# A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks
## 6 Discussion and Evaluations
### Comparing the Surveyed Categories and Metrics  
The three major groups of quality metrics distinguish the assessment regarding the spatial structure of data (spatial coverage quality), the information in the data itself (content quality) and the conditions for data acquisition (dependable quality). By definition, the groups are very different, being hard to define the best or the most assertive. Each metric presents its own benefits for each kind of application. The proof of this is the fact that 18 works used more than one class of metric to evaluate the visual quality monitoring of the application, with one of them even using all three classes (see Figure 10). Actually, since there are works using all possible combinations of the metric classes, it may be seen as a good indication that the research community is applying quality metrics that best fit the monitoring requirements of the applications, without a strict rule to follow. As a basic principle in this research area, each scenario is expected to demand specific analysis when selecting proper quality metrics. Figure 11: Distribution of the groups and metrics. Figure 10: Classification groups. For instance, spatial coverage quality is generally used when it is intended to optimize the usage of available resources, minimizing the employed sensors set or the application power consumption. Content quality revealed to be important for target detection applications, being essential to represent every little detail from the monitored environment. Dependable quality, in turn, seems to be adequate for safety critical applications, when the successful operation of the application infrastructure is as important as the gathered information itself. In such applications, it is common to be concerned with real-time operation, fault-tolerant systems and contingency measures. In these scenarios, quality evaluation combining more than one group of metrics is an interesting solution to achieve a more comprehensive panorama from the application. It is possible to assess the minimum WVSN configuration to better monitor and represent a region of interest in an intrusion detection application, also guaranteeing face detection and recognition within a bounded time. Furthermore, for each major group of the proposed classification, the sub-classes of metrics also vary widely, existing different ways to compute the same kind of monitoring quality, which can be adjusted for each application. For example, the area coverage for spatial coverage quality can be computed using a discrete and approximated approach, which is computationally faster and energy saving, or it can be computed through an accurate and continuous method, which is computationally and energetically costly, since it may be more realistic in some scenarios. In both cases, the application is evaluated over the same category of quality metric. For each surveyed major group, several metrics were identified in the literature characterizing quality assessment regarding spatial coverage, monitoring content, and dependability. In order to enlighten the reader about which metric is more adequate for an specific evaluation of application performance, a comparative analysis is presented. Tables 4 and 5 provide a comparative analysis of the performance of several surveyed metrics regarding spatial coverage and content quality (respectively), for different monitoring applications on Wireless Visual Sensor Networks. This comparison for dependable quality seems unnecessary, since the only two metrics found in this category (reliability and availability) are, by definition, a special case of the other, i.e., if a system could not be repaired, its availability is equal to its reliability.