پوشش نظارتی PTZ بر اساس هوش مصنوعی
Abstract
1- Introduction
2- Literature review
3- Problem definition
4- Methodology
5- Validation experiments & results
4- Case study: “the Green River in the new administrative capital in Egypt”
7- Conclusions
References
Abstract
Surveillance cameras have a plethora of usages in newly born cities including smart traffic, healthcare, monitoring, and meeting security needs. One of the most famous new cites is the Egypt’s new administration capital “New Cairo”. The new administration capital of Egypt mainly characterizes with the green life style via the “Green River “. In this paper, a new enhanced Artificial Intelligence (AI) algorithm is introduced for adjusting the orientation of Pan–Tilt–Zoom (PTZ) surveillance cameras in new Cairo. In other words, the new proposed algorithm is used for improving the field of view (FOV) coverage of PTZ cameras network. For validating the proposed algorithm, it is tested on many scenarios with different criterions. After that, the proposed algorithm is applied to adjust the PTZ monitoring cameras in the green river which locates on new administrative capital as an equivalent to the river Nile. In addition, it compared with several other AI algorithms through the appropriate statistical analysis. The overall experimental results indicate the prosperity of the proposed algorithm for increasing the coverage of the PTZ surveillance system.
Introduction
The wave of technological development has swept through our world until most of the modern residential cities have become smart cities characterized by automation and intelligence. The smart city can be defined as a high-level ontology that describes the semantic categories including a series of innovations in urban systems sustained by broadband networks, sensors, data management technologies, software applications and e-services (Komninos & Mora, 2018). Roughly speaking, the smartness of the city is determined by the Structure and Functions of its Semiotics (Data, Information, Knowledge) management system. So, these functions can be summarized as (Ramaprasad, Sánchez-Ortiz, & Syn, 2017):
Therefore, one of the most important pillars of such a smart urban is the surveillance systems so-called image sensors/camera networks, which can be considered vision organs of the smart city.
Network cameras are used in smart cities across the globe for monitoring, surveillance and other security needs. Due to the Internet of Things (IoT) comes to life; they extend well beyond simple surveillance tasks to other application scenarios. There are several types of cameras which differ in servo capabilities, sensor element, lens type, etc. In general, they can be categorized into three main types (Erdem & Sclaroff, 2006): Fixed Perspective, Omni-directional, and Pan-TiltZoom (PTZ) cameras. The former has a fixed position, orientation, and focal length. The second has a full 2 horizontal coverage but it has a small focal length which may cause undesirable lens aberration effects. The last type of cameras (PTZ) is adjustable in a predefined range. They can be rotated horizontally and vertically around their (Tilt) and (Pan) axis respectively. Also, some PTZ cameras have an adjustable focal length (Zoom).