research-article

Design of an intelligent video surveillance system for crime prevention: applying deep learning technology

Authors:

Chang-Soo Sung,

Joo Yeon ParkAuthors Info & Claims

Multimedia Tools and Applications, Volume 80, Issue 26-27

Pages 34297 - 34309

https://doi.org/10.1007/s11042-021-10809-z

Published: 01 November 2021 Publication History

Abstract

As the security threat and crime rate have been increased all over the globe, the video surveillance system using closed-circuit television (CCTV) has become an essential tool for many security-related applications and is widely used in many areas as a monitoring system. However, most of the data collected by the video surveillance system is used as evidence of objective data after crime and disaster have occurred. And, often time, video surveillance systems tend to be used in a passive manner due to the high cost and human resources. The video surveillance system should actively respond to detect crime and accidents in advance through real-time monitoring and immediately transmit data in case of an accident. This study proposes developing an intelligent video surveillance system that can actively monitor in real-time without human input. In solving the problems of the existing video surveillance system, deep learning technology will be carried through the data processing model design to visualize data for crime detection after building an artificial intelligence server and video surveillance camera. In addition, this design proposes an intelligent surveillance system to quickly and effectively detect crimes by sending a video image and notification message to the web through real-time processing.

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Cited By

Wang SPan XRuan SHan HWang ZYuan HZhu JLi QBaeza-Yates RBonchi F(2024)DiffCrime: A Multimodal Conditional Diffusion Model for Crime Risk Map InferenceProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671843(3212-3221)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671843
Jha R(2022)A novel hybrid intelligent technique to enhance customer relationship management in online food delivery systemMultimedia Tools and Applications10.1007/s11042-022-12877-181:20(28583-28606)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s11042-022-12877-1

Index Terms

Design of an intelligent video surveillance system for crime prevention: applying deep learning technology
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
  2. Machine learning
    1. Machine learning approaches
      1. Neural networks
2. Information systems

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 80, Issue 26-27

Nov 2021

903 pages

ISSN:1380-7501

Issue’s Table of Contents

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021. corrected publication 2021.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 November 2021

Accepted: 10 March 2021

Revision received: 16 November 2020

Received: 17 January 2020

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Cited By

Wang SPan XRuan SHan HWang ZYuan HZhu JLi QBaeza-Yates RBonchi F(2024)DiffCrime: A Multimodal Conditional Diffusion Model for Crime Risk Map InferenceProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671843(3212-3221)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671843
Jha R(2022)A novel hybrid intelligent technique to enhance customer relationship management in online food delivery systemMultimedia Tools and Applications10.1007/s11042-022-12877-181:20(28583-28606)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s11042-022-12877-1

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