also asked the tenants for suggestions concern-

ing more effective feedback about energy consump-

tion. The most popular suggestion concerned feed-

back through SMS, sent by the utility once per day.

Daily feedback through email was another interesting

suggestion. Some people requested that the electric

utilities should provide more detailed electricity bills.

Still, 61% believed that our approach is more effective

than what they suggested.

Finally, all residents agree that the government

must give smart incentives to people to save energy.

According to them, these incentives could be simi-

lar competitions with awards from the utilities, scalar

pricing schemes that reward green ﬂats and houses

while punishing energy-wasting buildings, more per-

vasive and real-time energy feedback techniques and

grants from the utilities or the government for renew-

able energy systems and green lighting.

6 CONCLUSIONS

In this paper, we examined the effectiveness of a local

competition for energy conservation using real-time

information about consumption of electricity. A so-

cial competition for blocks of ﬂats was created, en-

couraging tenants to actively take part in the competi-

tion by following energy-saving practices. We wanted

to demonstrate whether the combination of social in-

ﬂuence and amusement can motivate people to save

energy. A small case study was performed in two

blocks, one in an urban location and the other at the

suburb, counting in total 26 ﬂats and 39 residents.

Our ﬁndings are very positive, however, they just

constitute the product of a small case study and can

not be considered safe to extract conclusions about the

general population. Furthermore, the selected months

of the study have prevented a solid analysis of the re-

sults, due to the ﬂuctuations of temperature. Future

studies need to select months in which temperature is

not a dominant factor in the energy consumption of

residents.

An important issue when attempting to perform

such studies is to respect the privacy of people. It

must be solely their option whether they are willing

to participate and it must be deﬁned from the very

beginning in which extend their personal data will

be exposed. Written declarations of participation are

needed, to avoid legal problems.

A main drawback of our approach is related to the

necessity of having costly real-time energy monitor-

ing devices installed in the ﬂats, which is not a com-

mon practice nowadays. Nevertheless, the smart grid

of electricity suggests the massive deployment of

smart meters in residences, for real-time acquisition

of household electrical consumption. It is planned

that every home in Britain will be equipped with a

smart meter by the end of 2020

. Hence, our ap-

proach complies with the future smart grid, as the

smart power outlets we currently employ could be

replaced by residential smart meters. Accordingly,

such social competitions for saving energy could be

enabled by the electric utilities in the near future.

Future work needs to include a larger case study,

involving also blocks of buildings in more rural areas.

Such studies need to be performed to validate our ini-

tial ﬁndings and consider more conﬁdently the effect

of social norms on energy conservation. A longer pe-

riod of observation may also be interesting, to foster

the learning effect of the participants.

Long-term inﬂuence on residents’ behavior is an

important dimension not yet explored. For example,

considering energy awareness through real-time feed-

back, the saving effects are persistent mostly when the

feedback systems are present (Van Houwelingen and

Van Raaij, 1989). Thus, we need to consider also the

inﬂuence of the social competition at the blocks in the

coming months.

In this study, we tried to differentiate our social-

based efforts for saving energy from real-time feed-

back techniques. In such a way, we evaluated our

approach without direct inﬂuence from other factors.

Future work could combine continuous energy feed-

back with a social competition, to examine whether

further savings could be achieved.

Also, it would be interesting to consider if any

other incentives, other than the ”ranking and awards”

approach we followed, may be most efﬁcient in such

social competitions.

Our study conforms to the broader vision of smart

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neighborhoods

, deﬁned as groups of buildings (e.g.

blocks of ﬂats) mimicking living systems, collaborat-

ing inside the smart cities of the future. Similar to liv-

ing systems in nature, buildings will act collectively in

relation to the ecosystem (e.g. neighborhood) they re-

side in. This will help to address safety, health-related

or sustainability issues in the smart city, such as en-

ergy conservation and reduction of carbon emissions.

We encourage researchers, organizations and util-

ities to follow our methodology and perform similar

studies, giving awards and incentives to residents. So-

cial inﬂuence has the potential to boost the energy-

saving initiatives towards a greener world.

ACKNOWLEDGMENTS

We would like to thank the tenants of buildings

Costantinou 20 and Golden Hill A for their partici-

pation and support during this study. Also, the De-

partment of Computer Science, University of Cyprus

for access to the equipment used during the study.

REFERENCES

Allcott, H. (2011). Social norms and energy conservation.

Journal of Public Economics, 95(9-10):1082–1095.

Barbato, A., Borsani, L., Capone, A., and Melzi, S. (2009).

Home energy saving through a user proﬁling system

based on wireless sensors. In First ACM Workshop

On Embedded Sensing Systems For Energy-Efﬁciency

In Buildings (BuildSys), Berkeley, California.

Chetty, M., Tran, D., and Grinter, R. E. (2008). Get-

ting to green: understanding resource consumption in

the home. In Proceedings of the 10th international

conference on Ubiquitous computing, UbiComp ’08,

pages 242–251, New York, NY, USA. ACM.

Cialdini, R. (2001). Inﬂuence: science and practice. Allyn

and Bacon.

Darby, S. (2006). The effectiveness of feedback on energy

consumption - A review for defra of the literature on

metering, billing and direct displays.

Dillahunt, T., Mankoff, J., and Paulos, E. (2010). Under-

standing conﬂict between landlords and tenants: im-

plications for energy sensing and feedback. In Pro-

ceedings of the 12th ACM international conference on

Ubiquitous computing, Ubicomp ’10, pages 149–158,

New York, NY, USA. ACM.

Ehrhardt-Martinez, K., Donnelly, K., and Laitner, J. A. S.

(2010). Advanced Metering Initiatives and Residen-

tial Feedback Programs: A Meta-Review for House-

hold Electricity-Saving Opportunities. Washington,

DC: ACEEE Report No. E105.

http://paper.li/CityInnovation/1324428156

Erickson, V. L., Lin, Y., Kamthe, A., Brahme, R., Surana,

A., Cerpa, A. E., Sohn, M. D., and Narayanan, S.

(2009). Energy efﬁcient building environment control

strategies using real-time occupancy measurements.

In First ACM Workshop On Embedded Sensing Sys-

tems For Energy-Efﬁciency In Buildings (BuildSys),

Berkeley, California.

Europa Press Release (2008). Communication from the

European Commission. Energy Efﬁciency: Delivering

the 20% target.

International Energy Agency (2007). World Energy Out-

look.

Kamilaris, A., Papadiomidous, D., and Pitsillides, A.

(2011a). Lessons Learned from Online Social Net-

working of Physical Things. In Sixth Interna-

tional Conference on Broadband and Wireless Com-

puting, Communication and Applications (BWCCA),

Barcelona, Spain.

Kamilaris, A., Trifa, V., and Pitsillides, A. (2011b). Home-

Web: An Application Framework for Web-based

Smart Homes. In 18th International Conference on

Telecommunications (ICT 2011), Ayia Napa, Cyprus.

Kamilaris, A., Trifa, V., and Pitsillides, A. (2011c). The

Smart Home meets the Web of Things. Interna-

tional Journal of Ad Hoc and Ubiquitous Computing

(IJAHUC), Special issue on The Smart Digital Home,

7(3):145–154.

Kuznetsov, S. and Paulos, E. (2010). Participatory Sens-

ing in Public Spaces: Activating Urban Surfaces with

Sensor Probes. In ACM Designing Interactive Systems

(DIS), Aarhus, Denmark.

Mankoff, J., Fussell, S. R., Glaves, R., Grevet, C., John-

son, M., Matthews, D., Matthews, H. S., McGuire,

R., Thompson, R., Shick, A., and Setlock, L. (2010).

StepGreen.org: Increasing energy saving behaviors

via social networks. In Proceedings of the 4th In-

ternational AAAI Conference on Weblogs and Social

Media.

Passy, F. and Giugni, M. (2001). Social Networks and In-

dividual Perceptions: Explaining Differential Partic-

ipation in Social Movements. Sociological Forum,

16(1):123–153.

Seligman, C., Becker, L. J., and Darley, J. M. (1981).

Encouraging residential energy conservation through

feedback. Advances in Environmental Psychology

Volume 3 Energy Conservation Psychological Per-

spectives, 3:93–113.

Van Houwelingen, J. H. and Van Raaij, W. F. (1989). The

Effect of Goal-Setting and Daily Electronic Feedback

on In-Home Energy Use. Journal of Consumer Re-

search, 16(1):98–105.

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