7/25/2019 Katt t Ttttt

1/7

ABSTRACT 1

In old times, castles were surrounded by moats (deep trenches flled with water, andeven alliators! to thwart or discourae intrusion attempts" #ne can now replace

such barriers with stealthy and wireless sensors" In this paper, we develop

theoretical $oundations $or layin barriers o$ wireless sensors" %e defne the notion

o$ &barrier coverae o$ a belt reion usin wireless sensors" %e propose e'cient

alorithms usin which one can uic)ly determine, a$ter deployin the sensors,

whether a reion is &barrier covered" *e+t, we establish the optimal deployment

pattern to achieve &barrier coverae when deployin sensors deterministically"

inally, we consider barrier coverae with hih probability when sensors are

deployed randomly" %e introduce two notions o$ probabilistic barrier coverae in a

belt reion - wea) and stron barrier coverae" %hile wea) barrier&coverae withhih probability uarantees the detection o$ intruders as they cross a barrier o$

stealthy sensors, a sensor networ) providin stron barriercoverae with hih

probability (at the e+pense o$ more sensors! uarantees the detection o$ all

intruders crossin a barrier o$ sensors, even when the sensors are not stealthy" Both

types o$ barrier coverae reuire sinifcantly less number o$ sensors than $ull&

coverae, where every point in the reion needs to be covered" %e derive critical

conditions $or wea) & barrier coverae, usin which one can compute the minimum

number o$ sensors needed to provide wea) &barrier coverae with hih probability

in a iven belt reion" .erivin critical conditions $or stron &barrier coverae $or a

belt reion is still an open problem"

Abstract /

Wireless sensor networks (WSN) have thus far been used for detection and tracking of

static and mobile targets for mission critical surveillance applications. However, detection

and tracking do not suffice for a complete and accurate target classification. In fact,

surveillance target imaging ields the most valuable information. !urrent techni"ues mainl

aim to provide images of static environment in a sensor network. Nevertheless, imaging of

mobile targets re"uires networked and collaborative detection, tracking and imaging

capabilities. With this regard, ultra#wideband ($W%) radar technolog stands as a promising

approach for networked target imaging due to its uni"ue features such as having no line#of#

sight (&oS) re"uirement. However, $W% wireless radar sensor network (W'SN) is et to be

developed for imaging of mobile targets. In this paper, an architecture and a new

collaborative mobile target imaging (!I) algorithm for W'SN are presented. he

ob*ective is to efficientl obtain an accurate image of mobile targets based on the

collaborative effort of deploed radar sensor nodes. !I enables detection, tracking and

imaging of mobile targets as a complete W'SN solution. +erformance evaluations reveal

%ater0"htm

7/25/2019 Katt t Ttttt

2/7

that !I ields high "ualit radar image of mobile targets inW'SN with ver low

communication overhead regardless of the target shape and velocit.

Abstract0

2nery&e'ciency in taret trac)in applications has been e+tensively studied in the

literature o$ %ireless Sensor *etwor)s (%S*!" 3owever, there is little wor) which

has been done to survey and summari4e this e5ort" In this paper, we address the

lac) o$ these studies by ivin an up&to&date Stateo$&the&Art o$ the most important

enery&e'cient taret trac)in schemes" %e propose a novel classifcation o$

schemes that are based on the interaction between the communication subsystem

and the sensin subsystem on a sinle sensor node" %e are interested in

collaborative taret trac)in instead o$ sinlenode trac)in" In $act, %S*s are o$ten

o$ a dense nature, and redundant data that can be received $rom multiple sensors

help at improvin trac)in accuracy and reducin enery consumption by usinlimited sensin and communication ranes" %e show that enery&e'ciency in a

collaborative %S*&based taret trac)in scheme can be achieved via two classes o$

methods6 sensin&related methods and communication&related methods" %e

illustrate both o$ them with several e+amples" %e show also that these two classes

can be related to each other via a prediction alorithm to optimi4e communication

and sensin operations" By sel$&orani4in the %S* in trees and7or clusters, and

selectin $or activation the most appropriate nodes that handle the trac)in tas),

the trac)in alorithm can reduce the enery consumption at the communication

and the sensin layers" Thereby, networ) parameters (samplin rate, wa)eup

period, cluster si4e, tree depth, etc"! are adapted to the dynamic o$ the taret

(position, velocity, direction, etc"!" In addition to this eneral classifcation, we

discuss also a special classifcation o$ some protocols that put specifc assumptions

on the taret nature and7or use a 8non&standard9 hardware to do sensin" At the

end, we conduct a theoretic comparison between all these schemes in terms o$

ob:ectives and mechanisms" inally, we ive some recommendations that help at

desinin a %S*&based enery e'cient taret trac)in scheme"

ABSTRACT6;

Intellient transportation systems are revolutioni4in the way in which road sa$etyis monitored worldwide" These systems have evolved $rom the s with the

interation o$ new technoloies and the desin o$ more e'cient detection systems

$or tra'c violations" At present, throuh these systems, it is possible to predict the

most danerous places on the road and store a set o$ data to support decision&

ma)in reardin sa$ety and road maintenance" In this paper, the current situation

in the development o$ intellient transportation systems worldwide and the tra'c

%ater0"htm

7/25/2019 Katt t Ttttt

3/7

situation o$ 2cuador is e+amined" The main ob:ective o$ the research is to suest a

re$erence architecture $or the development o$ an intellient transportation system

that meets the needs o$ 2cuador"

bstract-

ABSTRACT 2nery in sensor networ)s is a distributed, non&trans$erable resource"

#ver time, di5erences in enery availability are li)ely to arise" ?rotocols li)e routin

trees may concentrate enery usae at certain nodes" .i5erences in enery

harvestin arisin $rom environmental variations, such as i$ one node is in the sun

and another is in the shade, can produce variations in charin rates and battery

levels" Because many sensor networ) applications reuire nodes to collaborate to

ensure complete sensor coverae or route data to the networ)>s ede a small set

o$ nodes whose continued operation is threatened by low batteries can have a

disproportionate impact on the fdelity provided by the networ) as a whole" In the

most e+treme case, the loss o$ a sinle sin) node may render the remainder o$ the

networ) unreachable" %hile previous research has addressed reducin the eneryusae o$ individual nodes, the challene o$ collaborative enery manaement has

been larely inored" %e present Interated .istributed 2nery Awareness (I.2A!, a

sensor networ) service enablin e5ective networ)&wide enery decision ma)in"

I.2A interates into the sensor networ) application by providin an A?I allowin

components to evaluate their impact on other nodes" I.2A distributes in$ormation

about each node>s load rate, charin rate, and battery level to other nodes whose

decisions a5ect it" inally, I.2A enables awareness o$ the connection between the

behavior o$ each node and the application>s enery oals, uidin the networ)

toward states that improve per$ormance" This paper describes the I.2A architecture

and demonstrates its use throuh three case studies" @sin both simulation and

testbed e+periments, we evaluate each I.2A application by comparin it to simpler

approaches that do not interate distributed enery awareness" %e show that usin

I.2A can sinifcantly improve per$ormance compared with solutions operatin with

purely local in$ormation"

Abstract

+S (lobal +ositioning Sstem) is increasingl being used for a wide range of applications. It

provides reliable positioning, navigation, and timing services to worldwide users on a continuousbasis in all weather, da and night, anwhere on or near the /arth. +S is made up of three

segments0 Space, !ontrol and $ser. +S has become a widel used aid to navigation

worldwide, and a useful tool for map#making, land surveing, commerce, scientific uses,

tracking and surveillance, and hobbies such as geocaching and wa marking. None of the

present +S sstems satisf the re"uirements for the safet of civilian navigation in the sea as

the maritime boundar of a countr cannotbe marked. his paper deals on the versatilit and the

%ater0"htm

7/25/2019 Katt t Ttttt

4/7

usefulness of a +S device in the sea. he main ob*ective of the paper is to help the fishermen

not to navigate beond other countr1s border. If a fisherman navigates beond the countr1s

border, an alarm is generated indicating that the fisherman has crossed the border. dditionall,

a S transmitter interface will send a message to base station located on the shore indicating

that a vessel has crossed the border. hus guards in the shore can assist and provide additional

help to those fishermen if needed. 2eeping in mind about lives of Indian fishermen, this devicehas been created to help them not to move beond Indian. 3n the whole, it is an attempt to

build a suitable device for the fishermen at a reasonabl low cost.

WaTer:

he principle of level measurement is taken from the direct dependence of hydrostatic pressure (p) on

theheight of the water column (h). Where the constants of proportionality are the density () and the

gravitation acceleration (g)..

p=h.p.g

The method is resistant to the formation of foam onthe level surface & is directly dependent on the density

(specific gravity) of the liquid. When the liquid density is changing it is necessary to make an additional

correction of the output.

Level sensors

detect the levelof li"uids and other fluidsand fluidi4ed solids, includingslurries,granularmaterials,

andpowdersthat e5hibit an upper free surface. Substances that flow become

essentiall hori4ontalin their containers (or other phsical boundaries) because ofgravitwhereas

most bulk solids pile at an angle of repose to a peak. he substance to be measured can be inside a

container or can be in its natural form (e.g., a river or a lake). he level measurement can be either

continuous or point values. !ontinuous level sensors measure level within a specified range and

determine the e5act amount of substance in a certain place, while point#level sensors onl indicate

whether the substance is above or below the sensing point. enerall the latter detect levels that are

e5cessivel high or low.

here are man phsical and application variables that affect the selection of the optimal level

monitoring method for industrial and commercial processes. he selection criteria include the

%ater0"htm

https://en.wikipedia.org/wiki/Sensorshttps://en.wikipedia.org/wiki/Liquid_levelhttps://en.wikipedia.org/wiki/Fluidshttps://en.wikipedia.org/wiki/Slurryhttps://en.wikipedia.org/wiki/Slurryhttps://en.wikipedia.org/wiki/Slurryhttps://en.wikipedia.org/wiki/Granularhttps://en.wikipedia.org/wiki/Wiktionaryhttps://en.wikipedia.org/wiki/Wiktionaryhttps://en.wikipedia.org/wiki/Wiktionaryhttps://en.wikipedia.org/wiki/Free_surfacehttps://en.wikipedia.org/wiki/Horizontal_planehttps://en.wikipedia.org/wiki/Gravityhttps://en.wikipedia.org/wiki/Gravityhttps://en.wikipedia.org/wiki/Gravityhttps://en.wikipedia.org/wiki/Liquid_levelhttps://en.wikipedia.org/wiki/Fluidshttps://en.wikipedia.org/wiki/Slurryhttps://en.wikipedia.org/wiki/Granularhttps://en.wikipedia.org/wiki/Wiktionaryhttps://en.wikipedia.org/wiki/Free_surfacehttps://en.wikipedia.org/wiki/Horizontal_planehttps://en.wikipedia.org/wiki/Gravityhttps://en.wikipedia.org/wiki/Sensors

7/25/2019 Katt t Ttttt

5/7

phsical0 phase(li"uid, solid or slurr), temperature,pressureorvacuum,chemistr, dielectric

constantof medium,densit(specific gravit) of medium, agitation (action), acoustical or

electricalnoise, vibration, mechanical shock,tank or bin si4e and shape. lso important are the

application constraints0 price, accurac, appearance, response rate, ease

of calibrationor programming, phsical si4e and mounting of the instrument, monitoring or control ofcontinuous or discrete (point) levels. In short, level sensors are one of the ver important sensors

and pla ver important role in variet of consumer6 industrial applications. s with other tpe of

sensors, level sensors are available or can be designed using variet of sensing principles. Selection

of an appropriate tpe of sensor suiting to the application re"uirement is ver important.

%ater0"htm

https://en.wikipedia.org/wiki/Phase_(matter)https://en.wikipedia.org/wiki/Phase_(matter)https://en.wikipedia.org/wiki/Temperaturehttps://en.wikipedia.org/wiki/Pressurehttps://en.wikipedia.org/wiki/Pressurehttps://en.wikipedia.org/wiki/Pressurehttps://en.wikipedia.org/wiki/Vacuumhttps://en.wikipedia.org/wiki/Vacuumhttps://en.wikipedia.org/wiki/Vacuumhttps://en.wikipedia.org/wiki/Chemistryhttps://en.wikipedia.org/wiki/Dielectric_constanthttps://en.wikipedia.org/wiki/Dielectric_constanthttps://en.wikipedia.org/wiki/Transmission_mediumhttps://en.wikipedia.org/wiki/Densityhttps://en.wikipedia.org/wiki/Densityhttps://en.wikipedia.org/wiki/Agitation_(action)https://en.wikipedia.org/wiki/Noisehttps://en.wikipedia.org/wiki/Noisehttps://en.wikipedia.org/wiki/Vibrationhttps://en.wikipedia.org/wiki/Shock_(mechanics)https://en.wikipedia.org/wiki/Shock_(mechanics)https://en.wikipedia.org/wiki/Calibrationhttps://en.wikipedia.org/wiki/Mathematical_programminghttps://en.wikipedia.org/wiki/Phase_(matter)https://en.wikipedia.org/wiki/Temperaturehttps://en.wikipedia.org/wiki/Pressurehttps://en.wikipedia.org/wiki/Vacuumhttps://en.wikipedia.org/wiki/Chemistryhttps://en.wikipedia.org/wiki/Dielectric_constanthttps://en.wikipedia.org/wiki/Dielectric_constanthttps://en.wikipedia.org/wiki/Transmission_mediumhttps://en.wikipedia.org/wiki/Densityhttps://en.wikipedia.org/wiki/Agitation_(action)https://en.wikipedia.org/wiki/Noisehttps://en.wikipedia.org/wiki/Vibrationhttps://en.wikipedia.org/wiki/Shock_(mechanics)https://en.wikipedia.org/wiki/Calibrationhttps://en.wikipedia.org/wiki/Mathematical_programming

7/25/2019 Katt t Ttttt

6/7

%ater0"htm

7/25/2019 Katt t Ttttt

7/7

%ater0"htm