1

Energy Savings from Using Mobile Smart Technologies

Veton Këpuska1, Paul Karaffa2, Guinevere Shaw1, Jacob Zurasky1, Christopher Kovalik1, Jordan Arnold1, Salvador Macaraig1

1Florida Institute of Technology,

2U.S. Environmental Protection Agency ENERGY STAR

This paper presents the most recent results of energy saving benefits from the

convergence of consumer products into a multi-function smart device, such as a

smartphone or tablet, compared to single-function products (e.g., an electronic clock).

Although individual users are predominantly driven only by the marked trends and the

individual energy savings are moderate, the sheer number of users makes this global

trend promising and a model for sustainable energy.

The energy consumption of selected smart devices was tested using 42 frequently used

applications and utilities (e.g., portable gaming, scanning, music players, etc.). A range of

Operating Systems (OS) were selected for testing: Android OS (Google), Blackberry OS

(RIM), iOS (Apple), and Windows 7 OS (Microsoft). Testing was conducted using the

following smartphones: Blackberry Curve 9300, iPhone 4, Samsung Focus, Samsung

Galaxy S; and tablets: iPad 2 and Samsung Galaxy Tablet 7". In order to investigate the

battery consumption, two programs were developed in-house for iOS and Android

platforms. For the Windows phone, the built-in program was utilized, while a third-party

application was used for the Blackberry phone. To further test the battery, each device

was also decoupled from its battery and hooked up through a measuring device and

experiments were then repeated.

This study shows smart devices save consumers up to $150 annually compared to single-

function devices in a range of applications. The results from this study demonstrate how

2

smart devices are transforming our society by providing superior functionality at a lesser

cost in energy, paving the way for other technologies to be integrated into smart devices,

and energy reduction to continue.

I. INTRODUCTION

Traditional consumer electronics were designed to perform a single function, and were rarely

designed to act as multi-function devices. Many single-function devices draw power constantly, even when

turned off (e.g., stand-by, hibernation, or sleep mode), creating an increase in energy consumption [1], and

thus an increase in the monetary burden of the product. The advent of smart devices has allowed software

developers to create applications that reduce the necessity of owning many single-function devices.

Replacing electronic products with software applications could effectively reduce household energy

consumption, and simplify product purchasing and product maintenance.

For this research, 4 smart-phones and 2 tablets were tested (see Table I) to validate the stated

hypothesis: that there is a significant energy saving benefit by using a smart device versus several single-

function devices; namely for smartphones: Samsung Focus, Samsung Galaxy S, Blackberry Curve 9300,

iPhone 4; and for tablets: Samsung Galaxy Tablet 7” and iPad 2.

TABLE I. Smartphones and tablets with corresponding OS and information regarding the application used for non-invasive measurement.

Device Samsung Focus

Samsung Galaxy S

Blackberry Curve 9300 iPhone 4

Samsung Galaxy Tablet 7”

iPad 2

OS Windows 7 Android Blackberry iOS Android iOS

Application Built-in Developed in-house

Down-loaded

Developed in-house

Developed in-house

Developed in-house

Smart devices were chosen based on the U.S. market share of their OS in mid-2011 (Figure 1) [2].

Android was shown to have the largest share of the market at approximately 36% followed by iOS at 26%.

Two devices were tested using each of these operating systems (i.e., smartphones and tablets). Blackberry

3

held 23% of the market in 2011 but the majority of their phones were not comparable with Android and

iOS, as many did not support applications, and were therefore not considered “smart”. The Windows 7 OS

did not hold a significant share of the market, so only one device was tested.

All smart devices were subjected to invasive and non-invasive testing (using an internal software

application as indicated in Table I). The Samsung Focus (Windows 7 OS) had a built-in application for

measuring energy consumption. However, to non-invasively measure all smart devices in this study,

several comparable applications had to be developed in-house to include those smart devices running

Android and iOS. The Blackberry Curve 9300 had a third-party application which was used to non-

invasively measure battery consumption1. Figure 2 depicts the screen shots of all the applications used for

non-invasive measurements.

Three parameters were monitored during non-invasive testing to include battery life, battery

temperature, and battery voltage. Not all parameters could be tested on each device due to OS restrictions.

Table II identifies those parameters supported by each device and application.

TABLE II

PARAMETERS OF APPLICATIONS USED FOR NON-INVASIVE MEASUREMENTS

D

evice

S

ams

ung

Gal

axy

S

S

ams

ung

Gal

axy

Tab

let

7”

S

ams

ung

Foc

us

i

Pho

ne 4

i

Pa

d 2

B

lackb

erry

Curv

e

9300

T

est

1 Tiny Meter: http://appworld.blackberry.com/webstore/content/32468/?lang=en

4

P

ercent

age of

batter

y

Rema

ining

X X X X X X

B

attery

Temp

eratur

e

X X X X

B

attery

Volta

ge

X X X

A total of 42 applications were selected from a number of more popular applications reflecting a

range of categories to include business, news, games, utilities, etc. It was not possible to test all devices

against all the applications. Nevertheless, a large number of applications were tested across most of the

devices (see Table VI & VII).

5

II. TESTING PROCEDURE

Testing was separated into two procedures: invasive testing and non-invasive testing. Each test

began with the smart device battery charged to 100% capacity. Note that there were different energy

capacities for different devices as indicated in Table III.

TABLE III

BATTERY SPECIFICATION FOR TESTED SMART DEVICES

U

n

it

s

Sam

sung

Sam

sung

Bla

ckbe

rry

iPho

ne 4

Sam

sung

iPad

2

V

o

lt

s

[

V

]

3

.

7

3

.

7

3

.

7

3

.

7

3

.

7

3

.

7

W

a

tt

-

h

o

u

5

.

5

5

5

.

5

5

4

.

3

5

.

2

5

1

4

.

8

2

5

6

r

s

[

W

h

]

M

il

li

a

m

p

e

r

e

-

h

o

u

r

s

[

m

A

h

1

5

0

0

1

5

0

0

1

1

5

0

1

4

2

0

4

0

0

0

4

4

0

0

7

]

S

c

r

e

e

n

T

y

p

e

C

a

p

a

c

i

t

i

v

e

T

o

u

c

h

-

s

c

r

e

e

n

C

a

p

a

c

i

t

i

v

e

T

o

u

c

h

-

s

c

r

e

e

n

T

r

a

n

s

-

m

i

s

s

i

v

e

T

F

T

L

C

D

L

C

D

M

u

l

t

i

-

t

o

u

c

h

L

C

D

M

u

l

t

i

-

t

o

u

c

h

L

C

D

M

u

lt

i

-

t

o

u

c

h

S 4 4 2 3 7 9

8

c

r

e

e

n

S

i

z

e

” "

.

4

”

.

5

”

”

.

7

”

Each application was tested in increments of 5 minutes, during which time the application was run

as authentically as possible to mimic its actual usage, after expiration of which the results were recorded.

Note that for iOS devices the time was extended for non-invasive measurements from 5 minutes to 25

minutes to compensate for insufficient accuracy of the iOS that gives the resultant battery capacity to the

nearest multiple of 5%.

The smart device battery was then re-charged to its maximum load for the next measurement. This

procedure ensured that the different experiments started from the same charge level; that is, they were

started from the same initial conditions.

Experiments were repeated 7 times and each result was logged-in. The overall measurement was

computed as the average of all 7 measurements. The experimental cycle was then repeated with a

different application and after each cycle the battery was recharged to its maximum level.

Significant care was taken so that individual experiments were conducted under realistic

circumstances for each application. The measurement was kept under the same conditions for each

application, and each application was tested in the same manner irrespective of the smart device in order to

ensure equality during the measurement procedure.

9

Finally, the battery specification data, as indicated in Table III, was used to compute the average

battery capacity drop for each tested smart device using the non-invasive measurement.

The testing procedure was repeated invasively with an external energy measurement module

("Watts Up" Meter2) to confirm the accuracy of each individual OS as presented in Figure 3. The actual

laboratory setup for invasive testing is depicted in Figure 4.

Energy consumption was made comparable by calculating the actual battery level drop. The

average drop of battery level l is computed as indicated in Table IV. This table is a typical measurement

example for the Samsung Galaxy S (Android) smartphone obtained for the Tetris game. As specified in the

table the number, in this case, is 1.25%. This value is then used to compute battery charge by using the

capacity of the battery (see Table III); that is by applying the formula:

P=−C∗l

where l is the average drop of the battery level (e.g, 1.25/100), and C is the capacity of the battery

in [Wh] (obtained from Table III); in this case C = 5.55 [Wh]. Hence the actual drop is computed to be P =

-0.069375 [Wh].

2 http://www.powerwerx.com/digital-meters/watts-up-meter-dc-inline.html

To

External Power

To Phone/

Tablet

To Battery

External

“Watts Up”

10

Figure 3. Invasive measurement set up.

Figure 4. Actual laboratory setup for invasive measurements.

For invasive measurements actual battery level drop was computed similarly (see Table V). The

Ampere per hour [Ah] and Voltage were selected as being most reliable for computing energy

consumption in Watts per hour [Wh] since other parameters fluctuated during instantaneous readings by

the measuring device. The energy consumption was computed with the following formula:

P=−c∗V

wherec is the average change in Ampere per hour and V is the Voltage reading.

TABLE IV

EXAMPLE OF THE TETRIS GAME RECORDED USING THE SAMSUNG GALAXY S SMARPTPHONE (ANDROID OS) DURING NON-INVASIVE TESTING

T

etris

T T B C T V

11

ime in

min

ime

Log

atter

y

Leve

l (%)

hang

e in

Batte

ry

Level

emperatu

re

R

eading

(Celsius)

oltage

Readi

ng

T

ime at

Start

9

:12:0

0

1

00

3

1

4

.186

5

9

:19:0

0

1

00

0

3

3

4

.146

1

0

9

:27:0

0

9

9

-

1

3

4

4

.133

1

5

9

:34:0

0

9

7

-

2

3

4

4

.113

2

0

9

:38:0

0

9

6

-

1

3

4

4

.096

2

5

9

:44:0

0

9

4

-

2

3

3

4

.091

3

0

9

:50:0

9

3

-

1

3

3

4

.083

12

0

3

5

9

:55:0

0

9

1

-

2

3

3

4

.066

T

ime

Finish

ed

9

:59:0

0

9

0

-

1

3

3

4

.057

A

verag

e

-

1.25

TABLE V

EXAMPLE OF THE MAHJONG GAME RECORDED USING IPAD2 TABLET (IOS) DURING INVASIVE TESTING

Mah

jong

T

ime

in

min

T

ime

Log

A

m

p

W

att

V

oltag

e

A

mp

per

hr

C

hang

e in

Am

p

per

hr

[

W

h]

T

ime

at

9

:00:

00

0

.8

4

3

.4

4

.02

0 0

13

Start

5 9

:05:

00

0

.8

4

3

.3

4

.01

0

.06

9

0

.069

0

.27

7

1

0

9

:10:

00

0

.8

3

3

.4

4

.00

0

.14

1

0

.072

0

.28

8

1

5

9

:15:

00

0

.8

4

3

.4

4

.00

0

.21

5

0

.074

0

.29

6

2

0

9

:20:

00

0

.8

5

3

.4

3

.99

0

.28

2

0

.067

0

.26

7

2

5

9

:25:

00

0

.8

4

3

.5

3

.98

0

.34

7

0

.065

0

.25

9

3

0

9

:30:

00

0

.8

5

3

.4

3

.97

0

.42

1

0

.074

0

.29

4

3

5

9

:35:

00

0

.8

5

3

.4

3

.96

0

.50

1

0

.08

0

.31

7

T

ime

Finis

9

:35:

00

14

hed

A

verag

e

0

.28

23

0

.071

6

-

0.2

85

The summary of each individual invasive and non- invasive measurement—a total of 42

experiments—were collected and tabulated (see Table VI and VII). Note that due to the differences in

measurement capabilities the units of the measurements are different (e.g., [mAh] for intrusive and [Wh]

for non-intrusive measurements.

TABLE VI

SUMMARY OF INVASIVE INDIVIDUAL APPLICATIONS MEASUREMENTS IN MAH

Phones Tablets

W

indows

7 Focus

G

alaxy S

Phone

B

lackberr

y Curve

9300

i

Phone 4

A

verage

Phones

G

alaxy

Tab

i

Pad2

A

verage

Tablets

Contr

ol

0

.017

0

.012

0

.020

0

.016

0

.016

0

.040

0

.071

0

.055

Alar

m Clock

0

.016

0

.011

0

.007

0

.021

0

.014

0

.043

0

.043

Angr

y Birds

0

.027

0

.036

0

.027

0

.030

0

.058

0

.083

0

.070

15

Barc

ode Scanner

0

.022

0

.048

0

.023

0

.015

0

.027

0

.060

0

.060

Bloc

ked In

0

.023

0

.016

0

.015

0

.026

0

.020

0

.073

0

.073

Brow

ser

0

.029

0

.023

0

.012

0

.020

0

.021

0

.029

0

.079

0

.054

Bubb

le Breaker

0

.030

0

.022

0

.012

0

.090

0

.038

Calc

ulator

0

.014

0

.012

0

.010

0

.076

0

.028

0

.040

0

.040

Cam

era

0

.033

0

.031

0

.029

0

.142

0

.059

0

.064

0

.064

Ches

s

0

.075

0

.010

0

.026

0

.017

0

.032

Craig

slist Mobile

0

.028

0

.018

0

.014

0

.016

0

.019

0

.068

0

.072

0

.070

Emai

l

0

.017

0

.015

0

.012

0

.018

0

.015

0

.365

0

.076

0

.221

ESP

N Mobile

0

.021

0

.019

0

.009

0

.014

0

.016

0

.052

0

.069

0

.061

Face

book

0

.021

0

.022

0

.014

0

.073

0

.033

0

.049

0

.071

0

.060

Face

book Chat

0

.015

0

.012

0

.020

0

.016

0

.043

0

.043

16

Flash

light

0

.016

0

.035

0

.025

0

.016

0

.023

0

.071

0

.071

Flixst

er

0

.023

0

.017

0

.018

0

.016

0

.019

0

.052

0

.082

0

.067

FM

Radio

0

.024

0

.008

0

.013

0

.015

0

.015

0

.050

0

.050

Fruit

Ninja

0

.022

0

.029

0

.036

0

.029

0

.066

0

.086

0

.076

Gas

Buddy

0

.022

0

.018

0

.009

0

.018

0

.017

0

.061

0

.082

0

.072

Goog

le Maps

0

.107

0

.023

0

.019

0

.063

0

.053

0

.058

0

.058

Goog

le Voice

0

.018

0

.018

0

.018

Hang

man

0

.028

0

.012

0

.012

0

.022

0

.018

0

.080

0

.080

Kindl

e

0

.027

0

.020

0

.069

0

.039

0

.046

0

.086

0

.066

Mahj

ong

0

.023

0

.014

0

.010

0

.045

0

.023

0

.072

0

.072

MP3

Player

0

.023

0

.010

0

.016

0

.016

0

.058

0

.073

0

.066

Need

for Speed

0

.027

0

.033

0

.030

0

.072

0

.087

0

.080

17

Netfl

ix

0

.030

0

.030

0

.059

0

.059

Pac

Man

0

.023

0

.052

0

.023

0

.033

0

.054

0

.074

0

.064

Pand

ora

0

.013

0

.014

0

.018

0

.015

0

.177

0

.082

0

.129

PDF

Scanner

0

.020

0

.024

0

.021

0

.021

0

.069

0

.069

Phot

o Editor

0

.020

0

.016

0

.020

0

.013

0

.017

0

.052

0

.052

Shaz

am

0

.023

0

.016

0

.023

0

.014

0

.019

0

.068

0

.068

Solit

aire

0

.032

0

.022

0

.009

0

.021

0

.050

0

.077

0

.064

Tetri

s

0

.024

0

.038

0

.011

0

.024

0

.072

0

.072

Twitt

er

0

.025

0

.015

0

.014

0

.018

0

.063

0

.073

0

.068

Uno

0

.025

0

.025

Voic

e Notes/Rec

0

.027

0

.013

0

.016

0

.019

Weat

her Bug

0

.011

0

.015

0

.064

0

.030

0

.057

0

.087

0

.072

18

Weat

her Channel

0

.011

0

.011

Web

MD

0

.049

0

.049

Word

s W/Friends

0

.024

0

.018

0

.021

0

.073

0

.073

Yout

ube

0

.027

0

.016

0

.020

0

.021

0

.021

Aver

age

0

.026

0

.021

0

.016

0

.034

0

.024

0

.070

0

.076

0

.073

Cons

umption

mAh

-

26.474

-

21.014

-

15.557

-

34.234

-

24.320

-

69.576

-

76.429

-

73.002

III. RESULTS

The weighted average energy consumption

of tested smart devices is presented in Figure 5

(invasive) and Figure 6 (non-invasive).

Measurements differed during invasive and non-

invasive testing. The inconsistencies are most likely

due to the fact that non-invasive measurements

were done by using the device being measured as

the measuring device.

The following initial conclusions can be

drawn by comparing those results:

19

(1) The results correlate well between non-

invasive and invasive measurements with the

exception of the Samsung Focus.

(2) The non-invasive measurements, utilizing an

on board OS, consistently underestimated its

energy consumption.

TABLE VII

SUMMARY OF NON-INVASIVE INDIVIDUAL APPLICATIONS MEASUREMENTS IN [WH]

Phones Tablets

W

indows 7

Focus

G

alaxy S

Phone

Bl

acbarry

Curve

9300

i

Phone4

A

verage

Phones

G

alaxy

Tab

i

Pad2

A

verage

Tablets

Contr

ol

-

0.286

-

0.857

-

1.000

-

1.143

-

0.821

-

1.000

-

1.143

-

1.071

Alar

m Clock

-

1.000

-

0.714

-

0.714

-

0.810

-

1.000

-

1.000

Angr

y Birds

-

1.429

-

1.571

-

2.143

-

1.714

-

1.429

-

1.429

-

1.429

Barco

de Scanner

-

1.571

-

1.286

-

1.429

-

1.429

-

1.286

-

1.286

20

Block

ed In

-

0.429

-

1.143

-

1.714

-

1.095

-

0.857

-

0.571

-

0.714

Brow

ser

-

1.286

-

1.429

-

1.143

-

1.429

-

1.321

-

1.000

-

0.857

-

0.929

Bubb

le Breaker

-

1.000

-

1.143

-

1.429

-

1.190

-

1.000

-

0.714

-

0.857

Calcu

lator

-

0.286

-

1.000

-

0.857

-

0.714

-

1.000

-

1.000

Came

ra

-

0.429

-

2.143

-

1.167

-

1.246

-

1.286

-

1.286

Chess-

1.571

-

0.714

-

1.143

-

1.429

-

1.214

-

0.857

-

1.429

-

1.143

Craig

slist Mobile

-

1.286

-

1.571

-

1.571

-

1.286

-

1.429

-

1.429

-

0.714

-

1.071

Email-

0.571

-

0.857

-

0.571

-

1.286

-

0.821

-

0.714

-

0.714

-

0.714

ESP

N Mobile

-

0.571

-

0.429

-

1.714

-

1.286

-

1.000

-

1.286

-

0.714

-

1.000

Faceb

ook

-

1.571

-

1.429

-

1.857

-

1.429

-

1.571

-

1.143

-

1.286

-

1.214

Faceb

ook Chat

-

1.571

-

1.000

-

1.286

-

1.286

-

1.143

-

1.143

Flash

light

-

0.857

-

1.714

-

1.286

-

1.286

-

1.571

-

1.571

Flixst - - - - - - - -

21

er 0.571 0.857 1.714 2.857 1.500 1.143 0.571 0.857

FM

Radio

-

0.571

-

0.714

-

1.714

-

1.429

-

1.107

-

1.000

-

0.571

-

0.786

Fruit

Ninja

-

0.429

-

1.286

-

2.000

-

1.238

-

1.286

-

2.857

-

2.071

Gas

Buddy

-

0.714

-

1.000

-

1.429

-

1.429

-

1.143

-

1.143

-

0.714

-

0.929

Goog

le Maps

-

1.571

-

1.429

-

2.000

-

1.143

-

1.536

-

1.143

-

1.143

Goog

le Voice

-

1.000

-

1.286

-

1.000

-

1.095

-

0.714

-

0.714

Hang

man

-

0.714

-

0.857

-

0.714

-

1.429

-

0.929

-

0.714

-

0.714

Kindl

e

-

1.429

-

1.429

-

1.143

-

1.333

-

1.000

-

1.429

-

1.214

Mahj

ong

-

1.429

-

1.286

-

0.714

-

1.143

-

1.143

-

1.286

-

0.714

-

1.000

MP3

Player

-

1.429

-

0.857

-

0.857

-

1.143

-

1.071

-

0.857

-

0.429

-

0.643

Need

for Speed

-

1.429

-

1.286

-

2.286

-

1.667

-

1.000

-

0.857

-

0.929

Netfli

x

-

1.429

-

1.429

-

1.429

-

0.571

-

0.571

22

PacM

an

-

1.429

-

1.000

-

1.571

-

1.333

-

1.000

-

0.714

-

0.857

Pand

ora

-

1.143

-

1.286

-

1.143

-

1.190

-

1.143

-

1.143

-

1.143

PDF

Scanner

-

0.429

-

1.286

-

1.143

-

0.952

-

1.143

-

1.143

Photo

Editor

-

1.286

-

1.000

-

1.571

-

1.286

-

0.857

-

0.857

Shaza

m

-

0.714

-

1.143

-

1.000

-

1.286

-

1.036

-

1.000

-

0.429

-

0.714

Solita

ire

-

1.000

-

1.429

-

1.000

-

1.143

-

1.143

-

0.714

-

0.429

-

0.571

Tetris-

0.714

-

1.286

-

0.857

-

0.952

-

1.286

-

1.286

Twitt

er

-

0.714

-

1.286

-

1.429

-

1.286

-

1.179

-

1.000

-

0.714

-

0.857

Uno-

0.714

-

0.714

Voice

Notes/Rec

-

1.429

-

0.857

-

0.857

-

1.048

-

0.857

-

0.857

Weat

her Bug

-

0.875

-

1.000

-

1.143

-

1.006

-

2.857

-

2.857

Weat

her Channel

-

0.429

-

1.857

-

1.143

-

1.286

-

1.286

23

Web

MD

-

0.857

-

0.857

-

1.000

-

1.000

Word

s W/Friends

-

2.429

-

1.429

-

1.929

-

1.571

-

1.286

-

1.429

Yout

ube

-

1.286

-

1.000

-

2.714

-

1.429

-

1.607

-

1.714

-

1.143

-

1.429

Aver

age [%]

-

0.986

-

1.180

-

1.286

-

1.455

-

1.227

-

1.117

-

0.980

-

1.195

Cons

uption [Wh]

-

0.055

-

0.065

-

0.055

-

0.076

-

0.063

-

0.165

-

0.245

-

0.137

Using invasive measurements (see Figure 4),

Blackberry Curve 9300 (Blackberry OS) and the

Samsung Galaxy S (Android OS) preformed the

best.

Tablets were found to be 19.44% less

efficient than smartphones in both measurements,

and their average capacity drop was found to be

(through invasive testing) 0.2907 [Wh]. The

Samsung Galaxy Tablet 7” was found to be more

energy efficient than the iPad 2, which may be

attributable to its smaller screen size (7" vs. 9.7").

Smaller screen size radiates less and hence

consumes less power to light its screen [3].

The results would presumably have been

impacted by the screen size and type (i.e. touch-

screen features) of particular smart devices, such as

the Blackberry Curve 9300, which has a

significantly smaller screen size (2.4") and no

touch-screen capabilities (Transmissive TFT LCD)

leading to minimal energy consumption of the

device during testing.

A detailed discussion of LCD displays and

how the screen size and type affects the

24

consumption of battery power can be found in the

reference publication of Wiley Series in Display

Technology [3].

Samsung FocusSamsung Galaxy S

Blacbarry Curve 9300Apple iPhone4

Average PhonesSamsung Galaxy Tab 7"

Apple iPad2Average Tablets

Phon

esTa

blet

s

-0.35-0.3

-0.25-0.2

-0.15-0.1

-0.05

-5.55111512312578E-17

-0.1052-0.0812

-0.0612-0.1398

-0.0969-0.2765

-0.3060-0.2913

Average Capacity Drop [Wh] - Invasive Measurement

Power Consumtion [Wh]

Figure 5. The average energy consumption of smart devices given in [Wh] using invasive measurements.

Samsung Focus

Samsung Galaxy S

Blacbarry Curve 9300

Apple iPhone4

Average Phones

Samsung Galaxy Tab 7"

Apple iPad2

Average TabletsPh

ones

Tabl

ets

-0.350 -0.300 -0.250 -0.200 -0.150 -0.100 -0.050 0.000

-0.0547

-0.0654

-0.0553

-0.0764

-0.0630

-0.1652

-0.2451

-0.1374

Average Capacity Drop [Wh] - Non-invasive Measurement

Power Consumtion [Wh]

Figure 6. The average energy consumption of smart devices given in [Wh] using non-invasive measurements.

25

IV. CONCULSION

Results for tested smartphones and tablets

were compared against energy data on the most

efficient units in their product category (see Table

VIII) using the results from both non-invasive and

invasive testing. For example, the Analog TV

consumes 140 [kWh] annually, while the

measurements in this study indicate smart devices

consumed 0.2584 [kWh] for the same time period.

With the average U.S. residential electric rate at

$0.1151/kWh [15], this translates to $16.08 of

energy savings. For the digital TV with set-top box

this energy gap is more significant: 520 [kWh] vs.

0.2584 [kWh] which in turn translates to $59.82

annually. Notebook and Laptop computers on

average consume about 59 [kWh] annually [3],[4],

and [6],

while smart devices on average consumes

less than 0.2888 [kWh], an annual savings of $6.76.

The most recent reports show smartphones

are capturing the Video Gaming market [10, 11]. In

term of energy savings smart devices outperform

top game consoles [5] Nintendo Wii 27 [kWh],

Microsoft’s Xbox 112 [kWh] and Playstation 3 118

[kWh] to 0.3052 [kWh], annually.

A typical home in the United States has 40

products continuously drawing power [13], and a

typical household includes a desktop computer and

LCD monitor, two TVs, a DVD or VCR, and an

allocation for “other” devices that include

telephones, consumer electronics, and home office

equipment [14].

A household which includes a Notebook PC,

two Digital TVs w/ Digital Set-top boxes, a digital

camera, an MP3 player, two clock radios, a modem,

two cordless phones, an answering machine, and a

game console could reduce their power

consumption by 1300-1400 [kWh], or up to $160.00

per year by using smart devices as their primary

consumer electronic device.

26

TABLE VIII

POWER CONSUMPTION OF DEVICES COMPARED TO A SMART DEVICE [2-5]

Device

Power

Consumption

(kWh/yr)

Smart

Device Power

Consumption

(Wh)

Smart

Device Power

Consumption

(kWh/yr)

Differen

ce in Power

Consumption

(kWh/yr)

Notebook PC [4] 59 0.1054 0.2888 58.7112

Analog TV [5] 140 0.0943 0.2584

139.741

6

Digital TV w/

Digital Set-top box [5] 520 0.0943 0.2584

519.741

6

Digital Camera [4] 7.2 0.0985 0.2699 6.9301

MP3 player [4] 5.6 0.0763 0.2090 5.3910

Nintendo Wii [6] 27 0.1114 0.3052 26.6948

Microsoft Xbox

360 (2007 Model) [6] 112 0.1114 0.3052

111.694

8

Sony Playstation 3

(2007 Model) [6] 118 0.1114 0.3052

117.694

8

Clock Radio [5] 15 0.0852 0.2334 14.7666

Modem (Cable &

DSL) [4] 53 0.0957 0.2623 52.7377

Answering

Machines [7] 26 0.0487 0.0487

25.8665

6

Cordless Phones [7] 28 0.0487 0.0487

25.8665

6

27

Average

92.5666

6667

0.09010

8333

0.23276

6667

92.1531

1

From our research the following conclusions can be

drawn:

(1) the convergence of products could save energy

[10-12]

(2) people would rather have one device that serves

several functions than a number of devices that

have only one function or limited functions [10-

12]

(3) consumers are interested in the energy

efficiency of their products, and do take that

into account when purchasing [2],[10-12].

(4) single-function products, and some multi-

function products, are losing market share to

smart devices [10-12].

In a recent IDC report [12], it was estimated 92.1 million

computers and over 100.9 million smartphones were sold in 2010. Other

reports indicate that the total market share of smartphones and tablets

has exceeded that of computers for the first time [9]. Smartphone

platforms continue to grab share of the portable gaming market [10],

[11].

The results from this study demonstrate how smart

devices are transforming our society by providing

superior functionality at a lesser cost in energy. It is

anticipated technologies will continue to be

integrated into smart devices, and will continue to

consume significantly less power than single-

function devices.

Consumers can save a substantial amount of money

by utilizing a smart device in replacement of single-

function consumer electronics.

V. ACKNOWLEDGMENT

The authors would like to thank the

Environmental Protection Agency (EPA) and the

Florida Institute of Technology (FIT) for the use of

their facilities and resources during the execution of

this research. In addition the authors would like to

thank the anonymous reviewers who evaluated this

research for technical accuracy.

28

VI. REFERENCES

[1] Horowitz N., May-Ostendorf P. Tuning in to

Energy Efficiency: Prospects for Energy Savings in

TV Set-top Boxes. EOC Consulting, 2008.

[2] M., Kurlyandichik. Google's mobile OS now

dominates 36 percent of the national smartphone

market. DailyTech, June, 2011. Article.

[3] Shunsuke Kobayashi, Shigeo Mikoshiba,

Sungkyoo Lim, Editors, LCD Backlights,Wiley

Series in Display Technology, 2009

[

4] Roth K., McKenney K. Energy Consumption by Consumer Electronics in U.S. Residences.

Cambridge, MA, TIAX LLC, 2007.

[5] Rosen K., Meier A. Energy use of U.S. Consumer Electronics at the End of the 20th Century. Berkeley,

Lawrence Berkeley National Laboratory, 2001.

[6] N., Horowitz, et al. Lowering the Cost of Play: Improving teh Energy Efficiency of Video Game

Consoles. NDS, Novemeber2008. NDS Paper.

[7] Karen B. Rosen, Alan K. Meier, and Stephan Zandelin, Energy Use of Set-top Boxes and Telephony

Products in the U.S., Environmental Energy Technologies Division, Lawrence Berkeley National

Laboratory, University of California, Berkeley, California 94720, June 2001,

http://eetd.lbl.gov/ea/reports/45305/45305.pdf

[8] Whole Sale Solar Inc. [Online] 2003. http://www.wholesalesolar.com/pdf.folder/Download

folder/Power-table.pdf.

[9] Power. www.edho.com. [Online] http://www.edho.com/power/.

[10] Digital Voice Recorders. us.sanyo.com. [Online] 2011.

http://us.sanyo.com/Digital-Voice-Recorders/SANYO-ICR-FP700D-Digital-Stereo-MP3-Voice-Recorder-

with-expandable-SD-card-memory-slot.[9] Weintruab, S.; Industry first: Smartphones pass PCs in sales,

CNNMoney, Technology. 2011.

29

[11] E., Slivka. Smartphone Platforms Continue to Grab Share of Portable Gaming Market. touchArcade,

April, 2011.

[12] Farango, Peter. Apple and Google Capture U.S. Video Game Market Share in 2010. Flurry, April 15,

2011. Web Blog.

[14] IDC Report, Worldwide Top 10 Mobile Phone Chipset and Connectivity Semiconductor 4Q10

Vendor Shares, 2011

[15] Meier, A., et al., Low Power Mode

Energy Consumption in California Homes, 2008,

California Energy Commission, Public Interest

Energy Research Program, Report No. CEC-500-

2008-035: Sacramento, Calif.

[16] Typical House memo, Lawrence

Berkeley National Laboratory, 2009

[17] 2011 U.S. Electric Rate: Energy

Information Administration, Annual Energy

Outlook 2012 (Early Release) edition. (converted

from 2010 to 2011 dollars).

VII.

VIII. BIOGRAPHIES

Veton Këpuska was born in Vushtrri, Republic of

Kosova, on November 7, 1957. He graduated from the

Technical Faculty of University of Prishtina, Prishtina,

Republic of Kosova. He continued his education by obtaining his MSci and

PhD degrees at Clemson University, Clemson SC, USA, and completed the

Post-Doctoral Research study at the Swiss Federal Institute of Technology in

Zürich Switzerland. He worked for over 10 year in industry as Speech

Recognition Scientist and has been issued two patents. He joined academia in

2003 in part to pursue independently his Wake-Up-Word Technology that he

has invented over a decade ago.

Paul Karaffa was born in Richmond, Virginia in

1985. He received his BSci & MSci degrees from George

Mason University in Fairfax, Virginia. He worked in the fields of

sustainability, water ecology, and environmental regulation at the beginning

of his career; and later continued environmental work in the field of energy

conservation. He began working with EPA’s ENERGY STAR in 2010 to

manage mobile technology interests and the development of several technical

specifications.

30

Guinevere Shaw was born in Washington

D.C. on October 4, 1989. She is a current undergraduate

at Florida Institute of Technology studying in Solar Earth

and Planetary Sciences. She interned for the Department

of Energy and Environmental Protection Agency during the Summer of 2011.

She also interned during the Fall of 2011 for the Department of Energy at the

E.O. Lawrence Berkeley National Laboratory. She plans to graduate Fall of

2012 and hopes to pursue a Ph.D at the University Tennessee in Knoxville for

Energy Science and Engineering program

IX. JACOB ZURASKY WAS

BORN ON JANUARY 3, 1984, IN

SAN ANTONIO, TEXAS. HE

GRADUATED SUMMA CUM LAUDE FROM

FLORIDA INSTITUTE OF TECHNOLOGY WITH

A B.S. IN ELECTRICAL ENGINEERING IN

2010.  HE IS CURRENTLY PURSUING A

MASTER'S DEGREE IN THE FIELD OF

SPEECH PROCESSING / RECOGNITION. HE

ALSO HAS A COUPLE PATENTS PENDING IN

THE AREA OF SLEEP DISORDER DIAGNOSIS

AND TREATMENT.