In conventional wireless sensor networks (WSNs), scalar phenomena can be traced
using thermal or acoustic sensor nodes. In camera sensor networks (CSNs), images and
videos can significantly enrich the retrieved information from the monitored environment,
and hence provide more practicality and efficiency to WSNs. Recently, there has been enormous
development of applications in surveillance, environment monitoring and biomedicine
for CSNs that has brought a new spectrum to the coverage problem. It is indispensable
to understand how the coverage of a camera depends on various network parameters to
better design numerous application scenarios.
In many network configurations, cameras are not mobile and they remain stationary
after the initial deployment. However, different from a stationary CSN, maritime environment
poses challenges on the deployment characteristic and mobility pattern for CSNs. In
stationary CSNs, when the deployment characteristic and sensing model are defined, the
coverage can be deduced and remain unchanged over time. In the maritime environment,
camera sensors are mounted on quasi-mobile platforms such as buoys. This thesis aims
to provide full-view coverage CSN for maritime surveillance using cameras mounted on
buoys.
It is important to provide full-view coverage because in full-view coverage, targets facing
direction is taken into account to judge whether a target is guaranteed to be captured.
Image shot at the frontal viewpoint of a given target considerably increases the possibility
to detect and recognize the target. The full-view coverage has been achieved using equilateral
triangle grid-based deployment for the CSN. To accurately emulate the maritime
environment, a mobility pattern has been developed for the buoy which is attached with
a cable that is nailed at the sea floor. The buoy movement follows the sea wave that is
created by the wind and it is limited by the cable.
The average percentage of full-view coverage has been evaluated based on different
parameters such as equilateral triangle grid length, sensing radius of camera, wind speed
and wave height. Furthermore, a method to improve the target detection and recognition
has been proposed in the presence of poor link quality using cooperative transmission with
low power consumption.
| Date of Award | 2014 |
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| Original language | American English |
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| Supervisor | Peng-Yong Kong (Supervisor) |
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- Buoy
- Camera Sensor Network
- Full-view Coverage
- Maritime wireless Mesh Network
- Sea Wave and Spring.
Full-View coverage camera sensor network (CSN) for maritime surveillance
Manoufali, M. A. A. (Author). 2014
Student thesis: Master's Thesis