Intelligent security systems engineering for modeling fire critical incidents: Towards sustainable security

Security systems are the guarantee of stable functioning of the organization, company, office, industry, housing and other types of buildings. For entire security, complex control devices are set on the building which has to be protected, like fire and burglar alarms, video-audio controls and access systems. Intelligent Security Management System is built on Atmel’s microcontrollers. This allows the system to be flexible and to modify it easily if needed. The reliability of the security system depends on its uniqueness. This given security system is easily modified and hence its reliability is high. The system can be easily integrated into a variety of external modules, which can further increase the factor of reliability. It’s also easy to adopt it to various security management systems. Many of the security and video surveillance systems allow to control the situation of the object from a large distance. From any point of the planet, we can track and manage the security system modes and make easy changes in them, which enable adequate reaction.Digital complexes of video surveillance are one of the variants of defense organization. The main areas of their use are the most important objects and large areas where buildings are located far from each other.

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Multi-Object Tracking Algorithm for RGB-D Images Based on Asymmetric Dual Siamese Networks

Sensors ◽

10.3390/s20236745 ◽

2020 ◽

Vol 20 (23) ◽

pp. 6745

Author(s):

Wen-Li Zhang ◽

Kun Yang ◽

Yi-Tao Xin ◽

Ting-Song Zhao

Keyword(s):

Object Tracking ◽

Human Error ◽

Tracking Algorithm ◽

Movement Trajectory ◽

Shopping Malls ◽

Security Systems ◽

Depth Images ◽

Combined Features ◽

Intelligent Security ◽

Siamese Networks

Currently, intelligent security systems are widely deployed in indoor buildings to ensure the safety of people in shopping malls, banks, train stations, and other indoor buildings. Multi-Object Tracking (MOT), as an important component of intelligent security systems, has received much attention from many researchers in recent years. However, existing multi-objective tracking algorithms still suffer from trajectory drift and interruption problems in crowded scenes, which cannot provide valuable data for managers. In order to solve the above problems, this paper proposes a Multi-Object Tracking algorithm for RGB-D images based on Asymmetric Dual Siamese networks (ADSiamMOT-RGBD). This algorithm combines appearance information from RGB images and target contour information from depth images. Furthermore, the attention module is applied to repress the redundant information in the combined features to overcome the trajectory drift problem. We also propose a trajectory analysis module, which analyzes whether the head movement trajectory is correct in combination with time-context information. It reduces the number of human error trajectories. The experimental results show that the proposed method in this paper has better tracking quality on the MICC, EPFL, and UMdatasets than the previous work.

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Overview of Biometrics and Biometrics Systems

Multimodal Biometrics and Intelligent Image Processing for Security Systems ◽

10.4018/978-1-4666-3646-0.ch002 ◽

2013 ◽

pp. 6-25 ◽

Cited By ~ 1

Keyword(s):

System Performance ◽

Behavioral Characteristics ◽

Biometric System ◽

Security Systems ◽

Biometric Data ◽

Multimodal Biometric System ◽

System Components ◽

Intelligent Information ◽

And Performance ◽

Intelligent Security

Recent security threats increase the necessity to establish the identity of every person. Biometric authentication is a solution to person authentication by analyzing physiological or behavioral characteristics. In this chapter, various biometric notions and terms are reviewed, along with typical biometric system components and different functionalities and performance parameters. The design and development of a biometric system, depending on a particular application scenario, is covered. This chapter also focuses on the inherent issues associated with biometric data and system performance through introducing radically new methods based on intelligent information fusion and intelligent pattern recognition, thus creating a notion of intelligent security systems. At the end of the chapter, the potential drawbacks of biometric unimodal systems, which serves as the motivation to introduce the concept of multimodal biometric system in the context of intelligent security systems, is discussed.

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