binit kc proposal computer network wsn wildlife monitoring
TRANSCRIPT
KATHMANDU UNIVERSITY
SCHOOL OF ENGINEERING
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
PROPOSAL
ON
“DATA AGGREGATION IN WIRELESS SENSOR
NETWORKS USING ANT COLONY ALGORITHM
FOR ENERGY EFFICIENT WILDLIFE MONITORING”
Prepared By:-
Binit K.C. [M.Tech. (IT)]
2nd Semester
October, 2012
Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring
[2012]
ABSTRACT
Wildlife management has today become a very important topic in terms of protection and
preserving our wildlife system and overall balancing the ecosystem and preserving the core
of the nature. And being an important area of which requires a lot of work to be done, and has
become a priority for many countries and organizations around the world. One of the very
basic idea surrounding wildlife management and most importantly for endangered species is a
good understanding of a species’ behavior and habitat. With Nepal being a country with
various diverse ecosystem, Nepal do possess various rare and endangered animals and those
require constant monitoring so that their habitat can be learned to help them survive the harsh
and unpredictable environment.
With the advent of technological field, the way the management is done has seen a great deal
of changes and with the help of Wireless Sensor Network (WSN), wildlife management
system can be designed in such a way that there is minimum invading in their habitat so as to
protect their habitat from external interfering. Since a full-fledged WSN requires lot of nodes
to work as a wholesome network, and since the wildlife management process can be for
longer period there is requirement for energy efficient WSN so that the research process can
be carried out for longer period with full maximum utilization of the resources available.
Data aggregation is important in energy constraint wireless sensor networks which exploits
correlated sensing data and aggregates at the intermediate nodes to reduce the number of
messages exchanged network. An ant colony algorithm for data aggregation in wireless
sensor networks provides an opportunity for energy efficiency. Artificial simulated ants will
be used to simulate the real time activities that ant perform while searching for source of food
or the path using pheromone trail and during this process every ant will explore all possible
paths from the source node to the sink node. The data aggregation tree is constructed by the
accumulated pheromone resulting in finding the shortest path between their nest and the food
sources.
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INDEX
TABLE OF CONTENTS Page No.
Cover page i
Abstract ii
List of Tables iv
List of Figures v
Abbreviations and symbols vi
CHAPTER No. Title Page No.
1. INTRODUCTION 1-8
1.1 Background 11.2 Problem System 31.3 Objectives 31.4 Literature Review 41.5 Significance 61.6 Limitation 71.7 Organization of Study 7
2. METHODOLOGY 9-15
2.1 Universe of Study 92.2 Data Collection and Sampling 102.3 Testing and Simulation 12
3. CONCLUSION AND DISCUSSION 16-17
3.1 Conclusion 163.2 Discussion 173.3 Future Works 17
BIBLIOGRAPHY 18
Appendix
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LIST OF TABLES
S. No. Table No. Caption of the Table Page No.
1 Table 1 Wildlife monitoring in Protective Areas of Nepal 10
2 Table 2 Pert Chart 14
3 Table 3 Division of work 15
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LIST OF FIGURES
S. No. Figure Number Caption of the Figure Page No.
1 Figure 1 Ant Colony Optimization shortest path selection 12
sample
2 Figure 2 ACO algorithm 13
3 Figure 3 Work Division of the Project 15
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ABBREVIATIONS AND SYMBOLS
ACO Ant Colony Optimization
APU Anti Poaching Units
BNP Bardiya National Park
CNP Chitawan National Park
CO Colony Optimization
DNPWC Department of National Parks and Wildlife Conservation
EIA Environment Investigation Agency
GPS Global Positioning System
GPRS General Packet Radio Service
OS Operating System
VHF Very High Frequency
WSN Wireless Sensor Network
WWF World Wildlife Federation
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CHAPTER 1
1. INTRODUCTION
1.1) Background
Various project work have been done in co-ordination with the various organization
involved in the work and has been solely concentrated on upgrading the information
system currently available but not in an extended format. So to determine the behavior
and location of wild animals, they need to be monitored in some way. So to track the
animals the main idea is to use a WSN to track their movements and follow their
tracks and try to protect their natural habitat and also help researchers to take the data
collected and use the data to further help in their quest to provide a better protection to
the animals and the natural landscape and environment of the habitat present.
Considerable research studies have been carried out in protected areas of Nepal over
last three decades. Often, these studies are species oriented on selected endangered
mammals and do not deliver conservation actions potentially to serve management
needs. Comprehensive, multidisciplinary research approach and long term monitoring
is scant at present and is of little conservation significance. Research policies,
guidelines, prioritization and evaluation criteria are important facets for sound
protected area management. Persistent concerted efforts are needed to make research
and monitoring as an integral part of protected area management.
With various research being conducted still the available resources which have been
widely used in various monitoring activities in other countries have not been widely
adopted in regards to monitoring in Nepal and still lag a long way behind in terms of
research works being carried out. Use of Wireless Sensor Networks can be applied in
the field of wildlife monitoring with WSNs being composed of huge number of sensor
nodes which can monitor the environment by collecting, processing as well as
transmitting collected data to the remote sink node through direct or multihop
transmission.
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With motes being powered with GPRS, Bluetooth, GPS modules, sensor boards,
TinyOS and many more, there is a lot of possibilities which can be worked, with these
features of the motes which goes in long way to carrying out the monitoring activities.
The main concern regarding the sensor nodes is the fact that it is resource constrained
and that is where data aggregation using ant colony optimization comes in since the
tiny sensor nodes are powered by limited battery resources, energy efficiency is one
of the primary challenges to the successful application of WSNs. Usually energy is
consumed during three processes which are sensing, processing and communication
process.
In ACO (Ant colony optimization) a colony of artificial ants is used to construct
solutions guided by the pheromone trails and heuristic information. ACO was inspired
by the foraging behavior of real ants. This behavior enables ants to find shortest paths
between food sources and their nest. Initially, ants explore the area surrounding their
nest in a random manner. As soon as an ant finds a source of food, it evaluates
quantity and quality of the food and carries some of this food to the nest. During the
return trip, the ant deposits a pheromone trail on the ground. The quantity of
pheromone deposited, which may depend on the quantity and quality of the food, will
guide other ants to the food source. The indirect communication between the ants via
the pheromone trails allows them to find the shortest path between their nest and food
sources. This functionality of real ant colonies is exploited in artificial ant colonies in
order to solve Optimization problems. In ACO algorithms the pheromone trails are
simulated via a parameterized probabilistic model that is called the pheromone model.
The pheromone model consists of a set of model parameters whose values are called
the pheromone values. The basic ingredient of ACO algorithm is a constructive
heuristic that is used for probabilistically constructing solutions using the pheromone
values. In general, the ACO approach attempts to solve a CO problem by iterating the
following two steps:-
1. Solutions are constructed using a pheromone model, that is, a parameterized proba-
bility distribution over the solution space.
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2. The solutions that were constructed in earlier iterations are used to modify the
pheromone values in a way that is deemed to bias the search toward high quality so-
lutions.
1.2) Problem Statement
Natural habitats are vital for assuring sustainable development. Wild habitats are the
repositories of biological diversity (biodiversity) which are the raw material for
natural selection and adaptation. They provide myriad services that enrich and sustain
human life with both tangible and intangible economic and social value. Biodiversity
is especially important to South Asia which is home to 13 – 15% of the world's
biodiversity and hosts some of the most charismatic and endangered species on Earth.
Habitats across Bangladesh, Bhutan, India and Nepal are home to over 65% of the
3,000 or so remaining wild tigers and the Himalayas is the last redoubt of the
critically endangered snow leopard, whose numbers are unknown. India is classified
as a mega-diverse country and the Himalayas. In Nepal basically various hunting,
poaching and illegal trading of animals parts which are endangered are being
conducted under a racket making it difficult for activists and those involved in
protection a very hard time, so using the latest technology available a well deployed
system can be used to make it better for the habitat monitoring of such animals.
Poaching has become so intense that tigers have disappeared from many parks
throughout Asia. Nowhere has the impact been greater than in India and Nepal which
remain the bastions of tiger conservation. Nepal has emerged as the transit hub for the
trade in illegal wildlife commodities destined for consumption in East China which is
a very serious issue and have to be addressed very soon which can be done with the
help of the monitoring system that can be well devised to pertain to the needs of such
habitat in need of monitoring.
1.3) Objectives
The main objective of the research undertaken is to: -
To create an energy efficient wireless sensor network for wildlife monitoring
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To determine optimal in-network data aggregation points in sensor network
using ACO algorithm
To test the equipment and various application in co-ordination with the na-
tional park in small scale and then try a full-fledged project
Keep track of the animals’ travels that are under study and, with immediate
learning if they have fell prey to any mishaps naturally or artificially.
Develop a fully functional, highly mobile, energy efficient sensing system that
determines accurate positional data and can propagate it through the network.
To design an optimized system to incorporate as maximum elements as possi-
ble for the tracking and usability of the information system as a whole
1.4) Literature Review
Scientists have used a variety of methods to track animal species. Before the 1960s,
it was common practice to capture a small number of subjects, attach identifiers (i.e.,
tags or bands) to them, and release them back into the wild so that they could be
tracked. Eventually, the animals were recaptured, or their remains were found, and
the identifiers were retrieved. Generally speaking, this approach is cheap and can
provide baseline information about the observed wildlife; however, the recovery rate
is low and the accuracy is poor due to inevitable observation errors.
The first breakthrough in tracking technology occurred with the advent of radio
telemetry. A radio telemeter, which consists of a Very High Frequency (VHF)
transmitter, an antenna, and a power cell, is attached to the subject by a harness, a
collar, glue, subcutaneous prongs, or surgical implants. Signals emitted by VHF
transmitters are detected by using receivers with homing techniques or by applying
triangulation-based techniques. Although these approaches can collect much more
accurate information than previous methods, the radio telemeter system causes two
additional problems: 1) the maximal lifespan of the system is limited by the battery
capacity, which is also a common problem in the methods discussed below; and 2)
the tracking range is limited by the radio range, which makes wildlife tracking
extremely labor-intensive.
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Currently, the US/French Argos system is the only functional satellite telemeter
system, and it has been widely applied by many wildlife tracking projects. However,
to transmit signals to satellites, the Argos system consumes much more power than
radio telemeter based systems and thus has a shorter lifespan. Moreover, the
operating cost is quite high - about USD 500 per animal per month.
The Great Duck Island (GDI) project addressed the requirements for habitat
monitoring in general. It’s proposed the architecture for monitoring seabird nesting
environment and behavior. The deployed network consisted of 32 nodes on a small
island off the coast of Maine streaming useful live data onto the web. The application
driven design exercise served to identify important areas of further work in data
sampling, communications, network re-tasking, and health monitoring.
The Princeton’s ZebraNet Project is an inter‐disciplinary effort with thrusts in both
Biology and Computer Systems to track zebra behavior at Mpala Research Centre,
Kenya. ZebraNet team finally developed a fully functional, highly mobile, energy
efficient sensing system that determines accurate positional data and can propagate it
through the network. Several system level energy management techniques were
deployed to reduce energy consumption. The hardware utilized a solar array to
recharge the batteries. The system was first tested on January 12, 2004 where seven
zebras, six females and one male were collared. Position logs were generated for
these zebras. The area covered was around 36 square kms.
Jurdak et al. in their paper related to energy efficient localization for virtual fencing
have specified that addresses the tradeoff energy consumption and localization
performance in a mobile sensor network application. It focused on combining GPS
location with more energy-efficient location sensors to bound position estimate
uncertainty in order to prolong node lifetime. The focus was on an outdoor location
monitoring application for tracking cattle using smart collars and using empirically-
derived models to explore duty cycling strategies for maintaining position
uncertainty, within specified bounds.
Regarding the energy efficiency of the WSNs various works have been carried out in
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this field which includes Directed diffusion (DD) (Intanagonwiwat et al., 2003),
which is a typical data-centric routing paradigm for sensor networks. It consists of
four basic elements: interests, data messages, gradients, and reinforcements. In DD, a
task, which is a list of attribute-value pairs, is flooded into the whole network as an
interest for named data. A gradient is a direction state created in each node that
receives an interest. Events start flowing toward the originator of interest along the
established shortest path. Data from different sources are opportunistically
aggregated. However, opportunistic aggregation on a low-latency tree is not efficient
because data may not be aggregated on nodes near the sources. In-network data
aggregation is an important in energy constraint sensor network which exploits
correlated sensing data and aggregates at the intermediate nodes reducing the number
of messages exchanged network. In data gathering application large amount of
communication is reduced by in-network aggregation achieving maximum lifetime
of network.
Optimal aggregation tree problem is NP-hard (Al-Karaki et al., 2004) which is
equivalent to Steiner tree (Krishnamachari et al., 2002), weighted set cover
(Intanagonwiwat et al., 2002) problems. Many researchers have made efforts on data
aggregation in wireless sensor networks (Bhattacharjee and Das, 2007;
Intanagonwiwat et al., 2002; Krishnamachari et al., 2002; Li et al., 2006; Misra and
Mandal, 2006; Motegi et al., 2006).
In Li et al. (2006), their greedy algorithm constructs a multicast tree by iteratively
adding source nodes to the existing tree until all the source nodes and the sink node
are included. Initially, the tree includes only the sink node. Each time the algorithm
finds a source node among the remaining source nodes, which is closest to the
existing tree, it adds the shortest path between that source node and the existing tree
to the tree. This process continues until all the source nodes have been included in
the tree. In addition, in order to further reduce the computational complexity and
improve the quality of the output solution, they design another heuristic
approximation algorithm based on minimum spanning tree to construct the data
aggregation tree.
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Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring
[2012]
1.5) Significance
In Nepal, the poaching and illicit trade of wildlife, particularly Asian big cats, is a
major concern. In response, WWF is working with the Nepalese government to close
down trade routes and transit markets for illegal wildlife through improved
monitoring and enforcement. Each year, hundreds of millions of plants and animals
are caught or harvested from the wild and then sold as food, pets, ornamental plants,
tourist curios and medicine. While a great deal of this trade is legal and is not harming
wild populations, a worryingly large proportion is illegal and threatens the survival of
many endangered species. With the help of such monitoring system a fast measure can
be taken in terms of protecting the endangered species. With such technological
advent in recent times, the monitoring system can be moved on from the previously
uncanny monitoring system that prevailed in Nepal can be replaced with simple and
effective system for monitoring the wildlife and using energy efficient WSNs is a
major step towards achieving what has till now been a difficult process regarding the
wildlife monitoring.
1.6) Limitation
The main limitation associated with the study is the fact that the permission of the na-
tional park is the very core component that defines the entire project and the study it-
self that has been proposed. The other main limitation of the study which may influ-
ence the study during its progress is the technological aspect of the study, since the
study itself is being carried out in the wild there may be some interference regarding
the transmission of the signal and maybe need to be complied to its suitableness to the
environment of the national park where the study will be conducted .The battery that
will be used in the nodes will only have some specific lifetime and since it is that spe-
cific area which we are trying to concentrate on improving and hence the lifetime of
the device thus used will be directly in consideration with the study being conducted.
Secure access to the data must be maintained so as to avoid snooping and various
other activities which the poachers or other people may use to their advantage and in-
formation thus gathered but it will be a long way before that can be achieved and the
security part will have to be worked out from the beginning of the study being con-
ducted.
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1.7) Organization of Study
The introduction introduces briefly the various aspects of the research that will be
carried out and covers the problem that the research is going to address along with
relevant information about why this is an important problem along with background
information, and the purpose of the study. The methodology and further topic covers
around with the details of various sources of data and methods used to design the
project with theoretical definition regarding various aspects of the project.
The summary, conclusion part of the report discusses about the overall work to be
carried out the research and the testing carried out and also about the future work with
respect to the project.
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CHAPTER 2
2. METHODOLOGY
2.1) Universe of Study
International trade of wildlife species and products is estimated to be worth USD 20
billion (Chungyalpa 1998). Despite strict legislation ensuring a poacher/trader 15
years' imprisonment or a fine of up to USD 1,300 (or both), trade has continued to
flourish (Chungyalpa 1998). In 1991, WWF Nepal and the Department of National
Parks and Wildlife Conservation (DNPWC) sought to identify deterrents to tiger and
rhino poaching in the national parks. As a result, antipoaching units (APUs) were
formed in Chitawan National Park (CNP) and Bardiya National Park (BNP). Although
APUs were set up to reduce the level of poaching of tigers and rhinos, they quickly
also became involved in monitoring the trafficking network of wildlife species and
their products. Concerns have focused on the increasing trend of Nepal being used as
a transit route by well-coordinated and well-financed organized groups with
international links. The Environment Investigation Agency’s (EIA) recent report The
Tiger Skin Trail described Kathmandu as a ‘staging point’ for illegal skins brought in
from India to be sent to Tibet
Responding to the overwhelming concern of the global community and recent tiger
conservation issues in India, WWF and TRAFFIC met to strategize on the emerging
threats to endangered wildlife due to illegal trade and consumption. A 5-year action
plan was drawn up to address issues at various sites in the trade chain. Nepal has been
identified as a key player in the transit process. This proposal thus draws upon the
action plan as well as on the national level priorities that have been identified as part
of WWF Nepal’s experience of wildlife trade issues in Nepal.
Nepal is a signatory and party to CITES and had in place all legal and institutional
instruments to address wildlife trade issues. However, the illegal wildlife trade has
recently become more organized, demand has increased and the traders have a more
sophisticated system for transporting consignments. Therefore, it is now also
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necessary for Nepal to address external drivers, like international demand and
enforcement at cross-border levels, as well as regional level advocacy, policy analysis
and feedback, working with non-conventional stakeholders such as transport
companies.
There have also been various study regarding the protection of endangered and other
in danger in Nepal but most of them have been non-technological methods and have
been conducted with help of manual labor and below is the table showing various
work regarding the recent survey that has been overtaken:-
Species Year Place Methods Results Collaboration
Rhino 2008 Chitawan and
Bardiya NP
Total direct
count
430 DNPWC/CNP/BNP/
NA/WWF
Nepal/NTNC/ZSL/Darwin
Initiative
Gaur 2008 Parsa WR Total direct
count
37 DNPWC/PWR/NA/WWF
Nepal-TAL
Tiger 2008 Suklaphanta WR Photographic-
capture recapture
sampling method
7 DNPWC/WWF Nepal-
TAL/NTNC-SCP
Gharial 2008 Koshi,Narayani,Rap
ti,Babai,Karnali
rivers
Total direct
count
81 DNPWC/WWF Nepal
Swamp
Deer
2008 Suklaphanta WR Total direct
count
1674 SWR/WWF
Nepal-TAL/NTNC-SCP
Table 1: - Wildlife monitoring in Protective Areas of Nepal
2.2) Data Collection and Sampling
Since this is an exploratory and descriptive research and its methodology will consist
of various conceptual frameworks, study area, source of information, methods and
techniques. The study will be done in the Bardiya National Park area, Parsa wildlife
reserve and Chitwan National Park to achieve the objectives that has been undertaken
for the completion of the research .The reason behind the selection is because the
demand and need of information system is very high in wildlife conservation area
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with lots of large organization and with lots of individual working towards its
conservation and protection. So to cope with the current requirement and need in
terms of protection it is perfect for data collection and analysis, the areas that has been
selected for the purpose .A set of questionnaire and pre-testing the questionnaire and
field survey and various different methods and techniques of data analysis will be
used during the course of this study regarding the information about habitat and the
number of animals that will be under investigation. With due concern for the
economical completion of the research study, the design in such studies must be rigid
and not flexible and must focus attention on the following: -
1. Formulating the objective of the study
2. Designing the methods of data collection
3. Selecting the sample
4. Collecting the data
5. Processing and analyzing the data
6. Reporting the findings.
Primary Data / Secondary Data
The being an exploratory and descriptive type, various sources and techniques
will be used in gathering the information. Both primary and secondary data
relevant to the study will be collected and analyzed during the study.
Sources of Primary Data
The organizations who are currently involved with fulfilling their services of
providing the work related to wildlife conservation and related field will be the
major sources of the primary data. Similarly internal analysis of the
organization involved and their promotional scheme and data achieving and
striving for the ultimate goal of providing an uncharted information system
which may be able to change the face of the information system regarding
wildlife research. Also apart from these, the information obtained through
observation, discussion and key informant survey will also be given due
consideration.
Sources of Secondary Data
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The sources of secondary data will be the various articles, reports, journals,
books etc. published by various organization and institutes.
2.3) Testing and Simulation
The Ant-Aggregation algorithm will be simulated in MATLAB with a setting of sensor
network of around 50 nodes to support for a single environmental setting with respect
to the Bardiya National Park, Chitawan national park and Parsa Wildlife Reserve indi-
vidually for each setting. The neighborhood is obtained from the random topology. Set
of source nodes 20, 30&40 and a destination will be considered for generating optimal
aggregation tree using Ant-Aggregation. On varying the ACO parameters and weights
of aggregation, shortest distance and correlation, the optimal aggregation tree in sensor
network will be the target to be obtained.
Figure 1: - Ant Colony Optimization shortest path selection sample
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Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring
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Algorithm: Outline of ant colony optimization metaheuristicSet parameters, initialize pheromone trailsWhile termination criterion not satisfied doConstructAntSolutionApplyLocalSearch /*optional*/Update pheromonesEnd while
Figure (a): - Basic ACO Algorithm
Each ant located at node i hops to node j selected among the neighbors that have not yet been visited according to probability. Probability that ant k in node i will go to node j.α: relative importance of pheromone trialβ : relative importance of the distanceg : neighborhood of current node idij : node potential, gives estimate of early aggregation or shortest route to destina-tion.
Figure (b): - Mathematical algorithm model
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Initialize (Variable Phermone, Aggregate_count,source,destination)
Iterate 100 times or Converge to
optimal cost
Permute source and allocate randomly to each Ant For each ant iteratively constructive route by locally selecting
next hop based on probability P(i,j)
If K reached destination?
Select Next hop
Next K (ant)
Find out totalcost
Second Pass: Transverse from destination to source
Until reaches to all source
Find optimal aggregation points from optimal aggregation tree: apply labeling of nodes ants visited once are leaf(src) and aggregation
nodes having Aggregate_count>1
Yes
YesYes
No
No
Figure (c) :- Flowchart representation of ACO
Figure 2 :- ACO algorithm
Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring
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S. No. TasksEstimated time (Weeks)
1 Title selection and Synopsis 2
2 Literature review 4
3 Project rationale 2
4 Design investigation and identify resources available 2
5 Draft a preliminary design to carry out the research 3
6 Finalize target area of conducting experiment 2
7 Identify target group animal and carry out pilot study re-garding the monitoring
4
8 Analyze the data from simulation and real time collec-tion and review pilot study
4
9 Analyze data and produce equivalent analysis 4
10 Conclude and finalize Documentation 6
Table 2 :- Pert Chart
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Project Work Division
Project selection and con-firmation
Designing and overview of the Project
Review and implementa-tion of available similar projects
Coding and review of Codes
Identification of possible area of implementation and future works possible
Testing and Debugging
Documentation
Figure 3:- Work Division of the Project
TASKS STUDENTS
Binit Research
Assistant 1
Research
Assistant 2
Project selection and confirmation X
Designing and overview of the Project
X X X
Review of available similar projects X
Coding and review of Codes X X
Identification of possible area of im-plementation and future works possi-
bleX X
Testing and Debugging X X X
Documentation X X X
Table 3:- Division of work
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CHAPTER 3
3. CONCLUSION AND DISCUSSION
3.1) Conclusion
Use of WSN is proving to be a very powerful tool and critical to the successful
implementation of a project of this scope and complexity. WSN for wildlife
monitoring can provide the means to tracking and monitoring of the wildlife and
especially endangered as that one. WSNs with various sensor nodes and equipment
have provided necessary tools for surveys, navigation, and tracking. Technologies are
being utilized to produce status and monitoring data about the wildlife that were
invaluable in conducting the research that has been carried out and giving an
alternate for resource constrained resource regarding the use of WSNs in tracking
system and was very useful in the final outcome with the system thus proposed for
the power saving property of the prototype system being very useful in getting the
final result which was very effective in the situations and useful for wildlife
management using energy efficient WSNs using ACO.
Patrolling is a basic and the most important function of protected areas. In spite of
patrolling, research and monitoring has remained a low priority activity in most of
the protected areas. A simple monitoring process consists of recording wildlife en-
counters by the staff while on routine patrols, in a standardized format should be
practiced in protected areas. The data so collected over a period of time can provide
insights into the population dynamics and distribution of most species. But the need
today is now to incorporate the use of technological aspect such as WSNs to make it
more easy and efficient for tracking and monitoring purpose.
A review of the use WSNs for wildlife management has indicated that these systems
are predominantly used for analysis of habitat requirements and the prediction of
areas of suitable habitat, and typically consider only relatively short time scales.
These approaches to wildlife management can be applied in the case of Tiger and
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Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring
[2012]
One-horned Rhinos because the issues are ones of ongoing management of data in a
manner that preserves the complex relationships that exist between data items,
allowing them to be analyzed.
3.2) Discussion
The use of energy efficient WSNs will enable to track the position of the animals and
their habitat and in turn help in tracking their daily life activities and their position
with respect to the national park and the reserve and in turn help in nurturing them
and protecting them. Also with respect to information system that has been planned
to be designed, the data available from WSN will be used to display various
attributes to the various animals for eg :- the current position of the animal, their
current location regarding which part of the park they are in so that it can help in
panning out data and reference to helping towards better protection of endangered
animal can be done using GPS enabled motes available. The research and its use has
potential use in various field of the wildlife tracking and then using energy efficient
WSNs to represent in various applications in future with further addition of
components and can do a great deal of tracking and information system that will be
able to provide various information related to wildlife with various pictures, snaps
and the history, origin of the animals and various aspects that will be helpful in better
protection of endangered animals.
3.3) Future Works
In the future there will be more co-ordination and working with biologists and devote
our effort developing adjustable collars that can be remotely controlled and released.
Various plan such as to improve the installation of the WSN motes so that they’re
placed efficiently in the monitored animals’ necks while keeping the antenna on the
top. Moreover, there a plan to package the motes with various sensor into a smaller
case, and perform a large scale field experiment so as to cover a wider area of the
National Park and other sanctuary which can be helpful in long term for the
researches and those working on protecting the habitat of the endangered species of
the animals.
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[2012]
BIBLIOGRAPHY
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Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring
[2012]
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Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring [2012]
APPENDIX
Figure: - Gantt chart of “Data Aggregation In WSN Using Ant Colony Algorithm For Energy Efficient Wildlife Monitoring”
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Department of CSE, Kathmandu University, Kavre