Abstract
Wireless sensor networks comprising nodes equipped with cameras have become common in many scenarios, providing valuable visual data for some relevant services such as localization, tracking, patterns identification and emergencies detection. In this context, algorithms and optimization approaches have been designed to perform different types of quality assessment or performance enhancement tasks, addressing challenging issues such as networking, compression, availability, reliability, security, energy efficiency and virtually any subject related to the operational challenges of those networks. However, the dynamics of coverage failures have not been properly modelled in visual sensor networks, resulting in unrealistic perceptions when optimizing or assessing quality in most visual sensing scenarios. Particularly, the Field of View of visual sensors will be affected by occlusion caused by obstacles in the monitored field, which may turn such sensors inadequate for the expected monitoring services of the considered network. Therefore, this article proposes a mathematical model to assess occlusion caused by mobile obstacles such as vehicles on a road or forklifts in an industrial plant, aiming at the selection of the visual sensor nodes that will not have their coverage significantly restricted by those obstacles. Doing so, the proposed model can be exploited by any optimization or quality assessment approach in wireless visual sensor networks, providing a preprocessing method when selecting visual nodes.
Highlights
The development of low-cost highly programmable hardware platforms and Systems on a Chip (SoC) devices have deeply transformed the way sensing and monitoring applications have been created and deployed, opening new possibilities for Wireless Sensor Networks (WSN) [1], [2]
RELATED WORKS Wireless visual sensor networks have been advocated as an important piece of the Internet of Things revolution, providing visual data as images and videos for an uncountable number of applications
The actual impact of the obstacles will vary according to the configurations of the visual sensors and the positions and dimensions of the obstacles. It is defined the concept of Occluded Field of View (FoV) (OFoV), which is a visual coverage area derived from an original FoV
Summary
The development of low-cost highly programmable hardware platforms and Systems on a Chip (SoC) devices have deeply transformed the way sensing and monitoring applications have been created and deployed, opening new possibilities for Wireless Sensor Networks (WSN) [1], [2]. Any performed optimization or quality assessment approach in wireless visual sensor networks should only consider visual sensors that are not under any coverage failure, at the risk of having their results compromised Regarding this perspective over visual sensing, the coverage failures assume a relevant role when perceiving a WVSN and those failures should be properly known and modelled [21]. Such computed set can be processed as an input to any existing optimization or quality assessment approach This innovative methodology might be further extended to include any other type of coverage failure, since this is a broader concept to be exploited, significantly contributing to the development of the wireless visual sensor networks research area. A discussion about the use of visual sensors selection as a tool to support other research works is conducted in Section VII, followed by conclusions and references
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