High crime rates plague many nations worldwide, and with it comes the problem of lack of security that these countries face. The lack of an efficient monitoring system allows people to commit the most varied types of crimes. Deploying minimally intelligent monitoring systems helps to a great extent to minimize the problem, but they are very costly and well-designed to avoid unnecessary expenses. A point of great importance in planning an intelligent monitoring system is to measure its availability to ensure a configuration that provides the highest possible uptime. In this context, this paper proposes models for evaluating the dependability of an intelligent monitoring system. The proposed models are stochastic Petri nets (SPN) models that allow evaluation of the availability and reliability of the proposed monitoring architecture. The models investigate the impact of maintenance issues on proposals to increase availability. When analyzing the maintenance routines, it was possible to perceive the peculiarity of each one, as well as some negative points in one of them. This study can help speed up planning smart monitoring systems by showing a low-cost method compared to a real test.