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AI surveillance framework integrates six threat detection capabilities

By PulseAugur Editorial · [1 sources] ·

Researchers have developed "City Sentinel," a unified AI framework designed for smart surveillance that integrates six distinct detection capabilities into a single platform. This system combines facial recognition, automatic number plate recognition, fire and smoke detection, weapon and knife detection, violence detection, and road accident detection. Utilizing models like InsightFace and YOLOv8, City Sentinel processes camera streams in real-time, achieving a median latency of 743 ms and supporting multiple concurrent streams within a two-second limit. The framework aims to provide comprehensive surveillance coverage with cloud-based auditability and flexibility for future expansion. AI

IMPACT This framework could enhance public safety by providing a more integrated and efficient approach to real-time threat detection in urban environments.

RANK_REASON The item is a research paper detailing a new AI framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI surveillance framework integrates six threat detection capabilities

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The item is a research paper detailing a new AI framework. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Hanan Syed Shabir, Noor Fatima, Safia Baloch, Masroor Hussain ·

    City Sentinel: A Unified AI-Based Smart Surveillance Framework for Real-Time Multi-Threat Detection Using Deep Learning

    arXiv:2608.08887v1 Announce Type: new Abstract: Rapid urbanization has increased the need for surveillance systems that can monitor multiple public safety risks at the same time. Traditional systems often use separate solutions for facial recognition, vehicle identification, fire…

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