AN ADAPTIVE SYSTEM TO CONTROL CONSUMER

ELECTRONICS BASED ON EARTHQUAKE EARLY WARNING

Takashi Kokawa, Ryota Sakamoto, Hitoshi Ogawa, Victor V. Kryssanov

Faculty of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, Japan

Keywords: Consumer electronics network, Earthquake early warning, Constraint satisfaction problem.

Abstract: In Japan, earthquakes happen on a regular basis. There is an earthquake early warning system operated by

the Japan Meteorological Agency. By sensing P-waves, it can notify people a few seconds before the

earthquake reaches them. Since only few seconds are left, it is often difficult for people to act with

consideration on who is where at the moment, what consumer electronics should be turned off, and how to

ensure a family’s safety in their house. We developed a system that supports people with control of

network-connected home appliances when an earthquake occurs. The system utilizes three types of control

rules: general, family-related, and personalized for each type of consumer electronics. As there can often be

operational conflicts if applying the rules simultaneously, a conflict-resolving mechanism is implemented,

based on an optimisation algorithm for weighted constraint satisfaction problems. A pilot study of the

system deployment is described, and its results are briefly discussed in the light of the related work.

Conclusions are drawn, and future plans are outlined.

1 INTRODUCTION

About 2000 earthquakes happen every year in Japan,

so that this country is often called earthquake-ridden.

It is a serious problem to prevent the occurrence of

secondary earthquake-provoked disasters, such as

fires, short-circuits, etc. With the recent advent of

consumer electronics networks, real-time earthquake

information can be received by every household, and

it can thus be used to control consumer electronics

and reduce the risk of the secondary disasters.

Real-time information about the seismic

activity is provided by the earthquake early warning

system (Doi, 2002) operated by the Japan

Meteorological Agency (JMA). By sensing primary

waves (P-waves), this system can notify people, e.g.

via the Internet, several seconds before the

earthquake reaches them.

There has been developed an automatic consumer

electronics control system by the Japan Electronics

and Information Technology Industries Association

(JEITA, 2005). When an earthquake early warning is

received, the system provides services such as

alarming people, stopping gas, opening doors, etc.

This system does not, however, comply with the

specific situation of each particular household (i.e.

information about who live in, where they are, what

they currently do, etc. is not utilized by the system).

In this paper, we propose an intelligent consumer

electronics control system for earthquake-caused

disaster prevention. The system uses family-specific

knowledge and provides for generally a higher level

of safety for the family members than other systems

having similar goals.

The system realizes an agent-based architecture,

and it is thus quite reliable in earthquake conditions.

Agents are installed in every room (e.g. of a house).

Each room agent is autonomous, monitors electronic

appliances and the human status in the room, and

controls the electronics when an earthquake happens.

For the control, countermeasure agents processing

different types of rules are developed. During an

earthquake, a countermeasure agent receives

earthquake information and selects appropriate

constraints from an electronics control set. A room

agent operates the electronic appliances based on the

constraints. As there can often be conflicts when

applying control rules obtained from different

countermeasure agents simultaneously, a conflict-

resolving mechanism has been implemented, and the

system finds an optimised control set of rules by

solving a weighted constraint satisfaction problem

with achievement parameters.

250

Kokawa T., Sakamoto R., Ogawa H. and V. Kryssanov V. (2006).

AN ADAPTIVE SYSTEM TO CONTROL CONSUMER ELECTRONICS BASED ON EARTHQUAKE EARLY WARNING.

In Proceedings of the International Conference on e-Business, pages 250-256

DOI: 10.5220/0001426202500256

 SciTePress

In the following sections, the earthquake early

warning system is first outlined. Second, the

proposed system architecture is presented. Next, it is

explained how the system agents act. The control of

home appliances in an earthquake situation is

analysed through a pilot study. Finally, related work

is discussed, and conclusions are given.

2 THE EARTHQUAKE EARLY

WARNING SYSTEM

All earthquakes produce two types of shock waves:

primary waves (P-waves) and secondary waves (S-

waves). P-waves arrive first and rarely cause any

damages. S-waves arrive next and often result in

destruction and loss of lives. The earthquake early

warning system operated by JMA utilizes current

seismic data, such as the magnitude of an earthquake

and the place of its occurrence, obtained by sensing

and processing P-waves. Since P-waves are

normally propagated about twice as fast as S-waves

(excepting for the case of epicentral earthquakes),

the system can provide earthquake information

seconds to tens of seconds before the damaging

wave hits an area. The system is presently deployed

on an experimental basis, and various organizations

and companies participate in the experiment.

In the presented study, a program developed by

the Japan Weather Association and the Earthquake

Research Institute at the University of Tokyo is used

to calculate the expected seismic intensity and time

of the S-wave arrival at a specific location for a

given earthquake.

3 AGENT-BASED

ARCHITECTURE

To achieve a high level of operational robustness

and autonomy, the proposed system implements a

multi-agent architecture. There are several types of

agents.

A room agent monitors a room to get the personal

status and the consumer electronics status, and it

then saves the data to the household status database.

The method of obtaining information may differ for

each agent, e.g. who is in the room can be monitored

using either web-camera or RFID tags. A

countermeasure agent proposes countermeasure

rules for earthquake disaster prevention, which are

specific to the place of a room agent’s installation.

When an earthquake occurs, all countermeasure

agents propose control actions, which may be

inconsistent because of different knowledge

possessed by the agents. A conflict resolution

method is used to find a balanced solution for all the

agent surroundings.

The system operates as follows (

Figure 1). An

earthquake information agent (EIA) at each house is

a “JAVA wrapping” of the program processing

earthquake early warning data. An EIA receives an

earthquake early warning from JMA and calculates

the S-wave arrival time and the expected seismic

intensity. The EIA sends a message to three

countermeasure agents, which are an earthquake

countermeasure agent (ECA), a personal care agent

(PCA), and a precondition for consumer electronics

control agent (PCCA). The ECA utilizes the

knowledge of general countermeasures for

earthquake disaster prevention. The PCA applies the

knowledge of personalized countermeasures by

utilizing family-related information. The PCCA

makes use of the knowledge of specialized

countermeasures to control home appliances. The

countermeasure agents propose constraints to room

agents. After a room agent communicates or

attempts to the countermeasure agents to update its

rules, it generates, through resolving achievement-

weighted constraints, a set of instructions to control

the electronics set up in the room.

home

Eart hquake Early

Wa r n i n g

room

control

count ermeasure agent s

eart hquake informat ion

inst r uct ions

Room Agent

ECA PCCA PCA

Eart hquake

Inf or mat ion Agent

Household St at us

Dat a Base

const raint s

CE and human

st at us

Consumer

Electronics

Figure 1: The system architecture.

AN ADAPTIVE SYSTEM TO CONTROL CONSUMER ELECTRONICS BASED ON EARTHQUAKE EARLY

WARNING

251

4 CONSTRAINTS FOR THE

ELECTRONICS CONTROL

A room agent decides on consumer electronics

control by solving an achievement-weighted

constraint satisfaction problem, AWCSP (Kokawa

and Ogawa, 2004). The AWCSP solver is an

enhanced reasoning method for constraint

satisfaction problems (CSP) that allows for

obtaining an optimised solution when constraints are

too strict. The AWCSP is represented with a set of

variables, a domain of values for each variable, and

a set of constraints in a way similar to the classic

CSP (Walliser et al., 2004). It also requires a set of

constraint weights and a set of constraint

achievement degrees defined.

Consumer electronics states and human actions

are represented with variables as follows: a set of

consumer electronics states, CE = {ce

, ce

, …,

}, where n is the number of electronic appliances

installed; a set of human actions, ACT = {act

, act

…, act

}, where m is the number of the family

members. Domain sets of the variable values are

represented as follows: D

= {

, …,

and D

ACT

= {

act

, …,

act

}, respectively.

Constraints for the variables are produced by the

countermeasure agents by utilizing the relevant

knowledge. In a room agent, a set of constraints is

represented as C = {c

, c

, …, c

}, where k is the

number of constraints which are sent from

countermeasure agents.

The ECA handles general countermeasure rules

for earthquake disaster prevention, which are usually

pre-defined. Constraints of the agent are represented

as ECc

, where j is the rule number. The PCA deals

with family-related rules by utilizing information

about the current status of each family member (as

well as of other people in the rooms), and the

corresponding constraints are represented as PCc

The PCCA processes personalized rules based on a

control policy defined for the house, and its

constraints are represented as PCCc

. The policy

can be set up to allow for sending camera-recorded

data to a server; it would then be possible to use the

video for rescue operations or in an analysis.

Below, this is a fragment of the knowledge of

countermeasure agents:

state(A, B) means that A implies B.

ECA:

Rule1: IF (Seismic intensity >= 2)

Send a Constraint

ECc

{state(ce

, Speaker), ce

“Announce(earthquake

information)”, i = 1,…, n}

Rule2: IF (Seismic intensity >= 3)

Send a Constraint

ECc

{state(ce

, Heater), ce

“OFF”, i = 1,…, n}

Rule3: If (Seismic intensity >= 4)

Send a Constraint

ECc

{state(ce

, Door), ce

“Open”, i = 1,…, n}

Rule4: If (Seismic intensity >= 4)

Send Constraints

ECc

{act

= “Hide under

furniture”, h

is a person}

ECc

{state(ce

, all electronics),

= “Off”, i

= 1,…, n}

PCA:

Rule1: IF (There is a person h)

Send a Constraint

PCc

{state(ce

, light), ce

= “On”,

is near h}

Rule2: IF (Seismic intensity =< 2 and a

person h is sleeping)

Send a Constraint

PCc

{act

= “Keep sleeping”}

Rule3: If (Seismic intensity >= 3 and

“There is a child at home”)

Send a Constraint

PCc

{act

= “Accompany the child”}

PCCA:

Rule1: If (Seismic intensity =< 3 and

“Video is recording”)

Send a Constraint

PCCc

{state(ce

, Video), ce

“On” , i = 1,…, n }

Rule2: If (Seismic intensity >= 5 and

“Agreement for recording”)

Send a Constraint

PCCc

{state(ce

, Camera), ce

“Record” , i =

1,…, n}

Owing to the different knowledge bases of the

countermeasure agents, constraints generated by the

agents may often conflict. For the conflict resolution,

a method that utilizes weights assigned to the

constraints has been proposed (Lau, 2002). A set of

constraint weights is represented as W = {w

, w

, …,

}, k is the number of constraints. When only the

constraint weights are used, some rules may get

completely ignored, e.g. when the seismic intensity

is over 4, the ECA sends ECc

for room agents. If

there is no furniture to hide under it in the room, the

ECc

is never satisfied, and the room agent produces

no instructions. The room agent should, however,

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recommend a substitute action for the person, such

as “Stay away from dangerous objects”. If one tries

to represent this agent behaviour with weighted

constraints, the rules become complicated, and it

becomes difficult to maintain the integrity of the

agent rules.

To cope with this problem, achievement degrees

are defined for the constraints. If a constraint is fully

satisfied, the room agent chooses a variable value

having the highest achievement degree. An

achievement degree is represented as a parameter

showing to what degree the constraint is achievable

in the given situation. The achievement parameter

thus consists of a variable and a threshold. The set of

achievement variables A = {a

, a

, …, a

} represents

the “satisfaction degree”. The set of achievement

thresholds F = {f

, …, f

} gives thresholds that the

values of a

must achieve to make the constraints

satisfied.

The achievement degrees for ECc

are presented

Table 1. ECc

is to issue recommendations that

would help maintain a higher safety level for the

family members. A safety level is a mapping to the

achievement degree of the constraints; the safety

level of the action defined in a constraint makes the

achievement degree 100%, the lowest level

corresponds to the achievement degree 0% (i.e. no

action).

The achievement degrees for consumer

electronics -related constraints, such as ECc

, are

determined by the number of appliances actually

turned off.

Table 1: Safety levels and recommended actions.

Safety level Action group

5 Hide under furniture (table, etc.)

4 Stay away from dangerous objects

(window, vase, etc.)

3 Be accompanied.

2 Make a contact (via IP phone,

video phone, etc.)

1 Report location.

0 No action required.

Weights are assigned to the constraints at the time

of constraint definition. The general

countermeasures and maintaining the family

members’ safety have higher priorities and, hence,

higher weights, while other rules have lower weights

(see

Table 2). Achievement thresholds for the

constraints are dynamically calculated by the

countermeasure agents, depending on the time

remaining until the earthquake and current

information collected by room agents.

Table 2: Constraint Weights.

Constraint Weight

ECc

PCc

PCCc

Assignments of values to the variables are made

via an optimisation procedure. Room agents produce

sets of assignment values corresponding to

achievement degrees higher than the achievement

threshold of a constraint. Room agents calculate M

an “optimisation degree” of the set as the following

sum:

∑

(if f

= 100)

−

100

(else).

If a constraint c

is completely satisfied, the

corresponding summand is the constraint’s weight w

Otherwise, the added value is the product of the

constraint’s weight w

and the distance of the

achievement degree value a

to the achievement

threshold f

; n is the total number of constraints.

5 PILOT STUDY

In this section, we describe an example of the

application of the developed system to control the

situation in a room with a predefined environment

during an earthquake (also, see the definitions of the

constraints in the previous section).

The environment of room A:

State(ce

, TV),

= {“Entertainment channel”, “News

channel”, “Sports channel”, “Off”};

State(ce

, Speaker),

AN ADAPTIVE SYSTEM TO CONTROL CONSUMER ELECTRONICS BASED ON EARTHQUAKE EARLY

WARNING

253

= {“On”, “Announce(x)”, “Off”};

State(ce

, Room light),

= {“On”, “Off”};

State(ce

, Corridor light),

= {“On”, “Off”};

State(ce

, Camera),

= {“Record”, “On”, “Off”};

State(ce

, Heater),

= {“On”, “Off”};

State(ce

, IP phone),

= {“Connect(room y)”, “Off”};

State(act

, Family member),

act

= {“Watch TV”, “Hide under

furniture”, “Stay away from

dangerous objects”, “Be accompanied”,

“Make a contact”, “Report location”,

“No action required”};

= “Entertainment channel”,

= “On”,

= “Off”,

= ”Off”,

= ”On”,

= ”Off”,

act

= ”Watch TV”

There is a child in room B.

(Other details

of the surroundings of room B are omitted.)

Case 1:

The system processes an earthquake early

warning: the seismic intensity is 5 and the remaining

time is 15 seconds.

Table 3 lists constraints for the

room agent that are sent from countermeasure agents.

Achievement thresholds are set as follows. The

constraint c

“turn off all the heaters” must be

completely satisfied, and its achievement threshold

is therefore 100%. It is possible to simultaneously

announce both the earthquake information and

instructions to the people, and the achievement

threshold of “announce the earthquake information ”

is 100%. Since the domain of c

is binary, the

achievement threshold f

is 0%. c

does not have to

be fully satisfied if there is a higher priority

constraint, and the achievement threshold f

is 20%,

because there are only “less dangerous” electronic

appliances in the room (if the room is a kitchen, this

achievement threshold would however be more than

50%). As there is no door lock in room A, the

constraint c

does not have to be satisfied, and the

value of f

is 0%. There is a person in room A,

therefore lights must be turned on near the person,

and the value of f

is set 100%. The achievement

thresholds f

and f

are 40% and 60%, respectively,

because there is a child in room B, who should be

contacted via the IP phone or accompanied.

There is a conflict between c

and c

: there is no

furniture in room B. Depending on the remaining

time, the safety levels of the family member in room

A and of the child in room B are balanced by the

corresponding achievement thresholds. If there is

enough time to go to the child’s room, act

specified as follows: “Hide under furniture” and

“Accompany the child”. Based on the values of M

calculated for each possible scenario, the system

generates the following set of variable values (this

set corresponds to the greatest M obtained):

= “Off”,

= “Announce (earthquake

information, ‘Go to

room B’)”,

= “Off”,

= “On”,

= “Record” (to record the result of

the family member’s action),

= “Off”,

act

= “Accompany the child”

Achievement degrees assigned to the variables are

given in

Table 3. The optimisation degree M is equal

approximately to 24.

Table 3: Constraint parameters in Case 1.

Received

constraint

ECc

4 100 100

ECc

6 100 100

ECc

5 0 0

ECc

5 40 60

ECc

3 20 57

PCc

4 100 100

PCc

5 60 100

PCCc

2 0 100

Case 2:

Same as Case 1, but the remaining time is 5

seconds. The achievement threshold f

becomes 80%,

as for anyone in room A, it is now impossible to

reach room B before the earthquake hits. The action

recommended is to hide under the desk, and the

countermeasure to increase the safety level of the

child may, depending on the phone location, be to

talk to the child via the IP phone. The recommended

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actions to control the consumer electronics are then

as follows (also see

Table 4):

= “Off”,

= “Announce (earthquake

information, ‘Hide under the desk

and talk to the child via the IP

phone’)”,

= “On”,

= “Off”,

= “Record”,

= “Off”,

= “Connect (room B)”,

act

= “Hide under the desk and use the

IP phone”

Table 4: Constraint parameters in Case 2.

Received

constraint

ECc

4 100 100

ECc

6 100 100

ECc

5 0 0

ECc

5 80 100

ECc

3 20 43

PCc

4 100 100

PCc

5 60 66

PCCc

2 0 100

The calculated optimisation degree M is equal

approximately to 23.

Case 3:

Same as Case 1, but the seismic intensity is

≤

The expected effect of the earthquake is not severe.

The system only announces the earthquake

information and/or changes the TV channel to news.

There is only one constraint ECc

, and it can be fully

satisfied.

6 A LITTLE RELATED WORK

Most of the studies reported in the literature deal

with earthquake early warning systems to merely

provide for efficient and effective announcement of

the earthquake information (e.g. Doi, 2002; Wu et

al., 2004). There were, however, reports in the past 2

years about developed systems that have goals and

capabilities similar to the ones pursued in the

presented study.

The system proposed by the JEITA (JEITA, 2005)

is an automatic consumer electronics control system

developed in Japan. A similar system was developed

by the Seismic Warning Systems Incorporated

(SWS), using the earthquake early warning in the

west coast of the U.S (SWS, 2004). These systems

can control the electronics for the earthquake

secondary disaster prevention by using the

corresponding earthquake early warning systems:

e.g. they can shut off gas, issue warnings, open door

locks and so on. The systems have, however, to have

countermeasures defined for every possible scenario

in advance, and if the environment changes, the

recommended actions may become ineffective or

even dangerous. Besides, the consistency of the

system knowledge bases is hard to maintain due to

the changing surroundings.

The system developed in the presented study is

able to adapt to dynamic environments, as each

room agent monitors its room and updates the

system knowledge- and data-bases. Furthermore, the

proposed system ensures a high level of operational

transparency by providing access to its data- and

knowledge-bases for its users. This is a unique

feature that, to our knowledge, is not present in any

other systems having similar purposes.

7 CONCLUSIONS

In the presented study, a prototype of an intelligent

adaptive system to control consumer electronics

based on earthquake early warning has been

developed. The system has an agent-based

architecture, and it controls home electronic

appliances via solving an achievement-weighted

constraint satisfaction problem. A pilot-study of the

deployment of the system was outlined, and some

typical situations of the system operation were

considered.

Presently, the system works with a simulator to

examine various households and earthquake-related

situations. We are planning to test the system in a

real environment in the near future.

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In: Jochen Zschau u., Andreas N., Kueppers (eds),

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Lau, H.C., 2002. A New Approach for Weighted

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