A Framework For An Event Driven Video Surveillance System

A Smart Home Environment (SHE) comprises various luxurious things which makes us very comfortable to live our lives happily and securely. The only problem that smart homes are facing is “SECURITY”. Security for smart homes is the biggest task to achieve. For this purpose, this work is to build a product that provides the security for the smart homes automatically when the crime is going to happen. In general case, if any crime had taken place in any smart home, the general procedure of investigation will take place i.e. the people will complain to the police and the police will visit the place and after that he will observe the surroundings clearly. In order to pull up the clues if any, he will watch the CCTV footage, consult the nearby people in-order to draw some facts and then FIR will be filed. In order to get rid of this time-consuming process, the automatic crime detection is proposed. Here malware practices are identified, when a person attempts crime activity. This type of automatic process of detection of crime will ensure a complete security for the smart homes. We will track the CCTV camera pictures when the thief is trying to commit a crime and the information along with the pictures will be sent to the fog server and the fog server will analyze whether the person is doing crime or not. In case if a fog server had identified the person as a crime person or a thief then it automatically sends the information to the near- by police station and as well as owners of the house and then provides security for the smart homes

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“…It likewise accomplishes huge proficiency contrasted with SoA or customary observance structures. [21][22]…”

Section: Related Workmentioning

confidence: 99%

Security management in smart home environment

Gladence

Anu

Revathy

et al. 2021

Preprint

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“…Fan et al [31] described a novel visualization mechanism which fuses multimodal information for large-scale intelligent video surveillance, utilizing an event-driven approach. Some architectures and frameworks for eventdriven video surveillance approaches are also described in [32], [33], and [34], along with energy-aware, event-driven video surveillance solutions, such as [35] and [36].…”

Section: Related Background Surveymentioning

confidence: 99%

IoT-Guard: Event-Driven Fog-Based Video Surveillance System for Real-Time Security Management

Sultana

Wahid

2019

IEEE Access

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In this paper, we design and implement a distributed Internet of Things (IoT) framework called IoT-guard, for an intelligent, resource-efficient, and real-time security management system. The system, consisting of edge-fog computational layers, will aid in crime prevention and predict crime events in a smart home environment (SHE). The IoT-guard will detect and confirm crime events in real-time, using Artificial Intelligence (AI) and an event-driven approach to send crime data to protective services and police units enabling immediate action while conserving resources, such as energy, bandwidth (BW), and memory and Central Processing Unit (CPU) usage. In this study, we implement an IoT-guard laboratory testbed prototype and perform evaluations on its efficiency for real-time security application. The outcomes show better performance by the proposed system in terms of resource efficiency, agility, and scalability over the traditional IoT surveillance systems and state-of-the-art (SoA) approaches. INDEX TERMS IoT, edge, fog, video surveillance, convolutional neural network, motion detection, gun-knife detection, real-time security, message queuing telemetry transport (MQTT).

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“…This framework has been used for a range of tasks such as fall detection [10] or recognizing and regulating emotions [11,12]. [47] describes a multisensor architecture for event detection in video sequences where the focus changes from one sensor to another for monitoring as optimally as possible. The events are detected by finite state machines.…”

Section: Framework For Hybrid Monitoringmentioning

confidence: 99%

A Review on Intelligent Monitoring and Activity Interpretation

Castillo

Fernández-Caballero

López

2017

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This survey paper provides a tour of the various monitoring and activity interpretation frameworks found in the literature. The needs of monitoring and interpretation systems are presented in relation to the area where they have been developed or applied. Their evolution is studied to better understand the characteristics of current systems. After this, the main features of monitoring and activity interpretation systems are defined. Resumen Este trabajo presenta una revisión de los marcos de trabajo para monitorización e interpretación de actividades presentes en la literatura. Dependiendo delárea donde dichos marcos se han desarrollado o aplicado, se han identificado diferentes necesidades. Además, para comprender mejor las particularidades de los marcos de trabajo, esta revisión realiza un recorrido por su evolución histórica. Posteriormente, se definirán las principales características de los sistemas de monitorización e interpretación de actividades.

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A Framework For An Event Driven Video Surveillance System

Cited by 20 publications

References 14 publications

Security management in smart home environment

Security management in smart home environment

IoT-Guard: Event-Driven Fog-Based Video Surveillance System for Real-Time Security Management

A Review on Intelligent Monitoring and Activity Interpretation

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