# Perception of Risks and Usefulness of Smart Video Surveillance Systems
## 3 Results
### Perceived Privacy Risk  
An ANOVA with repeated measures was conducted to answer the second research question. This aimed to determine whether there are differences between gender and privacy levels of smart video surveillance systems in terms of perceived privacy risk.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline  & PL & PG & AW & AS & AP & CS & PLG & TS & AR & SS & SM & ME \\ \hline LS & 3 & 3 & 3 & 1 & 3 & 1 & 3 & & & 3 & \\ PL & 3 & 3 & 3 & 1 & 3 & 3 & 3 & & 3 & \\ PG & & 3 & 3 & 3 & 3 & 3 & & 2 & 3 & 3 & \\ AW & & & 3 & 2 & & 2 & 3 & 3 & 3 & 1 & 2 & 3 \\ AS & & & & & 3 & 3 & 3 & & 3 & & \\ CS & & & & & & 2 & 3 & 3 & 1 & 3 \\ PLG & & & & & & & 3 & 3 & 1 & 2 & 3 \\ TS & & & & & & & & 3 & 3 & 3 & 3 \\ AR & & & & & & & & & 3 & 3 & 3 \\ SM & & & & & & & & & & 3 & \\ \hline \hline \end{tabular} Note: Only significant (\(\rho\leq 0.05\)) results are presented for each group by mapping the following numbers: (1) only men, (2) only women, (3) both groups men and women.  
\end{table}
Table 4: Results of interaction public area \(\times\) gender.  
Figure 4: Interaction public area \(\times\) gender. Note: Significant results are marked with asterisks (*), \(\rho\leq 0.05\). Standard error of means are represented.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline  & PL & PG & AW & AS & AP & CS & PLG & TS & AR & SS & SM & ME \\ \hline LS & 3 & 3 & 3 & 3 & 1 & 2 & 2 & 3 & 3 & & 2 & 1 \\ PL & 3 & 3 & 2 & 2 & 3 & 3 & 3 & 2 & 3 & 3 & 2 \\ PG & & 3 & 3 & 3 & 3 & 3 & 3 & & 3 & 3 & 3 \\ AW & & & & 1 & 3 & 1 & 1 & 3 & 3 & 3 & 1 & 3 \\ AS & & & & & 2 & 1 & 1 & 3 & 2 & 2 & 1 & 2 \\ AP & & & & & 3 & 3 & 3 & 3 & 3 & 1 & 3 \\ CS & & & & & & & 2 & 3 & 3 & 1 & 2 & 3 \\ PLG & & & & & & & & 3 & 3 & 3 & 3 \\ PS & & & & & & & & & 3 & 3 & 3 \\ MS & & & & & & & & & 3 & 3 & 3 \\ \hline \hline \end{tabular} Note: Only significant (\(\rho\leq 0.05\)) results are presented for each group by mapping the following numbers: (1) only day, (2) only night, (3) both groups day and night.  
\end{table}
Table 3: Results of interaction public area \(\times\) time of day.  
The results show a significant effect of privacy levels of a smart video surveillance system, \(F_{GG}(2.58,551.48)=216.17,\rho\leq 0.0001\), \(\eta_{part}^{2}=0.503\) (see Figure 5). No significant interaction gender \(\times\) privacy levels can be shown, \(F(3,642)=2.29\), \(\rho=0.077\), \(\eta_{part}^{2}=0.011\). Furthermore, a significant effect of gender can be shown, \(F(1,214)~{}=~{}11.19,\rho=0.001\), \(\eta_{part}^{2}~{}=~{}0.050\). According to the results of post hoc analyses (Bonferroni) the perceived privacy risk of the exclusive analysis of body movements using digital skeletons and of the exclusive analysis of possible crime weapons are estimated to be significantly lower than the perceived privacy risk of the analysis of biometric features (both: \(\rho\leq 0.0001\)). The privacy risks of the exclusive analysis of body movements using digital skeletons and the exclusive analysis of possible crime weapons are also perceived to be significantly lower than that of the analysis of video recordings but censoring of biometric features (both: \(\rho~{}\leq~{}0.0001\)). Furthermore, the analysis of video recordings but censoring of biometric features is assessed to be significantly less risky than the analysis of biometric features (\(\rho~{}\leq~{}0.0001\)). Other pairwise comparisons do not reach the level of significance of 5%. Additionally, women perceive the risk to their own privacy as significantly lower (\(M~{}=~{}3.45,SD~{}=~{}0.88\)) than men (\(M~{}=~{}3.05,SD~{}=~{}0.81\)).