Abstract

Many companies and organizations highlighted the importance of developing various security monitoring systems for the purpose of protecting their assets against any undesirable events. The process of installing surveillance cameras inside buildings is complex and costly. One of the most important issues that can affect the cost of surveillance cameras in buildings is finding the best placement of cameras. Individuals who are responsible for the camera installation are facing great challenges due to the large number of variables related to this problem. Finding effective scientific methods to address this problem can lead to increasing the efficiency of the camera placement through maximizing the coverage and minimizing the cost. Furthermore, available methods did not take into consideration the impact of different elements (e.g. the HVAC system) that can affect the camera placement.
Building Information Modeling (BIM) is becoming an indispensable process for the Architecture, Engineering and Construction (AEC) industry. In terms of security management, BIM technology can improve the performance of security systems during the design phase because of its ability to identify various elements that surround the 3D surveillance cameras in the form of geometrical and non-geometrical entities. iv

The objectives of this research are: (1) to develop a method that can help in calculating the coverage of surveillance cameras inside buildings; (2) to investigate the impact of the building elements on the camera configurations, parameters and coverage using BIM; (3) to develop a method that can find the near-optimum types, number and placement of fixed cameras inside a building; and (4) to develop a method that can find the near-optimum placement and movement plan of a Pan-Tilt-Zoom (PTZ) camera inside a building.
A method is developed to calculate the camera coverage inside buildings using BIM and a game engine for the purpose of automating the calculation process and achieving accurate results. This method includes a sensitivity analysis for evaluating the suitable cell size in order to cover the monitored area. Also, the research proposes a novel method using BIM, which provides a new opportunity to better optimize the number and locations of cameras by exploiting the rich information available in the model. The near-optimum results aim to maximize the cameras’ coverages and to minimize their costs. BIM is used to define the input of the optimization process and to visualize the results. The method uses Genetic Algorithm (GA) to solve the optimization problem. Finally, the research addresses the placement problem for a PTZ camera. PTZ cameras are used as an addition to fixed cameras in order to ensure the detection of dynamic activities. The research extends the previous method to optimize the placement and movement plan of a PTZ camera inside a building. Several case studies are used to demonstrate the applicability of the proposed methods. The proposed methods can help individuals who are responsible of the camera installation to efficiently determine