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AI system enhances crowd safety with real-time monitoring and response

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Drishti AI-Event Guardian, a real-time crowd monitoring system designed to enhance safety at mass gathering events. The framework utilizes deep learning models, including YOLOv8 and gradient-boosted regression, to process data from CCTV and UAVs for crowd density estimation, anomaly detection, and predictive crowd-flow modeling. Key features include facial recognition for missing persons, automated medical emergency dispatch, a conversational AI chatbot for incident reporting, and dynamic guard reallocation based on crowd density. AI

IMPACT This system could significantly improve public safety at large events by enabling proactive interventions and more efficient resource allocation.

RANK_REASON The cluster contains a research paper detailing a new AI system for crowd monitoring and emergency response. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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

AI system enhances crowd safety with real-time monitoring and response

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The cluster contains a research paper detailing a new AI system for crowd monitoring and emergency response. [lever_c_demoted from research: ic=1 ai=1.0]
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paper, product, safety
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High
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114 days old
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ritabrata Roy Choudhury, Arkajyoti Karmakar, Rudra Pratap Mitra ·

    Drishti AI-Event Guardian: An Intelligent Real-Time Crowd Monitoring and Emergency Response System for Mass Gathering Events

    arXiv:2606.05185v1 Announce Type: cross Abstract: Mass gathering events are associated with critical safety incidents caused by insufficient crowd monitoring and inadequate emergency response coordination. Traditional surveillance systems lack intelligent analytics, resulting in …

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