## 3 Simulation Model for Surveillance Systems
### The Overview of Simulator Structure  
Our simulator was primarily coded using the C# programming language on the Windows 10 operating system. We utilized MATLAB only for visualization purposes. Figure 2: Simulation modeling: (**a**) visualization of a system\(-\)level simulation of a surveillance camera system (red circles mark camera locations, sectors indicate coverage areas, and rectangles represent pedestrians) and (**b**) various parameters of a surveillance camera and a target object. The complete source code is available in the GitHub repository at [[https://github.com/0](https://github.com/0) BoOKim/Surveillance_System_Revision]([https://github.com/0](https://github.com/0) BoOKim/Surveillance_System_Revision) (accessed on 6 August 2023). The fundamental approach taken to implement our system-level simulator involves defining classes that configure the surveillance camera, pedestrians, and the environment. Each class is responsible for generating a predetermined number of instances of surveillance cameras and pedestrians. These entities are then placed on an environment created through the employment of the environment class. This holistic approach enables conducting a comprehensive, system-level simulation of a surveillance camera system. Figure 3 illustrates the architecture of the developed simulation, demonstrating its core structure and components. The main simulation revolves around the utilization of classes that meticulously define the attributes and functionalities of key elements, namely surveillance cameras, pedestrians, and the environment. To start, the Surveillance Camera Class plays a pivotal role in the simulation. This class encapsulates the intricate details of surveillance cameras, encompassing their crucial characteristics and behaviors:  
* The Position property indicates the precise coordinates of each surveillance camera within the simulated environment. * Properties like Sensor Width, Sensor Height, and Focal Length contribute to configuring the camera's sensor, dictating its capture dimensions and focus capabilities. * Viewing Angles in both Horizontal and Vertical domains are also integral properties, determining the extent of the camera's observable field. * The trio of Maximum Surveillance Distance, Blinded Surveillance Distance, and Effective Surveillance Distance properties together outline the range within which the camera operates, accounting for its maximum reach, potential obstructions, and optimal monitoring capability. * Lastly, the class defines the Surveillance Area in the Horizontal and Vertical domains, reflecting the actual coverage area based on sensor dimensions, viewing angles, and distances. Moving on, the Pedestrian Class is another crucial element of the simulation:  
Figure 3: Simulator structure of surveillance camera systems. Within this class, the Position property manages the specific coordinates of each pedestrian object in the environment. * The class also incorporates a Mobility Model, encapsulating details like the pedestrian's moving direction and speed as well as their intended destination. Lastly, the Environment Class encapsulates foundational aspects of the simulated environment:
* It includes attributes like Map Size, which indicates the number of lanes, intervals, and the lane width, defining the scope and structure of the environment. * Vector Values for Roads store critical information about the road network's layout and characteristics. * This class accounts for Intersection Areas, pivotal sections where roads cross each other. * Additionally, it encompasses details about the Initial Positions of Cameras and Pedestrians, setting the stage for the simulation's starting conditions. Collectively, these classes constitute the backbone of the simulation, as described below, enabling the accurate representation and interaction of surveillance cameras, pedestrians, and the environment. By utilizing these meticulously designed classes, the simulation effectively mirrors physical world scenarios and facilitates comprehensive analysis.