Abstract
Wireless visual sensor networks are commonly employed on several applications contexts such as smart cities, intelligent transportation systems and industrial management, aiming at the use of visual data from cameras to provide enhanced information and to expand the networks utilities. In these scenarios, some applications may require high-definition images when performing more specialized tasks, for example in face and text recognition, adding an important monitoring requirement when using camera-based sensors. In fact, it is important to ensure that the network is able to gather visual data with the associated required quality to each task, and such perceived quality may be processed as a function of the Field of View (FoV) of the visual sensors. In order to address this issue, new quality metrics are proposed for wireless visual sensor networks that are deployed to perform area coverage, exploiting for that different perceptions of the FoV. Those metrics are proposed along with redeployment optimization methods for visual sensor nodes aiming at the improvement of the perceived monitoring quality, which are based on greedy and evolutionary-based approaches. The proposed metrics and algorithms are expected to be more realistic than previous solutions, allowing flexible processing of variables as cameras' positions, orientations and viewing angles, providing then high flexibility on the definition of parameters and significantly contributing to the development of sensor networks based on visual sensors.
Highlights
Several applications have benefited from the use of distributed systems and visual information when achieving a more comprehensive perception of the monitoring context, usually employing (Wireless) Visual Sensor Networks (WVSN) composed of a set of camera-enabled nodes [1]
PROPOSED OPTIMIZATION ALGORITHMS In order to illustrate the utility of the proposed metrics, three optimization algorithms are proposed aimed at the maximization of the Field of View (FoV)-based quality of monitoring on randomly deployed WVSN
We show how the metrics Area Quality Metric (AQM) and AQMrel are associated and how they can be used together to analyze the Quality of Monitoring (QoM) perception
Summary
Several applications have benefited from the use of distributed systems and visual information when achieving a more comprehensive perception of the monitoring context, usually employing (Wireless) Visual Sensor Networks (WVSN) composed of a set of camera-enabled nodes [1]. It is possible to save resources or use cheaper hardware in order to perform simpler monitoring tasks, while achieving acceptable results Such scenario, with applications with different demands concerning the quality of retrieved visual data, is susceptible to the adoption of quality metrics that leverage the processing and resource allocation in such networks. Quality of monitoring is a generic term used to refer to the capability of a network to perform the expected monitoring functions over the region of interest In this case it is assessed the value of gathered visual information not considering content degradation, it is possible to join both approaches for a more realistic assessment.
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