## 5 Practical Dependability Assessment
### Dependability Evaluation  
Once the dependability parameters are set, the application requirements need to be defined to assess the system dependability. In this case, it is necessary to define the minimum acceptable area coverage (\(CA_{mb}\)) and quality of monitoring (\(AQM\)), \(CA_{min}\) and \(AQM_{min}\), respectively. For this, based on the layout shown in Figure 9, we consider two obstacles on the monitoring area: a wall \begin{table}
\begin{tabular}{c c c c} \hline \hline
**PRR** & **Failure Probability** & **Fuzzy Function Parameters (\(a,b,c,d\))** & \(\lambda_{lR}\) \\ \hline
0–50\% & Down link & \((0,0,0,0)\) & \(\infty\) \\
50–60\% & Very High & \((0.94,0.95,1,1)\) & \(4.3962\times 10^{4}\) \\
60–70\% & High & \((0.865,0.875,0.925,0.935)\) & \(6.2411\times 10^{4}\) \\
70–80\% & Reasonably High & \((0.77,0.80,0.85,0.86)\) & \(9.4357\times 10^{4}\) \\
80–90\% & Moderate & \((0.715,0.725,0.775,0.785)\) & \(1.3609\times 10^{3}\) \\
90–95\% & Reasonably Low & \((0.64,0.65,0.70,0.71)\) & \(1.5641\times 10^{3}\) \\
95–98\% & Low & \((0.565,0.575,0.625,0.635)\) & \(2.5627\times 10^{3}\) \\
98–100\% & Very Low & \((0.5,0.5,0.55,0.56)\) & \(3.6855\times 10^{3}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters of link reliability and fuzzy model approach. separating a management station to the chemical processes and a forklift that spends most part of time near to a conveyor belt to get the paperboard boxes. Figure 11 shows the network deployment, including the obstacles (blue rectangles) and the quality perspective of \(MA\). Notice that the FoV of visual sensors \(vs_{3}\) and \(vs_{7}\) are partially occluded by the forklift and the FoV of visual sensors \(vs_{4}\) and \(vs_{5}\) are partially occluded by the wall. The coverage area is \(CA_{mb}~{}=~{}21,691\) m\({}^{2}\), which is approximately 50% of total \(MA\), and the quality of monitoring is approximately \(AQM~{}=~{}28\%\). Since in this work it is not considered network redeployment, the maximum coverage area and the maximum quality of monitoring are those ones presented by the network deployment. This means that \(CA_{min}\leq 50\%\) and \(AQM_{min}\leq 28\%\), otherwise this network will not fulfill the application requirements. In order to evaluate the impact of visual failures on dependability, first we perform the system availability assessment considering that \(AQM_{min}~{}=~{}0\%\), varying \(CA_{min}\) from 0% to the maximum value of the area able to be covered by the network deployment (50%). In this case, we intend to verify how large is the portion of area of the monitored field that the system can cover considering the proposed deployment. We can observe in Figure 12a that the system presents an acceptable availability (>99%) for values of \(CA_{min}\) from 0% to 33%. Then, the same analysis is performed considering \(CA_{min}~{}=~{}0\%\) and varying \(AQM_{min}\) from 0% to the maximum value of quality of the monitoring provided by the network deployment ( 28%). Here we intend to verify how well the monitoring field is covered considering the proposed deployment. We can observe in Figure 12b that the system presents an acceptable availability (>99%) for values of \(AQM_{min}\) from 0% to 28%. This analysis implies that, if an application intends to implement the proposed deployment, it will have a considerably satisfactory availability if its requirements of coverage area and monitoring area are \(CA_{min}\leq 33\%\) and \(AQM_{min}\leq 18\%\), respectively. Actually, dependability is assessed here in terms of availability. Notice that, in order to perform a system reliability evaluation, it is only necessary to disregard the repair activities, which means setting the repair rates \(\mu_{hw}\), \(\mu_{bt}\) and \(\mu_{lk}\) equal to zero.