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Automation in Home Appliances 83.2 Application Examples, Guidelines, and Techniques 1475

with the appliance itself making all necessary deci-

sions about time and temperature, thus automating the

process.

In a still more advanced realization of cooking au-

tomation, the cooking appliance would be provided

with detailed cooking instructions by the food itself.

The food’s packaging – a box or wrapper – could be

equipped with an RFID tag which would be read by the

cooking appliance, either as it is placed into the appli-

ance or when it is passed near a sensor manually. This

approach is clearly most feasible in the context of pre-

pared foods. The RFID tag would contain details of the

nature of the food (e.g., its type and weight), cooking

time, and cooking temperature. The only required user

intervention would be selecting the desired doneness, if

applicable, and pressing start, substantially automating

the process. When integrated with temperature probes

and sensors, the cooking appliance could automate the

entire process, from defrosting to cooking, simply tak-

ing the desired meal time as an input.

Extending the concept of a digital recipe to cooking,

the power of the AAN could be leveraged to coor-

dinate the functions of the cooking and refrigeration

appliances and substantially automate food preparation

from end-to-end: The smart fridge would manage the

ordering and inventory of ingredients, while the smart

cooking appliances would manage the cooking based

on XML-encoded instructions(time andtemperature) in

the digital recipe or a similar information classiﬁcation

protocol (Fig.83.7).

83.2.3 Cleaning

Cleaning appliances – clothes washers, clothes dryers,

and dish washers – again offer a substantial degree of

process automation by their very nature. However, fur-

ther levels of automation are possible. Some examples

are as follows.

Washing appliances – clothes and dish washers – are

optimized by their users according to the nature of the

task at hand. The number of cycles offered by each ma-

chine is limited, and users sometimes utilize only one or

two of the available cycles. Thus, there exists the oppor-

tunity to automate the decision-making process further.

With an appropriate array of sensors – such that the fab-

ric/dish type, volume, and soil level can be assessed –

the washer can automatically optimize its cycle. Among

the variables which can be adjusted are the wash, rinse,

spin, etc. durations, the nature of the chemistry (such

as the detergent type and volume), and optimal water

temperature and volume.

greatrecipes.com

Fig. 83.7 Semiautomated food preparation

In an even more advanced implementation, clothing

and dishes would be equipped with RFID tags which

would inform the appliance as to the nature of the item

as well as speciﬁc care instructions. The cleaning appli-

ance could then determine the optimum washing/drying

cycle based on all the contents loaded into the ma-

chine, perhaps suggesting, for example, that certain

items should not be washed together, or should not be

machine washed (or dried) at all (Fig.83.8).

It is easily observable that water-consuming appli-

ances such as clothes washers and dish washers can

cause a substantial drop in household water pressure

during their operation. They can also consume a sub-

stantial portion of the household hot water reserve. The

power of the AAN can be leveraged automatically to

coordinate the operation of water-intensive processes;

for example, the clothes and dish washers can commu-

nicate over the AAN to ensure that they do not both

operate at the same time, and both devices can com-

municate with the water heater to ensure a sufﬁcient

reserve for other water-intensive activities in the home

(Fig.83.9). Both appliances further could be conﬁgured

to avoid operation during bathing times.

83.2.4 General Appliance Automation

Thus far we have examined the automation of the

speciﬁc processes performed by individual home ap-

pliances. We now examine automation as it pertains

to home appliances in general. Microprocessor con-

trol, sensor arrays, and connectivity enable a number of

generic automation functions in any so-equipped home

appliance. Some possibilities include:

Part I 83.2

1476 Part I Home, Ofﬁce, and Enterprise Automation

120

100

–20

–40

RFID

95% cotton, 5% polyester

Machine wash

Warm water

Tumble dry

Read fabric info

Read load level

Modified delicate wash cycle

Dispense 0.5ml detergent

0ml bleach

0.5ml softener

Wash: 14min, 16°C

Rinse: 13min, 7°C

Spin: 10min, 600rpm

Modified delicate dry cycle

Heat: 15min, 16°C

15min, cool down

Tumble: 40rpm

1/1

1/2

Fig. 83.8 RFID-based wash cycle optimization

•

Performance monitoring

•

Fault monitoring

•

Software maintenance

•

Consumables monitoring.

Performance Monitoring

Traditionally, poor appliance performance is not de-

tected and acted upon until it degrades to a catastrophi-

cally-low level; for example, a refrigerator evaporator

fan becomes clogged with debris and the fridge fails

to cool effectively and begins to consume inordinate

amounts of energy. As performance continues to de-

grade, the fridge is unable to maintain a sufﬁciently low

temperature and food spoils, resulting in a risk to the

user’s health. Usually only when this near-fault condi-

tion occurs is the user alerted to the problem. However,

advanced automation techniques permit home appli-

ances to monitor various internal performance metrics

continuously. In our example, this might include:

•

The electric current drawn

•

The condenser fan on time

•

Time during which the cooling chamber exceeds the

desired temperature.

These metrics could be compared against their

long-term average values, or against some factory-

programmed limits. If performance, as determined by

these metrics, degrades below the desired level, the

user or the appliance service center is automatically

alerted – by the appliance – to the need for mainte-

nance (Fig.83.10), thus avoiding a catastrophic outage

and food spoilage.

Fault Monitoring

Similarly, appliance faults which are not preceded by

gradually degrading performance can be acted upon au-

tomatically. Appliances can execute internal diagnostic

testing periodically and can detect when subsystems

Part I 83.2

Automation in Home Appliances 83.2 Application Examples, Guidelines, and Techniques 1477

Starting cycle

Projected water demand: 70l

Okay to proceed?

Active cycle in progress?

Water demand in next 30min?

Delay cycle by 30min

Exceeds peak

hour water

reserve limit?

Refilling the tank?

Water demand in next 30min?

Refilling in progress

Projected usage next 30min: 200l

Active cycle in progress

Projected usage next 30min: 150l

Fig. 83.9 Water usage coordination

fail. This information can both be shown on the appli-

ance’s video display and be reported to the appliance

service center. Armedwith exact knowledgeof thefault,

the responding technician can be dispatched with all

necessary tools and parts, minimizing the time to repair

and the need for a follow-up visit to the user premises.

Critically, large volumes of fault and performance

data – gathered from an appliance vendor’s installed

base – can be aggregated and analyzed to spot trends.

Subcomponents which have unusually high fault rates

can be swapped in the manufacturing process to re-

duce the incidence of the fault in future appliances

(Table 83.2). Similarly, appliances showing trends in

a certain mode of performance degradation can be re-

designed to minimize the likelihood of occurrence in

future units.

Software Maintenance

Once home appliances are functional Internet nodes,

it becomes possible to automate appliance software

maintenance. Just as a home personal computer (PC)’s

operating system and application software are updat-

able automatically viathe Internet, socan anappliance’s

software be updated. As software bugs are discovered,

new loads containing the bug-ﬁx can be pushed out

to the connected appliances, eliminated the need for

a service call, the need to disassemble the appliance,

or even the need to connect tools – such as a PC –to

the appliance. Beyond bug-ﬁxes, this technique can be

used to deploy new software-based functionality, such

as new or optimized machine cycles. This is a partic-

ularly powerful capability when used in conjunction

with the aforementioned large-scale performance data

analysis, which might indicate that certain software pa-

rameters – such as performance thresholds – need to be

tweaked.

Consumables Monitoring

Some home appliances utilize consumable items

– items which have a limited useful life and must be

replaced periodically. Examples include ﬁlters and ad-

ditive or detergent cartridges. When an appliance is

Part I 83.2

1478 Part I Home, Ofﬁce, and Enterprise Automation

Measurement report

Average current: 12.3A

Condenser on time: 4h

Average fridge temperature: 2°C

Average freezer temperature: –15°C

Fridge over-temperature time: 4 h

Freezer over-temperature time: 2.1h

Trouble notification

Maintenance request

Maintenance confirmation

Customer service

back office

Maintenance scheduled

Poor performance detected

Execute remote diagnostics

Measurement report

Compressor efficiency: 38%

Initiate performance monitoring

tom

ser

back offic

Fig. 83.10 Remote performance monitoring

under microprocessorcontrol, theremaining life of con-

sumables can be monitored precisely. When this metric

falls below a predetermined threshold, the connectivity

capability can be used to reorder the consumable auto-

matically, thus eliminating the possibility of appliance

downtime or degraded performance.

83.2.5 Household Energy Management

For a number of reasons, household energy usage – pri-

marily electric power usage – has been brought to the

forefront of the energy debate. Concerns over climate

change, energy supply stability, and national energy

Table 83.2 Trending using aggregated performance data

Type Subtype Model Revision Units in ﬁeld Fault code Fault instances

Refrigerator Side-by-side K123 2 67839 1 0

Refrigerator Side-by-side K123 2 67839 2 0

Refrigerator Side-by-side K123 2 67839 3 42

Refrigerator Side-by-side K123 2 67839 4 690

Refrigerator Side-by-side K123 2 67839 5 0

... ... ... ... ... ... ...

independence have refocused government and public

utilities on the issue.

A particular concern of electric utilities is transient

peaks in demand which exceed the utility’s ability to

produce power. In such situations, the utility is forced to

purchase energy on the open market from a third-party

supplier. Since such suppliers know that electric power

in such overload conditions is extremely valuable to the

utility, they charge relativelyhigh prices for the electric-

ity, negatively impacting the utility’s margins, in some

cases to the extent that the utility loses money, after

having sold the electric power for less than it cost to

acquire it.In order to minimize their loss, utilities some-

Part I 83.2

Automation in Home Appliances 83.2 Application Examples, Guidelines, and Techniques 1479

times must cut their supply of power. In order to spread

the pain, this is done for brief periods within a number

of geographic regions, producing the infamous roving

brownouts.

In other industries, if a supplier runs out of capacity,

it simply builds or otherwise procures additional sup-

ply capacity. In the case of a manufacturer of goods,

a new factory might be constructed. However, electric

power generation facilities are both expensive to build

and sensitive politically. So increasing supply is difﬁ-

cult and sometimes infeasible. In order to address the

electric power supply–demand problem, utilities have

taken a demand-side approach. This approach entails

direct control of power consumption by the electrical

devices – including appliances – in the home, as well

as in load-based, real-time pricing of electricity. Thus

we introduce the concept of automated electric power

usage in the home.

Direct Load Control

Direct load control (DLC) refers to the ability of the

electric power utility to reduce the amount of power

consumed by electrical equipment in the home by

communicating directly with the equipment, without

the need for resident intervention [83.3]. Examples of

home electrics which are key to the DLC strategy in-

clude HVAC systems, electric water heaters, and major

appliances.

With DLC, as the utility approaches its capacity

limit (Fig. 83.11), it sends signals to the home electrics

which indicate the need to conserve power; for exam-

ple, the HVAC system can be requested to operated at

a higher (in summertime) or lower (in wintertime) tem-

perature. Likewise, the water heater can be requested to

Electric utility capacity

Electricity demand

Time

Fig. 83.11 Hypothetical electricity demand versus electric

utility capacity

switch off temporarily, resulting in power savings with

a slight reduction in water temperature. Electrical ap-

pliances – which sometimes have complex operating

cycles – can be requested to operate in high-efﬁciency

mode, or to delay starting until the power demand has

subsided.

Many architectures exist for realizing DLC-based

automated home energy usage control. In one imple-

mentation, the electric utility operates a server which

monitors instantaneouspowerdemand. As demand con-

tinues to rise toward the utility’s peak capacity, the

server sends signals to smart power meters in partic-

ipating homes, which in turn send signals – perhaps

wirelessly – to the subtending appliances, indicating the

need to conserve power (Fig.83.12).

If the number of participating households is large,

and if the aggregated power savings are sufﬁcient, then

the utility can avoid going to the open market to procure

power and the associated possibility of a brownout. As

demand begins to wane, the utility’s server signals the

smart power meters with a signal indicating that power

consumption can return to normal. Thus, home power

demand control is automated.

DLC ismost applicable in markets where retail pric-

ing is regulated, i. e., real-time pricing is not possible.

Consumers are offered incentives to participate in DLC

programs in the form of rebates from the electric utility.

Real-Time Pricing

Real-time pricing refers to the electric utility’s ability to

vary pricing for electric power over relatively short pe-

riods of time, for example, on a per-hour basis [83.4].

Fig. 83.12 Direct load control using smart power meters

Part I 83.2

1480 Part I Home, Ofﬁce, and Enterprise Automation

Relative usage

Relative rate

Relative usage

Relative rate

0 4 8 12 16 20

Relative usage

Home electricity usage, flat-rate pricing

Hour of day

0 4 8 12 16 20

Relative usage

Home electricity usage, real-time pricing

Hour of day

Fig. 83.13 Home electricity usage: ﬂat-rate versus real-

time pricing

Real-time pricing can be used – among other things –

to disincentivize power consumers from using power

during periods of peak demand. This reduces the prob-

Fig. 83.14 Real-time pricing using appliance control node

ability that the utility’s own capacity will be exceeded,

and minimizes the likelihood that the utility has to pur-

chase additional power on the open market.

When real-time pricing information is relayed to

consumers, they make decisions about how to use their

home electrics so as to keep their electric bill within

their spending limits. So, for example, during peak

hours in summertime, residents can choose to set ther-

mostats to a higher temperature in the mid-afternoon,

when energy prices are highest. Likewise, certain

household activities – such as laundry and dish wash-

ing – can be deferred until pricing is more amenable

(Fig.83.13). With enough participating households, the

aggregated power demand on the utility is eased to the

point that it does not have to purchase additional power

from a third party.

We have described a mechanism by which electric

utilities can automate demand control by manipulat-

ing the retail price of power. However, further power

consumption automation opportunities exist on the con-

sumer side. If the pricing information is relayed directly

to appliances – for example, via a smart meter – then

compatible appliances can automatically adjust their cy-

cles so as to minimize the net energy cost; for example,

the clothes washer, after having received a start signal

from the user, could delay starting its cycle until energy

prices are more favorable.

Alternatively, if pricing information is relayed to

a hypothetical appliance control node located in the

home, the control node can schedule appliance (and

HVAC, water heater, etc.) operation so as to meet

consumer-conﬁgured criteria regarding comfort, conve-

nience, and cost (Fig.83.14).

For example, the user could decide that he wants to:

1. Minimize cost during weekdays

2. Balance cost with comfort and convenience during

weeknights

3. Maximize comfort and convenience on weekends.

The control node would then conﬁgure and sched-

ule tasks accordingly. This could mean, for example,

switching off the air conditioning during weekdays,

raising the temperature slightly on weeknights, and op-

erating it normally all weekend.

A more sophisticated energy control node algorithm

might look something like that shown in Table 83.3.

Thus the user can achieve the optimal balance of

electric power cost and comfort and convenience in an

automated way.

Part I 83.2

Automation in Home Appliances 83.3 Emerging Trends and Open Challenges 1481

Table 83.3 Appliance energy control node algorithm

A/C Water heater Clothes washer Clothes dryer Dish washer Fridge

Weekdays Temperature: Temperature: Deferred Deferred Deferred High efﬁciency

high price −6.67

◦

C −6.67

◦

C operation operation operation

Weekdays Normal Normal High efﬁciency High efﬁciency High efﬁciency Normal

low price

Weekends Temperature: Temperature: High efﬁciency High efﬁciency Deferred Normal

high price −16.1

◦

C −12.2

◦

Weekends Normal Normal Normal Normal Normal Normal

low price

83.3 Emerging Trends and Open Challenges

83.3.1 Trends

Display Devices

Advancements in home appliance automation are driv-

ing – and are enabled by – advancements in display

devices. More and more appliances are available with

advanced light-emitting diode (LED), monochrome

liquid-crystal display (LCD), and full-color LCD dis-

play devices (Fig. 83.15). These user interfaces (UIs)

facilitate the richer user experience required for ad-

vanced status and control (input/output, I/O) functions,

such as those required by advanced automation tech-

niques.

For example, with either the DLC or real-time pric-

ing modes of energy management, the appliance user

must be informed of in-process energy management ac-

tivities. In the case of DLC, the user must know when

the utility is actively managing the appliance. For real-

Fig. 83.15 Appliance I/O device evolution

time pricing, the user needs to be apprised of the current

price of power. In either case, the user must have the

ability to control the appliance’s behavior. A user might

want to override DLC or the real-time pricing program

if some process, e.g., laundry, needs to be performed

immediately due to some immanent need. All of these

functions required the rich I/O facilities whichadvanced

display devices provide.

Interconnectivity

Most advanced appliance automation techniques re-

quire remote transmission of information to, or remote

retrieval of information from, the appliance. This im-

plies that appliances must interconnected – to each

other, and most importantly to the Internet. Household

energy management, remote performance analysis and

fault detection, and remote software maintenance are

all critically dependent on interconnectivity. Thus, in-

Part I 83.3

1482 Part I Home, Ofﬁce, and Enterprise Automation

terconnectivity is emerging as a major area of research

and development in the home appliance industry.

Smart Resource Usage

We have discussed at length the initiatives on the front

of home appliance automated electric power conserva-

tion. While home appliances become more convenient,

they are simultaneously becoming more efﬁcient and

more intelligent in their use of electricity, the culmina-

tion of which being automated energy management.

Beyond electricity, questions about supply and price

of water and natural gas are driving improvements in

efﬁciency on those fronts. From the user’s perspec-

tive, such savings are automated, realized internally by

advanced software algorithms, mechanical techniques,

and materials within the home appliance.

83.3.2 Challenges

Retail Cost

Home appliances are consumer products and, as such,

are highly dependent on sales volumes. In some cases,

an appliance only becomes proﬁtable to produce if hun-

dreds of thousands – or millions – of units can be sold.

Competition is ﬁerce and only grows more intense as

time goes on. Thus, tremendous efforts are put into

minimizing costs.

All the technology presented here – sensors, dis-

plays, and communication electronics – add cost to

the appliance. This creates a signiﬁcant barrier to the

introduction of such advancements on a large-scale ba-

sis. Consider that a mere dollar of additional cost to

an appliance could result in the loss of hundreds of

thousands of dollars of revenue for the manufacturer.

(Note that retail prices are set by the market, not by the

manufacturer, so additional manufacturing costs cannot

necessarily be passed onto the consumer.)

Thus, costs represent a signiﬁcant challenge to

the deployment of advanced automation techniques in

home appliances. Whereas the value of having – say

– a clothes washer is obvious to most consumers, the

value of having an interconnected washer is less so. The

home appliance industry is thus tasked with convincing

consumers that the added value provided by advanced-

automation appliances justiﬁes the incremental cost.

Personal Control and Privacy

Consumers are used to having full control over their ap-

pliances: When the start button is pressed, the machine

should start operating. Advanced automation requires

that users cede some of this control either to the lo-

cal machine or to some other remote device. Consumer

acceptance ofthis paradigmwill require signiﬁcant edu-

cation on the part of appliance manufacturers.It islikely

that, in order to achieve consumer acceptance, the ulti-

mate control for appliance behavior will have to remain

in the hands of the consumer, with the appliance and

other control systems simply providing suggestions for

machine operation.

Further, the introduction of interconnectivity might

present privacy concerns. It is not clear whether con-

sumers would be receptive to the notion of their home

appliances automatically relaying information to the In-

ternet, nor to the idea of an Internet node (e.g., the

electric utility) remotely accessing information in their

appliances. In order to gain consumer acceptance, appli-

ance manufacturers willneed toassure consumersof the

nature and security of the information being exchanged.

This will almost certainly involve using common In-

ternet information security techniques to ensure data

privacy.

Standardization and Interoperability

Particularly in the case of interconnectivity, stan-

dard implementation methods are required. If, for

example, the electric utility is to implement DLC,

it is not practical for the utility to use a dif-

ferent communication protocol for each appliance

vendor and each appliance model. Further, in the

case in which appliances from different vendors

within a single home must communicate with each

other, the appliances cannot be expected to know

each other’s proprietary protocols. In sum, a uni-

versal communication protocol is required. At the

time of this writing, standardization efforts are un-

derway both within the International Electrotechnical

Commission (IEC) and within the Association of

Home Appliance Manufacturers (AHAM) on this topic.

The outcome should be a standard for home ap-

pliance communication that permits full intervendor

interoperability.

Part I 83.3

Automation in Home Appliances References 1483

83.4 Further Reading

•

V.V. Badami: Home appliances get smart, IEEE

Spectrum 35(8), 36–43 (1998)

•

P. Bertoldi, A. Ricci, A. de Almeida: Energy

Efﬁciency in Household Appliances and Lighing

(Springer, Berlin Heidelberg 2001)

•

R.Kango, P.R. Moore, J. Pu: Networked smart home

appliances – enabling real ubiquitous culture, IEEE

5th Int. Workshop Netw. Appl. (2002) pp. 76–

•

K.J. Myoung, J.M. Lee, D.-S. Kim, W.H. Kwon:

Home network controlprotocol fornetworkedhome

appliances, IEEE Trans. Consumer Electron. 52(3),

802–810 (2006)

•

J. Nicholls, B.A. Myers: Controlling home and of-

ﬁce appliances with smart phones, IEEE Pervasive

Comput. 5(3), 60–67 (2006)

•

Y. Tajika, T. Siato, K. Teramoto, N. Oosaka,

M. Isshiki: Networked home appliance system

using Bluetooth technology integrating appliance

control/monitoring with internet service, IEEE

Trans. Consumer Electron. 49(4), 1043–1048

(2003)

References

83.1 US Energy Information Administration,

http://www.eia. doe.gov

83.2 J.C. Gallawa,

http://www.gallawa.com/microtech/history.html

83.3 Paciﬁc Northwest Demand Response Project,

http://www. nwcouncil.org/energy/dr

83.4 Federal Energy Regulatory Commission: Assessment

of demand response and advanced metering 2007

staff report (2008), http://www.ferc.gov/

industries/electric/indus-act/demand-response/

dem-res-adv-metering.asp#skipnavsub

Part I 83

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