DISTRIBUTED EMERGENCY MANAGEMENT

WITH SPATIAL SCENARIOS

Peter Sapaty

Institute of Mathematical Machines & Systems, National Academy of Sciences,

Glushkova Ave 42, Kiev 03187, Ukraine

Robert Finkelstein

Robotic Technology Inc., 11424 Palatine Drive, Potomac, Maryland 20854, USA

Joaquim Filipe

Departamento Sistemas e Informática, Escola Superior de Tecnologia de Setúbal,

Setúbal 2910-761, Portugal

Keywords: Critical infrastructures, key resources, emergency management, emergent societies, crisis relief, information

technologies, distributed control, WAVE-WP model, wearable electronic devices, mobile robotics, spatial

scenarios.

Abstract: A radically new approach will be described for the fully distributed and dynamic management of advanced

crisis relief operations and missions. It is based on the installation of a universal “social” module in many

existing and massively used data processing and control devices, including (but not limited to) internet hosts,

laptops, mobile robots and mobile phones. These modules can collectively interpret a special scenario

language while exchanging higher-level program code with accompanying data and control in parallel. This

can dynamically integrate any scattered post-disaster human and technical resources into an operable

distributed system which, from one side, is effectively supervised externally, and from the other side, is

capable of solving complex self-analysis, coordination, survivability, relief, and reconstruction problems

autonomously.

1 INTRODUCTION

1.1 The Grim Big Picture

Millions of people are on the move, traffic jams

everywhere. Houses destroyed, infrastructures gone,

winds hundreds kilometers per hour, flooding and

fires. No electricity, shortage of food and fuel, usual

ties broken, businesses vanished, jobs lost. No

central authorities or services, looting and

lawlessness… This is becoming a familiar picture

throughout the world, especially due to global

warming and climate change. Katrina and Rita are

the recent sad examples. Earthquakes are another

disaster area, like the recent one in Pakistan, and the

tsunami a year before. Manmade disasters caused by

armed conflicts and terrorist attacks are effectively

contributing to this list too.

How to regain integrity, restore law and order,

and assemble scattered resources for a collective

survival? How to rebuild the damaged territory,

revive the previous infrastructures or create new

ones, and return to normal life?

In Fig.1, a symbolic picture of the post-disaster

area, once representing an integral organism, is

shown with the wreckage of living quarters,

organizations and infrastructures, also separated and

scattered individuals and their emergent grouping.

Despite indiscriminate damages, the disaster area

can still hold key human, technical and natural

resources; its parts can still be able to communicate

with each other. For example, cellular towers, at

least some of them, can still be operating, and/or

Sapaty P., Finkelstein R. and Filipe J. (2006).

DISTRIBUTED EMERGENCY MANAGEMENT WITH SPATIAL SCENARIOS.

In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics, pages 57-66

DOI: 10.5220/0001221500570066

 SciTePress

access to internet may remain available. Radio

communications, usually local, can be helpful too,

and some units in the area may have satellite phones.

The electric grid power may remain available, and

the same grid can potentially be used for data

communications too (such promising projects

already exist). Possible stratospheric solutions for

broadband communications, which are discussed

now too, may look promising to cope with the crisis

situations. So there may be sufficient resources for

self-survival and even self-recovery after the major

disasters, especially with an external aid hurrying to

the area, but they may be highly scattered and very

much disorganized.

Individuals

Wreckage of regions, organizations, and infrastructures

Emergent grouping

Casual

communications

Figure 1: A grim picture of the disaster area.

Restoring integrity and coordination in the disaster

area is becoming a primary goal in emergency

management efforts.

1.2 Emergency Management

Emergency management, EM (Bullock, 2004), due

to the increased world dynamics, is one of the

hottest topics today. The emergency managers

around the world are faced with new threats, new

responsibilities, and new opportunities. It is widely

believed (Nunn, 2005) that the combination of novel

technologies and data bases can allow law

enforcement and intelligence investigators to

identify potential terrorist plots, use a multitude of

data bases that may contain hidden patterns of

information about transactions needed to execute

plots, and then mount preemptive strikes to stop

their plans.

The National Response Plan (2004) establishes a

comprehensive all-hazards approach to enhance the

ability to manage domestic incidents. The plan

incorporates best practices and procedures from

different incident management disciplines. Another

prominent document, The National Infrastructure

Protection Plan, NIPP (2005) provides a unifying

structure for the integration of all critical

infrastructures and key resources protection efforts

into a single national program.

However, the existing efforts are actually

offering yet another infrastructures, to be built on the

same principles as the existing ones, i.e. consisting

of specialized components located in certain places

and communicating with each other, with a good

deal of central control over them. Due to this, they

may inevitably be as (if not more) vulnerable to

attacks and failures as other infrastructures, and may

become a burden rather than savior.

Even in the relatively modest Katrina case, local

infrastructures were indiscriminately fragmented and

totally inoperable (while malicious ones thriving),

and federal bodies showed clumsiness and

inefficiency. The new global infrastructures outlined,

like what we see in NIPP, may result in a similar

performance in case of major disasters caused by

hurricanes, earthquakes, or WMD attacks.

1.3 New Approaches Needed

We believe that the critical infrastructure protection,

recovery, and relief ideologies and technologies

should be based on quite different, revolutionary

rather than evolutionary, principles, and they should

evolve and operate in other time-space dimensions

than the traditional infrastructures and forces that

can harm them, in order to be incomparably superior

and unaffected themselves in case of major crises.

A completely different approach is being

developed of how to penetrate into any distributed

and open systems and establish an overwhelming

power over them (destruction of malicious

infrastructures in these systems being an option).

Any global or local scenario we want to

implement over any area or system is formulated in

a special spatial control language, which is

interpreted cooperatively in a distributed system

widely using smart mobile program code covering

the system or its parts in parallel. This provides

spatial hologram-like algorithms which dynamically

exist in between system components rather than

inside them, often being unobservable and

unreachable by conventional means.

Actually, this work follows a sort of an

intelligent super-virus ideology, with its potentially

unlimited self-penetration and self-recovery

possibilities. The approach can also setup, at runtime,

any needed infrastructures over scattered post-

ICINCO 2006 - INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION

disaster human or technical resources, and these

infrastructures can evolve and freely migrate in both

physical and virtual worlds, self-recovering after

damages and preserving integrity and goal

orientation. The paper summarizes the technology

called WAVE-WP that serves these purposes,

outlines its applications and possible implementation

with the use of massively wearable devices.

Examples of spatial programming of some

exemplary relief operations will be demonstrated too.

The paper also uses and extends the material

previously reported at (Sapaty, Sugisaka, 2006).

2 THE WAVE-WP PARADIGM

The distributed computation and control WAVE-WP

(or World Processing) model and technology

(Sapaty, 1999, 2005; Sapaty, Sugisaka, 2005) are

based on a higher-level language describing parallel

distributed solutions in computer networks as a

single seamless spatial process rather than traditional

collection and interaction of parts (agents), while

shifting these and other routines to an efficient

automatic implementation.

Communicating copies of the WAVE-WP

language interpreter (WI) should be present in

sensitive points of the system to be governed (like

internet hosts, robots, troop carriers, dismounted

soldiers, separated groups of individuals, laptops,

mobile phones, etc.), as shown in Fig. 2 for the post-

disaster area of Fig. 1.

Dynamic channels

Wave interpreters

Figure 2: Wave interpreters in sensitive points of the

distributed system.

Parallel spatial scenarios (or waves) written in

the language can start from any interpreter, covering

the network at runtime and cooperating with each

other in the distributed space. The approach often

provides hundreds of times application code

reduction and simplification, allowing us to

concentrate on efficient global solutions rather than

implementation details.

Spreading via networked WIs, waves can create

dynamic knowledge infrastructures arbitrarily

distributed between the system components.

Subsequently or simultaneously navigated by same

or other waves, they can effectively support

distributed databases, advanced command and

control, global situation awareness, parallel

inference, and autonomous decisions. It is

convenient to operate in this seamless virtual world

fully ignoring its physical distribution, whereas

virtual networks can migrate (partially or as a

whole) in physical networks while being processed.

Installed in advance (or loaded in an emergency)

in different components that may happen to be

located in a disaster area, with possibilities of their

communication using any remaining channels, WIs

can convert the whole area into an operable self-

organized system. The latter being able to solve

complex tasks on itself, where high-level relief

scenarios in WAVE-WP can start and evolve from

any interpreter, covering the whole system or its

needed parts at runtime (see Fig.3).

Spatial scenario

Knowledge network

Waves

Continuous

processes

Figure 3: Converting the disaster area into an operable

system.

The technology has been working successfully in

(mainly static) computer networks since 1990, with

many computers distributed between different

countries, via the Internet. From 1993, many

complex parallel and distributed solutions were

shown with the creation of distributed virtual

infrastructures mounted between UK, Germany,

Canada, and the US, also multiple chases of mobile

agents & objects by the other ones throughout the

globe. Information about these projects can be found

DISTRIBUTED EMERGENCY MANAGEMENT WITH SPATIAL SCENARIOS

in (Sapaty, 1999).

The current orientation of this activity has been

fully on highly dynamic networks, which may

include Internet, mobile cellular networks, radio and

satellite communications, etc. There may also be no

networks at all in the post-disaster zone, in the usual

sense. In the worst case, people can see each other at

a distance (e.g. sitting on floating roofs and

shouting) passing manually the higher-level

commands and accompanying data in the user-

friendly WAVE-WP version. The people can happen

to be on a constant move, changing casual links with

each other over time.

The technology is fully orienting on such loosely

connected, dynamic and emergent systems. We can

write arbitrary complex distributed algorithms

finding the needed solutions in completely

distributed environments with such unsafe and

emergent links. This can allow us to start both local

and global businesses in the disaster zone without

restoration of regular communications, which, of

course, would be much helpful.

3 WAVE-WP LANGUAGE

3.1 The Language Basics

We are considering here only the top definition of

the WAVE-WP language, shown in Fig. 4, with

more details in (Sapaty, 1999, 2005).

wave → { advance ; }

advance → { move , }

move → constant | variable | [ rule ] ( wave ) |

{ move act }

rule → forward | echo

act → fusion | flow

variable → nodal | frontal | environmental

constant → information | matter | code

Figure 4: WAVE-WP language syntax.

Starting from a certain position, the program, or

wave, navigates in physical or virtual space, with

successive advances (separated by a semicolon)

starting from positions reached by the previous

advances. An advance may consist of moves

(separated by a comma) which can develop in

parallel, each one from the same position.

Moves may: reflect the result directly, as a

constant or variable; represent any wave in

parentheses optionally prefixed by a rule; be

arbitrary expressions where other moves are

separated by elementary operations, or acts.

Rules being forward rules, coordinating

spreading of waves or setting up special navigation

contexts, or echo rules detailing the fusion and

return of (remote) states and data. Acts classify as

fusion acts producing new values from operands,

and flow acts moving data and control in space. The

same operations on waves may be set up by both

rules and equivalent to them acts within the

expressions. Variables may be: nodal, dynamically

associated with space positions and shared by

waves; frontal, moving in space with control; and

environmental, accessing the navigated environment

in points reached.

Constants and variables may represent both

information and physical matter; they may also

represent program code to be created, processed or

modified with a subsequent execution as waves, thus

providing programming flexibility in dynamic

environments.

3.2 Spatial Interpretation

What follows from this language definition, is the

unwrapping and replication of the recursive

formulae, rather than traditional reduction, as shown

in Fig. 5.

advances

Positions

reached in

physical or

virtual space

Start

Spatial

coordination

with rules

Control & data echoing

Figure 5: Spatial evolution of waves.

The wave program matches, conquers, floods,

covers the distributed physical or virtual world in

parallel, establishing full control over the space.

Each act is performed in the reached space positions

on local data there, or on what is obtained and

returned by other waves of the expression. The

resultant value on any construct comprises all values

obtained in the points of space reached by it. All

constructs return control states, which are merged

and generalized on higher levels with the use of

rules, for making hierarchical spatial decisions.

ICINCO 2006 - INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION

A number of successful implementations of this

approach have been made in different countries,

with public domain of the previous implementation

available on the Internet, for example, in Canada

(Wave system, 2003)

. The new, advanced, version is

currently being re-implemented and patented, with

orientation on both software product and direct

“wave chip”.

4 USING WEARABLE DEVICES

Emergency management may be fundamentally

assisted by the massively wearable individual data

processing and communication devices, which are

expected to remain with individuals under any

circumstances. WIs, installed in them (this can be

done without problems, taking into account the

existing experience of implementation of the WAVE

system on different platforms and compactness of

the language interpreter) can make the whole

societies, especially emergent ones in the disaster

areas, to be programmable and controllable in the

way required, despite the scattering of resources and

limited communications.

Mobile phones, the undisputed leader among

wearables, are expected to be the most common

consumer electronics device on the planet (Mobiles,

2005). By the end of 2009, some 2.6 billion mobiles

will be in regular use around the world. Mobiles, for

example, are catapulting rural Africa into the 21st

century, making it the world's fastest-growing

cellphone market (LaFraniere, 2005). They are

enabling millions of people to skip a technological

generation and bound straight from letter-writing to

instant messaging. Asia is the next fastest-expanding

market.

Many also use GPS, digital cameras, portable

PCs along with mobile phones, and there already

exist advanced products that combine all these and

many other features within a single piece (including

also Bluetooth, WiFi, phone radio and TV (GPS,

2006; Samsung, 2005). 3G, or third generation,

brings broadband for mobiles too (3G, 2005). Also,

the recently unveiled sub-$100 laptop design (Sub-

$100, 2005), with its internet wireless access and a

hand crank for when there is no power supply, is

expected to contribute drastically to the

unprecedented electronic integration of the whole

world. Some of the currently popular massively

wearable devices are shown in Fig.6.

We may assume that these devices (at least some

of them) would remain able to communicate with

each other during and after the disasters via the

wireless networks, internet, radio or any other

channels, and in the worst case even via humans

(who, using voice, handwriting or gestures, can pass

manually the needed code and data, with the return

to an electronic WI level at the reception end).

Figure 6: Examples of massively wearable devices.

5 MANAGEMENT EXAMPLES

We will consider here only elementary examples of

spatial programming in WAVE-WP for some tasks

that may relate to emergency management, with

code simplifications necessary to fit the limited

paper space.

5.1 Spatial Counting of Casualties

Let us consider a fully distributed and parallel

counting of a total number of casualties in the

disaster area, on all affected regions, assuming for

simplicity that only a single WI is used for this task

in each region or group of individuals. (The

interpreter-participant can be negotiated locally if

more than one available in the group/region.)

The following program can be applied from any

WI as an entry or starting one, which can be far

away from the disaster area (say, located in a federal

center). This entry node can also happen to reside

within the area as a special or emergently selected

body or individual (or one of them).

frontal(Domain);

Domain = <disaster area>;

USER =

sum(

hop(direct, Domain);

repeat(

done(apply(casualties)),

hop(anylinks, Domain, first)))

DISTRIBUTED EMERGENCY MANAGEMENT WITH SPATIAL SCENARIOS

Let us explain its work step by step, where various

parts of the program can replicate and operate in

different places of the distributed word, in parallel,

always preserving scenario integrity and

subordination to global control. The latter being

parallel and distributed too.

frontal(Domain)

This declares variable Domain in the starting node

as a frontal one, which will subsequently propagate

with the program control in a distributed space, as its

property.

Domain = <disaster area>

In the same node, Domain is assigned proper

parameters of the disaster area (represented, say, as a

polygon or a set of them, here not detailed further),

sufficient to determine whether a point with given

coordinates may belong to the area of concern.

USER = sum( … )

Initiates in the starting node a distributed process

(enclosed in braces) covering the whole disaster area

and finding casualty numbers in different places

(regions) in parallel, summing them in parallel too.

The final result will be displayed to the human

operator in the entry node (represented by

environmental variable USER). The top control of all

these (hierarchical) processes will remain in the

starting node.

hop(direct, Domain)

This tries to make a direct, parallel, electronic hop

from the starting node to as many directly reachable

units within the area in Domain as possible. The

hop may use for this any available means and

channels for finding such nodes (existing records,

databases, and cable, cellular, satellite or radio links,

with selective or broadcasting mode of operation).

The number of nodes accessed directly may be

limited, especially if the communication

infrastructures in the area are damaged, and also it is

far from the starting node.

repeat( … )

From the node(s) reached above, starts a spatial

navigation loop throughout the whole disaster area,

with the following two parallel branches in its body.

done(apply(casualties))

This first branch in each reached node activates

an external procedure casualties, which counts

the number of humans badly affected in the current

region, resulting in forming of an open value of this

branch. Enclosure of the branch by rule done

makes it also a terminal one in each node (i.e. from

which the spatial loop will not continue). The

casualties procedure may be fully automatic,

performed, say, by special observation robots;

automated, with manual use of electronic equipment

to check damages; or fully manual, with casualties

counted by people visually and then returned to the

electronic level via a terminal to the wave interpreter.

hop(anylinks, Domain, first)

This second branch of the loop tries to hop from

a node in the disaster area to other nodes of the same

area, given in Domain. It uses any available local

communication means from the current node which,

for example, may be registered in its mobile phone

as dial numbers of people this person knows and

communicates regularly. These may also be still

operating radio channels, usually of a limited

distance, or longer range Bluetooth-like direct

wireless communications used between different

mobile phones and PCs (i.e. not needing cellular

towers or Internet that may be damaged). And

finally, in the worst case, it may just be passing user-

friendly WAVE-WP commands and data by voice or

handwriting to other persons in direct contacts.

This hop assumes contacting as many

neighboring nodes and as simultaneously as possible.

To exclude duplications of actions on the same

request stemming from different neighbors, the

nodes will react only if the request comes to them

first time (additional parameter first in the hop).

In all the new neighbors reached by this parallel hop,

the full body of the loop, i.e.:

repeat( … )

will start again, with the terminal done branch

assessing casualties, and the hopping branch trying

to reach its own neighbors within the area,

prolonging the loop until there are neighbors visited

first. The terminal branches will leave casualty

numbers in all nodes reached in the area, which will

subsequently be summed up, returned, and finally

output to the USER.

On the internal implementation layer, invisible

for a user, this spatial repetitive parallel program

forms a runtime spanning tree covering (if

communications permit) the whole disaster area via

ICINCO 2006 - INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION

the embedded and reached wave interpreters in it,

with the discovered local casualty numbers

suspended in all the tree nodes. These numbers are

subsequently collected and summed up in parallel

when echoing from the fringe nodes and up the tree,

finally receiving the total number of casualties at the

root node. As can be seen, the whole disaster area

has been effectively converted into a runtime

parallel spatial (here tree-structured) machine,

capable of solving the problem in a fully distributed

manner and without any central computational

resources, as shown in Fig. 7.

Waves

Merging

results

Start

Responding

nodes

120

108

204

128

332

Returning

results

Figure 7: Spatial counting of the total number of casualties.

5.2 Delivery to an Affected Region

If to use echo rule max instead of sum of the

previous program, and also lift physical coordinates

of the navigated regions, it is possible to get the final

result on the disaster area as an aggregated

maximum casualties-location value, as follows:

frontal(Domain); nodal(Max);

Domain = <disaster area>;

Max =

max(

hop(direct, Domain, random);

repeat(

done(apply(casualties)_WHERE),

hop(anylinks, Domain, first)))

The first part of the result in nodal variable Max at

the entry node will give the number of casualties of

the most affected region, and the second part will

provide physical coordinates of this region. The

latter -- as measured from physical position of the

related WI by using a special environmental variable

WHERE associated, say, with GPS devices.

The underscore here represents an aggregation

act, with the first part of the compound values

obtained in all regions behaving as keys for the

spatial rule max (operating in parallel on the runtime

spanning tree of the whole area). The second part

serves just as an attachment to this key.

Using the obtained value in Max, it is easy to

describe in WAVE-WP an assemblage of the needed

number of relief packages for the most affected

region (as objects “relief”, with physical matter

in the language identified by double quotes). These

objects can be multiplied on the number of

casualties (as the first part in Max, using the colon as

an indexing act), with assignment of the physical

result to frontal variable Supply, as follows.

frontal(Supply);

Supply = “relief” * Max:1;

hop(direct, Max:2);

apply(distribute, Supply)

The rest of the program provides direct movement

into a physical location identified by the second part

in Max, and distribution, upon reaching the

destination, of the relief packages between

individuals that may need them, using external

(manned, or robotic) procedure distribute.

5.3 The Delivery to All Regions

It is easy to modify the previous two programs in

order to find casualty numbers separately on all

affected regions, with corresponding coordinates of

these regions, and then pack the needed amount of

goods for every region and forward all these to the

proper destinations, with a subsequent distribution.

The collection of casualty numbers on all regions

of the disaster area will be as follows:

frontal(Domain); Nodal(All);

Domain = <disaster area>;

All =

collect(

hop(direct, Domain, random);

repeat(

done(apply(casualties)_WHERE),

hop(anylinks, Domain, first)))

After the spatial work of this program, in a nodal

variable All at the entry node will be the list of

aggregated two-point values on all regions reached

in the parallel distributed loop. The following

program splits the list on its aggregated scalar values

to be used in parallel by the rest of the program.

DISTRIBUTED EMERGENCY MANAGEMENT WITH SPATIAL SCENARIOS

frontal(Supply);

split(All);

Supply = “relief” * VALUE:1;

hop(direct, VALUE:2);

apply(distribute, Supply)

After splitting, the rest of the program will replicate

on the implementation layer into identical branches

with different starting open values (the latter

accessed by an environmental variable VALUE

individual for each branch). Each branch prepares its

own physical collection of relief packages for the

corresponding region (using first part of VALUE),

which will be delivered by individual coordinates for

this branch & region (second part of VALUE).

The above two programs can be effectively

integrated into a single spatial program, as follows:

frontal(Domain, Supply);

Domain = <disaster area>;

split(

collect(

hop(direct, Domain, random);

repeat(

done(apply(casualties)_WHERE),

hop(anylinks, Domain, first)

)));

Supply = “relief” * VALUE:1;

hop(direct, VALUE:2);

apply(distribute, Supply)

The needed number of packages will be

delivered to the related destinations via routes

available, as shown in Fig. 8.

Start

Figure 8: Delivery of the goods to affected regions.

This may take into account the remaining usable

road infrastructures, also peculiarities of the terrain.

This delivery may be performed by manned vehicles

or convoys, or by advanced unmanned mobile

ground systems like those described in (Joint

robotics, 2005). Any concrete delivery, including

path finding and avoidance of obstacles, can be

effectively represented in WAVE-WP, with related

examples discussed and programmed in (Sapaty,

1999, 2005).

6 MORE MANAGEMENT ISSUES

In a similar way, it is easy to describe and execute

much more complex spatial scenarios of both

external supervision and self-organization of

affected regions. These may include massive

evacuation, forming new, emergency infrastructures,

fighting malicious post-disaster inclusions and

groupings (linked with terrorism and looting, for

example), movement and spreading of external relief

teams cooperating with each other and with the self-

organizing disaster area, and so on. The following

are some details on other important EM-related

problems, which are currently being investigated

with the use of WAVE-WP.

6.1 Distributed Data Mining

The currently performed data mining for a search of

suspected individuals is often restricted, mostly in

localized databases, as can be understood from

(Markoff, 2006). But very different and mutually

complementary information about, say, a suspected

criminal can simultaneously be present in many

databases throughout the globe, and she may have

many (stable, as well as casual) links with other

persons – also scattered in different databases.

The persons of interest and their groups may be

on a constant move, leaving dynamically

(temporary) records in different databases (say, in

airports by registering their tickets, also by video

cameras installed at the departures and arrivals).

Links between these persons -- from direct, voice, to

electronic via Internet or mobile phones -- may vary

rapidly during runtime. The WAVE-WP technology

provides for an effective finding and tracing of

single and multiple persons/objects, discovery of any

imaginable (and so far even unimaginable) patterns

of possible relations between them (which may be

fuzzy, dynamic, and situation dependent) throughout

the whole world in a highly automated, including

fully automatic mode, often ahead of time. The

model does not need any central databases for this,

using in parallel many computers with databases

directly where they are located, without copying the

information and its subsequent collection for central

processing (such a collection can make dynamic

ICINCO 2006 - INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION

information useless, actually dead).

The technology just treats the whole world with

all its available databases as a parallel

supercomputer/global knowledge base, and spatial

programs for it can be injected from any point,

covering the distributed virtual world (or its parts

needed) at runtime and in parallel. No other existing

approaches can compete with this so far.

6.2 Tracing Uninhabited Containers

The cargo containers traveling throughout the world

may pose a serious threat due to the potential

possibility of spreading unregistered hazardous

objects and materials (Our porous port protections,

2006). Their great numbers, movement on large

distances by different kinds of transportation means,

and between and through different countries, make

their supervision a serious problem for any existing

systems and technologies.

With the technology described in this paper we

can dynamically (and if needed, secretly) attach an

individual mobile intelligence to each container and

trace its movement worldwide, in parallel with

millions of other such intelligences. This can also

guarantee their regular remote reporting on the cargo

states and direct interaction with other such

intelligences, if needed. These multiple tracking

intelligences can effectively cooperate with other

important EM systems, for example, those providing

worldwide search for suspected individuals and

organizations, as in the previous section.

All this can be organized in WAVE-WP fully

automatically, without human involvement, by

“infecting” the world with a powerful supervisory

“supervirus”, massively penetrating into any

infrastructures and services, while preserving its

own global integrity and goal orientation.

6.3 Memetics

Memetics, which proclaims stable self-reproducing

and propagating information structures of higher

levels, or memes, analogous to genes in biology, has

so far been considered by many as a doubtful and

controversial discipline (Finkelstein, 2006). But it

can contain, in principle, high philosophical

potentials for explaining and solving complex

problems in human societies, which may help, for

example, understand and fight terrorism globally --

if this materializes into practical methodologies,

technologies, and tools. We can assume that memes,

from the engineering point of view, are distributed,

evolving and dynamic spatial structures, or patterns,

not observable from local points as a whole, and

therefore so hardly comprehendible by single human

brains. Using WAVE-WP approach, we can

automatically discover, study, and comprehend

spatial memes spatially, much superior to a localized

human brain. Moreover, the technology can apply

spatial memes spatially too, in parallel, effectively

impacting societies as a whole.

We can imagine a large distributed system, say, a

country or an army. A meme for us may be a

persistent complex pattern with hidden self-

replicating and self-evolving algorithm deeply

integrated with its structure (i.e. forming an active

spatial pattern). In WAVE-WP, we can describe any

such pattern in a highly dense, recursive form. We

can then apply this pattern to the same or any other

system, starting form any point, in a parallel

matching & covering mode. We can modify the

whole system to fit this pattern, or change the

existing patterns in it to fit the one we have just

injected. We can also implant into any system some

higher-level patterns (or "meta-memes") that can

discover the existing spatial patterns (memes) in it,

copy them spatially, wrap in the WAVE-WP

recursive syntax, transfer to other parts of the system

or to other systems, and unwrap there, with runtime

covering and updating these systems or their parts as

needed. Many related programs have been written in

WAVE, efficiently working in a distributed mode

via the Internet (Sapaty, 2006).

The memes, whether they really exist or not as

physical or virtual entities, may in any case inspire

us for a search of higher-level mechanisms and

abstractions in human societies in order to influence

them properly, with application in emergency

management and terrorism fight too, and especially.

7 CONCLUSIONS

A dynamic and ubiquitous approach for emergency

management has been proposed, based on the

distributed processing and control technology

WAVE-WP. Operating in a different space-time

continuum than the existing systems or forces that

can harm them, it can set up any needed control over

the distributed worlds. The compactness and

simplicity of relief scenarios in the WAVE-WP

language can allow us to program them on the fly,

reacting timely on rapidly changing situations. The

technology can effectively convert scattered human

and technical resources into operable distributed

systems, autonomously solving complex self-

survivability and self-recovery problems. The

DISTRIBUTED EMERGENCY MANAGEMENT WITH SPATIAL SCENARIOS

implementation of the technology can be easily done

on any existing software or hardware platform, and

the corresponding “social” module, as a software or

hardware wave language interpreter, can be readily

installed in many wearable devices, and first of all

mobile phones and handheld and laptop PCs.

As WAVE-WP technology allows us to set up

the formal description of what was considered

predominantly human activity before, the relief

scenarios can be effectively performed by any

combination of multi-agent (Sapaty, Filipe, 2005)

manned and unmanned units. With this approach,

humans and robots will not only perform complex

relief operations together, but will also share

responsibility for key decisions in different space-

time locations. Massive use of advanced mobile

robotics in the future relief missions, and its

integration with manned components under the

unified command and control, can be drastically

simplified by this flexible control model too.

In this paper, only the spatial WAVE-WP

automaton and examples of programming in it with

relation to emergency management problems have

been briefly described. Of course, the EM managers

will be relieved from most of this internal relief

mission programming “kitchen”, as there will be

user-friendly interactive facilities with graphics,

video, and audio interfaces. But the technology users

should also be taught how to think and act like

generals rather than privates on the disaster

“battlefields”, in order to reduce the necessity of

keeping special qualified system programmers, and

quickly react in the emergency situations themselves.

REFERENCES

3G industry optimistic for 2006, 2005. BBC NEWS,

Technology, 25 November, http://news.bbc.co.uk/.

Bullock, J. A., Haddow, G. D., 2004. The future of

emergency management. Journal of Emergency

Management, Volume 2, Number 1, pages 19-24.

http://www.pnpco.com/.

Finkelstein, R., (Compiler & Editor), 2006. A Memetics

Compendium: Vol. 1, 2. In Workshop on Memetics.

Executive Conference Center of Strategic Analysis

Inc., Arlington, Virginia.

GPS mobile phone, 2006.

http://www.easydevices.co.uk/pcp/Mobile_Phone.html.

Joint robotics program, master plan FY 2005, 2005. US

Department of Defense.

http://www.jointrobotics.com/activities_new/masterpla

n.shtml.

LaFraniere, S., 2005. Cellphones catapult rural Africa to

21st century. The New York Times, August 25.

www.NYTimes.com.

Markoff, J., 2006. Taking spying to higher level, agencies

look for more ways to mine data, The New yor Times,

February 25. www.nytimes.com.

Mobiles head for sales milestone, 2005. BBC NEWS,

Technology, 19 July. http://news.bbc.co.uk/.

National Infrastructure Protection Plan, Draft, 2005. US

Department of Homeland Security, Office of the

Assistant Secretary for Infrastructure Protection, 161p.

www.dhs.gov.

National Response Plan, 2004. US Department of

Homeland Security, 95p.

http://www.dhs.gov/interweb/assetlibrary/NRPbasepla

n.pdf.

Nunn, S., 2005. Preventing the next terrorist attack: the

theory and practice of homeland security information

systems. Journal of Homeland Security and

Emergency Management, ISSN 1547-7355, Vol. 2, Iss.

3. http://www.bepress.com/jhsem/.

Our porous port protections, 2006. The New York Times,

Editorial, March 10. www.nytimes.com.

Samsung i730, 2005.

http://www.vzwshop.com/samsungi730info/.

Sapaty, P. S., 1999. Mobile Processing in Distributed and

Open Environments, John Wiley & Sons, ISBN:

0471195723. New York, 436 p.

Sapaty, P., Sugisaka, M., Mirenkov, N., Osano, M.,

Finkelstein, R., 2005. Grasping the distributed entirety.

In AROB 10

. The Tenth International Symposium on

Artificial Life and Robotics. Beppu, Japan.

Sapaty, P. S., 2005. Ruling Distributed Dynamic Worlds,

John Wiley & Sons, ISBN 0-471-65575-9. New York,

256p.

Sapaty, P., Filipe, J., (Eds.), 2005. Multi-agent robotic

systems. Proceedings of the 1

International

Workshop on Multi-Agent Robotic Systems MARS

2005. Barcelona, Spain, September 2005, INSTICC

PRESS, ISBN: 972-8865-34-1, 200p.

Sapaty, P., Sugisaka, M., Finkelstein, R., Delgado-Frias, J.,

Mirenkov, N., 2006. Emergent societies: an advanced

IT support of crisis relief missions. In AROB 11

. The

Eleventh International Symposium on Artificial Life

and Robotics, Beppu, Japan.

Sub-$100 Laptop Design Unveiled, BC NEWS,

Technology, 29 September 2005,

http://news.bbc.co.uk/.

Wave system public domain, 2003.

http://www.ece.ubc.ca/~sergiog/wavefiles/.

ICINCO 2006 - INTELLIGENT CONTROL SYSTEMS AND OPTIMIZATION