## 1 Introduction  
Demand for security and surveillance technologies has emerged recently. This kind of technology provides potential solutions for preventing and reducing crimes and violations. With this significant demand, the use of camera surveillance networks has increased. Indeed, camera or video surveillance is considered as a powerful system used in maintaining order and security in public space (such as transport infrastructure, seaport, airport, parks, stores, _etc._). Accordingly, it is necessary to define appropriate and optimal methods that determine the best location of cameras surveillance. In fact, Camera Placement has a strong effect on the quality and the efficiency of surveillance. An appropriate placement is related to camera properties such as; the range, the field of view, the resolution, the cost of use, the type of the camera (visible-light, infrared...) and so on. However, the most important factor is the environment in which the placement will take place. Indeed, the effectiveness of video surveillance system depends heavily on the physical placement of cameras [1]. Seaports are among the most important places where security is a major concern. Indeed, they are one of the most essential facilities for commercial and tourism activities, especially for coastal countries. They play a major role in the worldwide merchandises' distribution because almost 90% of these goods are shipped through maritime port [2]. Hence, in recent decades, the need for improving seaports security is growing in order to allow safe and efficient transportation of people and merchandises through these transit hubs [3]. In general, the main issues related to seaport security may be classified as perimeter security, internal security and operative controls, maritime security, port community systems, decision support systems, prevention and emergency management, _etc._[4]. To deal with these issues, there are many useful technologies such as video surveillance, radar and sonar, cargo/container screening systems, perimeter security systems, mass notification, wireless systems [3]. According to the same reference, video surveillance is the most common technology used for port security. Through analytic methods, it is possible to extract very useful information from the acquired videos such as perimeter intrusion, following object of interest, and object classification [3]. However, the complexity of the physical landscape can make the tasks of monitoring seaports very hard to fulfill [3]. In this paper, a new GIS oriented approach called \"HybVOR\" (Hyb: Hybrid, VOR: Voronoi) is proposed. It aims to find the optimal placement of surveillance cameras. The main purpose is to reach coverage close to 100% with a minimum number of cameras. The proposed approach is based on a combination of: (1) 3D Modelling and analysis of the Seaport physical landscape and (2) Voronoi approach for the segmentation of space. The space segmentation based on Voronoi Diagram will allow us to specify the number and the location of the cameras for an optimal coverage. In addition, the analysis of the seaport 3D model is based on a combination of Raster and 3D Vector Analysis offered by GIS software, hence, the part \"Hyb\" (from Hybrid) of the name HybVOR. These two types of spatial analysis allow calculating and assessing the coverage area based on the network placement of the surveillance cameras. This paper is structured as follows: The first Section is a literature review on surveillance cameras placement, Voronoi diagram principles, and coverage calculation. The second Section is dedicated to, the principles of HybVOR approach. This Section demonstrates why and how this proposed approach combines Raster and Vector 3D analysis with Voronoi Diagrams. Next, a case study that corresponds to the implementation of the HybVOR approach in Jeddah Seaport is introduced. Afterward, a discussionregarding the results of this case study is presented. Finally, the last section concludes this work and highlights some of the important perspectives and future works.