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All Journal International Journal of Electrical and Computer Engineering
Lakshmanagowda, Chayadevi Mysore
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Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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A deep learning-based surveillance system for enhancing public safety through internet of things and digital technology using Raspberry Pi Sanapannavar, Shreedevi Kareppa; Lakshmanagowda, Chayadevi Mysore; Sundararajan, Geetha
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp7198-7210

Abstract

In public spaces, individuals encounter challenges due to the prevalence of malicious activities like theft and kidnapping. As the internet of things (IoT) and digital technology continue to expand rapidly, efforts to create safe environments are becoming increasingly sophisticated. To address these security concerns, a proposed solution involves the utilization of video-capturing technology with the help of a Raspberry Pi web camera. Videos of the surroundings are recorded, a digital signature algorithm is applied to protect the videos, and they are then transmitted to authorized individuals who use them for forensic analysis. This process allows for the identification and investigation of any suspicious or criminal activities. The captured video data is compared with a standard dataset using a deep learning process. By analyzing the content of the videos and identifying the potential threat objects, we can allow for prompt intervention or further investigation by relevant authorities.
Co-Authors Sanapannavar, Shreedevi Kareppa Sundararajan, Geetha