Ai-enabled Surveillance System For Abnormal Activity Detection And Alerting

• Author(s):

  Satheesh Kumar K | Satheesh Kumar.k | B.yogeshwaran | G.v.prabakaran | G.Maheshwaran

• Keywords:

  Convolutional Neural Networks(CNNs), Suspicious Human Behaviors, Proactive Security Management, High False Alarm Rates

• Abstract:

  Surveillance System Is A Network Of Interconnected Devices And Technologies Designed To Monitor, Record, And Analyze Activities In A Particular Area Or Environment. The Primary Purpose Of Surveillance Systems Is To Enhance Security, Gather Data For Analysis, And Provide Insights Into Various Aspects Of The Monitored Space. These Systems Are Commonly Used In A Wide Range Of Settings, Including Public Spaces, Commercial Establishments, Residential Properties, And Governmental Facilities. Many Surveillance Systems Rely On Motion Detection Algorithms To Trigger Alerts. As A Result, False Alarms Are Common, Leading To Alert Fatigue And Reduced Effectiveness. Traditional Surveillance Systems, However, Often Face Challenges Such As Limited Coverage, Manual Monitoring, And False Alarms, Which Can Hinder Their Effectiveness In Detecting And Responding To Security Threats. In Recent Years, Advancements In Artificial Intelligence (AI) And Computer Vision Technologies Have Revolutionized Surveillance Systems By Enabling More Intelligent And Automated Approaches To Monitoring And Analysis. This Project Presents An AI-driven Surveillance System Designed To Enhance Security By Detecting And Responding To Abnormal Activities In Real-time. The Proposed System Utilizes Convolutional Neural Networks (CNN) For Behavior Classification And YOLOv8 (You Only Look Once Version 8) For Abnormal Activities Detection, The System Identifies Abnormal Behaviors And Specific Objects Associated With Security Threats. Upon Detection, An Integrated Alert System Triggers Alarms And Sends SMS And Email Notifications To Designated Personnel, Enabling Swift Response And Intervention. The Customizable Alert Settings Allow For Tailored Notifications Based On The Severity Of Detected Activities. Additionally, The System Logs All Alerts For Post-incident Analysis And Reporting. By Combining Advanced AI Algorithms With Efficient Alerting Mechanisms, This Surveillance System Provides Proactive Security Measures And Enhances Situational Awareness In Monitored Environments.

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Other Details

• Paper id:

  IJSARTV11I5103628

• Published in:

  Volume: 11 Issue: 5 May 2025

• Publication Date:

  2025-05-21

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