A Deep Learning Model For Crime Surveillance In Phone Calls.


EOI: 10.11242/viva-tech.01.04.159

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Citation

Mr. Abhishek Khaire, Mr. Pranav Mahadeokar, Mr. Praveen Kumar Prajapati, Prof. Sunita Naik, "A Deep Learning Model For Crime Surveillance In Phone Calls.", VIVA-IJRI Volume 1, Issue 4, Article 159, pp. 1-6, 2021. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Public surveillance Systems are creating ground-breaking impact to secure lives, ensuring public safety with the interventions that will curb crime and improve well-being of communities, law enforcement agencies are employing and deploying tools like CCTV for video surveillance in banks, residential societies shopping malls,markets,roads almost everywhere to detect where and who was responsible for events like robbery, rough driving, insolence, murder etc. Other surveillance system tools like phone tapping is used to plot an event to catch a suspected person who is threatening an innocent or conspiring a violent activity over a phone call which is being done voluntarily by authorities . Now analyzing both the scenarios in the case of CCTV the crime(robbery,murder) has already occured and in the case of phone tapping there must be information in advance about the suspected person who is going to commit a crime, Now to overcome this issue a system is proposed to know in advace who is suspected and what conspiracy is being done over phone calls as well to detect it automatically and report it to law enforcemet authorities.

Keywords

Deep learning ,Phone calls, Audio analysis ,Surveillance Systems,Threats.

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