Contents
2
TOPICS COVERED SLIDE NUMBER
 Introduction to Wireless Visual Sensor Network-WVSN 3
 The Layer Wise Description of WVSN 4
 Applications Of Wireless Visual Sensor Networks (WVSN) 5
 WVSN Vs WSN 6
 Sensing Model of Sensor’s 7
 Hardware Components of Visual Nodes in WVSN’s 8
 Major Design Issues of WVSN 9
 Coverage Problem in WVSN 10-11
 Coverage Enhancement Principle in WVSN 12
 Conclusion 13
 References 14
 Questions/Answers Session 15

Introduction to Wireless Visual Sensor Networks
Due to rapid advancement of sensor technology equipping sensors nodes with camera’s is
possible. In this way, sensor nodes can send the captured visual data to provide richer
sensing and monitoring information, which enables more applications in areas such as
wide-life observation and security surveillance. These kinds of camera-equipped sensor
networks are known as Wireless Visual Sensor Networks (WVSNs).The hardware
components of a WVSN consist of tiny camera sensor nodes, embedded processors and
wireless transceivers.
Reference Architecture for a Wireless Visual Sensor Networks
3

The Layer Wise Description of Wireless Visual Sensor Network (WVSN)
4

Applications Of Wireless Visual Sensor Networks
5
 Visual surveillance sensor networks.
 Storage of potentially relevant activities.
 Traffic avoidance, enforcement and control systems.
 Environmental monitoring.
 Person Locator Services.
Emerging Application of VSN

How WVSN differs from normal WSN ???
6
1)Limited sensing range
Sensing Range in WSN Sensing Range in VWSN’s
2)Network bandwidth consumption
3)Collision in transmitting data
4)Visual data processing
5)Coverage issue

Sensing Model of Sensor’s
For WVSN, the sensing region of the visual sensor nodes is directional which is different
from the traditional sensor( temperature , pressure, etc. ) nodes used in WSNs which are omni
directional in nature. Visual sensor nodes equipped with camera differ from traditional Omni-
Directional sensor nodes because of the presence of unique characteristics such as Angle of
View(@), Working Direction(Wd),Line of Sight (LoS) and Field of View (FoV) properties.
Visual sensor node can capture objects within FoV region only whereas in traditional WSNs,
the node collect the scalar information of different phenomenon around them from the area
determined by its sensing range in Circular Disk like manner as shown in figure below.
7
Omni Directional Sensing Directional Sensing Directional(Camera,infrared,etc.)Sensor Properties

Hardware Components of Visual Nodes in WVSN’s
There are two types of WVSN platform. The first one is the low end WVSN platform
that is designed specifically for energy efficiency (e.g., Cyclops ). The other is the high
end WVSN platform (e.g., Meerkats ) that is designed for sophisticated visual data
applications where the system resource requirement and energy consumption are about
one order of magnitude higher.
Table: Hardware components in WVSN platforms
8

Major Design Issues of Wireless Visual Sensor Network
 Coverage
Most of the visual sensor applications aim at maximum coverage with minimum number of
visual sensors to improve lifetime simultaneously.
 Connectivity
Connectivity is part of the coverage problem. It ensures that there is at least one communication
path between any pair of active sensors to ensure barrier coverage.
 Network lifetime
Due to the limited capacity of existing batteries, visual sensor nodes do not last as long as desired.
 Network traffic:
The more messages are delivered, the more energy is consumed. Therefore, a sensor network should
minimize its message traffic
 Constraints associated with Visual Sensor Node
 Limited angle of view.
 Single working direction out of multiple working direction is active during sensing.
 Line of sight plays a key role.
 Fixed sensing radius.
 Motility allows adjustment of working direction.
 Mobility of nodes removes coverage holes.
9

Coverage problem is the basic problem of any type of sensor network, and is the evaluation
criteria of measuring sensor network quality of service (QoS). The core problem of visual sensor
network coverage is “how strong is the sensor network monitoring ability of observation in
physical space?" The coverage problem is centered on a fundamental question: “How well do the
sensors observe the physical space ? ”.
There are following types of coverage problem encountered during deployment phase:
1. Target-based coverage solutions
2. Area-based coverage solutions
3. Coverage solutions with guaranteed connectivity
4. Network lifetime prolonging solutions
10
Coverage Problem in WVSN

Coverage Problem in WVSN (Cont…)
Figure 4.1a presents a simple graphical 2D representation of a typical camera’s field of view. The viewing
angle is “2α” and “r” is the sensing radius. The orientation of the cameras’ field of view(FoV) is a key
parameter for network coverage. Figure 4.1b shows a configuration where seven sensors are employed to
cover eight targets. Changing the cameras’ orientation or performing motility also change their coverage
area, as depicted in Figure 4.1 c. The same eight targets are now covered by only four sensors, reducing the
cost of the deployed network and allowing the using of redundant nodes to prolong network lifetime. Note
that only the cameras’ orientations were changed, not their positions.
Figure 4.1 Target Coverage Problem in Visual Sensor Node
Figure 4.1a Figure 4.1a Figure 4.1a
11

Coverage Enhancement Principle in WVSN
Directional or Visual sensor networks can be deployed in two distinct ways:-
1. Controlled or Predefined Deployment
2. Random Deployment
In directional or visual sensor networks, the following five main principles can
be used for attaining high coverage rates in random deployment of visual nodes.
1. Deployment of excessive number of directional sensors.
2. Exploiting the motility of directional sensors.
3. Exploiting the mobility of directional sensor nodes.
4. Redeployment.
5. Hybrid solution (combination of motility and mobility).
12

Conclusion
Wireless visual sensor networks are a valuable resource for many
surveillance, tracking and general-purpose monitoring applications. Camera-
enabled sensors will retrieve visual information that can be exploited for public
security, military surveillance, industrial automation, weather monitoring,
rescue operations, traffic management uses, among many others. In this way,
sensor nodes can send the captured visual data to provide richer sensing and
monitoring information .For some of those applications, however, there will be
some criticality in the performed monitoring, requiring high coverage rate
throughout the network lifetime.
Coverage is highly relevant for modern wireless visual sensor networks,
but it has not been properly investigated. The coverage concepts for wireless
sensor networks (WSN )are not suitable for wireless visual sensor networks
(WVSN), since visual sensors collect visual information following a directional
sensing model and source nodes may have different field of view ( FoV ). Thus
it can be concluded that coverage should be a central design issue of visual
monitoring applications, especially in critical monitoring scenarios.
13

References
14
[1] Stanislava Soro and Wendi Heinzelman,”A Survey of Visual Sensor Networks” Advances in Multimedia Volume
(2009),Pg.1-21.
[2] I.F.Akyildiz ,T. Melodia, K.R.Chowdhury,“Wireless multimedia sensor networks: applic -ations and testbeds ,”
Proceedings of the IEEE,Vol.96 (2008),Vol.10,Pg. 1588 -1605.
[3] Florence G. H. Yap, Hong-Hsu Yen , ” A survey on sensor coverage and visual data capturing / processing /
transmission in wireless visual sensor networks.” Sensors (2014), Vol.14,Pg. 3506-3527.
[4] Xiaolan Liu,”A Survey on Wireless Camera Sensor Networks” Book Chapter -Frontier and Future Development of
Information Technology in Medicine and Education, Springer , 2014,pp 1085-1094.
[5] M.Amac Guvensan,A.Gokhan Yavuz,”On coverage issues in directional sensor networks: A survey”,Elsevier, Ad
Hoc Networks 9 (2011),Pg.1238–1255.
[6] A.Ghosh , S.K.Das,”Coverage and connectivity issues in wireless sensor networks: a survey”, Pervasive and Mobile
Computing ,4,(2008),Pg.303–334.
[7] Mohammad Rahimi et al., ”Cyclops: in situ image sensing and interpretation in wireless sensor networks ”,SenSys ,
Proceedings of the 3rd international conference on Embedded networked sensor systems,(2005),Pg. 192 – 204
[8] Stephan Hengstler et al.,” MeshEye: a hybrid-resolution smart camera mote for applications in distributed intelligent
surveillance”,Information Processing in Sensor Networks, (2007),Pg. 360-369.
[9] Daniel G. Costa, Luiz Affonso Guedes,” The Coverage Problem in Video-Based Wireless Sensor Networks: A
Survey”, Sensors (2010),Vol 10(9),Pg. 8215-8247.

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