Video-Based Abnormal Behaviour Detection in Smart Surveillance Systems

2021 ◽  
pp. 329-338
Author(s):  
Othman O. Khalifa ◽  
Hazwani Abdul Khodir ◽  
Noreha Abdul Malik ◽  
Norun Farihah Abdul Malek
Keyword(s):  
Surveillance Systems ◽  
Abnormal Behaviour ◽  
Smart Surveillance

WSN‐ and IoT‐Based Smart Surveillance Systems for Patients with Closed‐Loop Alarm

2022 ◽  
pp. 143-176
Author(s):  
Amit Sundas ◽  
Sumit Badotra ◽  
Shalli Rani ◽  
Chhabildas Madhukar Gajare
Keyword(s):  
Closed Loop ◽  
Surveillance Systems ◽  
Smart Surveillance

scholarly journals Affective State Based Anomaly Detection in Crowd

2019 ◽  
Vol 24 (2) ◽  
pp. 134-140
Author(s):  
Glorija Baliniskite ◽  
Egons Lavendelis ◽  
Mara Pudane
Keyword(s):  
Anomaly Detection ◽  
Video Surveillance ◽  
Positive Emotions ◽  
Emotional State ◽  
Affective State ◽  
Surveillance Systems ◽  
Abnormal Behaviour ◽  
Density Space

Abstract To distinguish individuals with dangerous abnormal behaviours from the crowd, human characteristics (e.g., speed and direction of motion, interaction with other people), crowd characteristics (such as flow and density), space available to individuals, etc. must be considered. The paper proposes an approach that considers individual and crowd metrics to determine anomaly. An individual’s abnormal behaviour alone cannot indicate behaviour, which can be threatening toward other individuals, as this behaviour can also be triggered by positive emotions or events. To avoid individuals whose abnormal behaviour is potentially unrelated to aggression and is not environmentally dangerous, it is suggested to use emotional state of individuals. The aim of the proposed approach is to automate video surveillance systems by enabling them to automatically detect potentially dangerous situations.

scholarly journals Arcabouço de Vigilância Inteligente para Operações de Compras Eletrônicas no Contexto de Smart Cities

2019 ◽  
Author(s):  
Suzani Dos Santos ◽  
Robson De Melo ◽  
Nivaldi Calonego Junior
Keyword(s):  
Computer Networks ◽  
Smart Cities ◽  
Computer Systems ◽  
User Profile ◽  
Surveillance Systems ◽  
Intelligent Surveillance ◽  
Vulnerability Reduction ◽  
Surveillance Model ◽  
Smart Surveillance ◽  
Suspicious Activity

Intelligent surveillance systems aim to identify suspicious activity beyond the observation of people and environments, as computer networks and computer systems remain vulnerable to malicious actions. The intelligent surveillance framework (Arcabouço de Vigilância Inteligente - AVI) uses the cognitive construction of a user profile and the recognition of devices for electronic purchases, aiming to ensure the authenticity of transactions for computer systems in networked interconnected. The AVI assessment shows that it is effective with respect to user authenticity and that the smart surveillance model in purchasing operations matches the expectation of vulnerability reduction.

Automated and coupled services of advanced smart surveillance systems toward green IT: tracking, retrieval and digital evidence

2014 ◽  
Vol 69 (3) ◽  
pp. 1215-1234 ◽  
Author(s):  
Su-Wan Park ◽  
Deok Gyu Lee ◽  
Jong Wook Han ◽  
JeongNyeo Kim
Keyword(s):  
Digital Evidence ◽  
Surveillance Systems ◽  
Green It ◽  
Smart Surveillance

A suspicious behaviour detection using a context space model for smart surveillance systems

2012 ◽  
Vol 116 (2) ◽  
pp. 194-209 ◽  
Author(s):  
Arnold Wiliem ◽  
Vamsi Madasu ◽  
Wageeh Boles ◽  
Prasad Yarlagadda
Keyword(s):  
Surveillance Systems ◽  
Space Model ◽  
Smart Surveillance

Smart Surveillance Systems and Their Applications

2020 ◽  
pp. 179-187
Author(s):  
Andrei Braicov ◽  
Ivan Budanaev ◽  
Marco Cosentino ◽  
Walter Matta ◽  
Alessandro Mattiacci ◽  
...  
Keyword(s):  
Surveillance Systems ◽  
Smart Surveillance
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