###### Abstract
We propose a simulation model that considers different factors such as the number of cameras, their locations, and the type of target objects. Our model can evaluate the surveillance system's performance based on the number of targets detected and the accuracy of target tracking. The simulation results can provide valuable insights into the surveillance system's performance to optimize the system's design and improve its effectiveness. We can identify the weaknesses and strengths of the surveillance system and make necessary improvements  
Figure 1: A surveillance camera system in the real world and in a digital twin world. to ensure better public safety. Our simulation approach can assist in decision making for installing surveillance systems and can be used to evaluate different surveillance system designs. In conclusion, the implementation of a proficient surveillance system holds paramount significance in ensuring public safety. Our simulation methodology offers invaluable perspectives into the system's operational efficacy, facilitating the enhancement of its design and functionality. The simulation model proposed can be employed to assess various surveillance system blueprints and aid decision making pertaining to the installation of a surveillance system in a smart city. We summarize the contribution of our simulation models or simulators towards the assessment and enhancement of surveillance system performance below:  
* Our simulation models offer a viable means of evaluating urban surveillance camera system performance, in line with the research objective of assessing system performance and identifying the factors that influence it. * The model simulates a surveillance area using different camera-related configurations and evaluates the system's performance based on target detection and quality. * Through the definition of the surveillance area and consideration of various camera parameters, the simulation model ascertains whether moving objects fall within the surveillance camera's scope of application, thereby providing insight into the system's operational efficiency. * A comprehensive insight into surveillance system performance is obtained from simulation results, enabling optimization of design and functionality. Moreover, the simulation approach can aid public safety improvements by supporting decision making regarding the installation of surveillance systems and the evaluation of various system designs. Meanwhile, our simulations can be extended to model real-world surveillance camera system behavior, generating data in diverse environments and conditions. This feature facilitates data collection for learning artificial intelligence models and verifying their performance in varied settings. Additionally, data can be collected in a simulated environment, reducing the time and cost required for data collection in an actual environment. The rest of this paper is organized as follows. In Section 2, previous research related to the topic of this study is provided. In Section 3, we introduce the modeling of a surveillance area and the target object to implement a surveillance camera system. This section will also determine whether a target object has been detected and introduce a performance index to evaluate the surveillance resolution. In Section 4, we analyze how various components of the surveillance camera system affect its performance using a simulation that we have implemented. Finally, we conclude our paper in Section 5.