Crowd Risk v1.0
AI-Powered Threat Detection & Mitigation System
Intelligent, real-time analysis of crowd behavior, vehicle movements, and individual risk factors to proactively identify and mitigate potential threats.
System Overview:
Crowd Risk utilizes advanced AI algorithms and multisource surveillance technologies to analyze crowd behavior, track suspicious movements, and identify potential threats in real-time. The system can trigger automatic interventions, such as raising barriers or alerting ground officers, and integrates with existing security infrastructure like facial recognition, FLIR cameras, and vehicle tracking systems.
Core Capabilities:
1. AI-Driven Crowd Behavior Analysis:
Rapid Movement Detection:
AI tracks individuals in high-density crowds, focusing on those exhibiting rapid or erratic movement patterns that may indicate suspicious behavior (e.g., fleeing, aggressive approach, or concealed actions).
Backpack and Item Detection:
Subjects carrying backpacks or other large items in restricted areas are flagged by the system as potential risks. The AI also analyzes whether the behavior aligns with patterns of previous incidents (e.g., suspicious packages).
Behavioral Risk Scoring:
Real-time analysis assigns a risk score to individuals based on their movements and proximity to other people, with thresholds configurable based on specific crowd dynamics or event context.
2. Subject and Vehicle Tracking:
Crowd Tracking and Highlighting:
Individuals flagged by the AI are automatically tracked within the crowd, with their movement paths highlighted for officers to assess. If the subject’s risk score exceeds a set threshold, the system escalates the situation and triggers ground unit intervention.
Vehicle Detection and Tracking:
Utilizes 4K PTZ cameras with high optical zoom to detect and track vehicles within a one-mile radius of crowded areas, particularly in zones where vehicle presence is prohibited.
Automatic Vehicle Flagging:
The system flags vehicles entering restricted zones or behaving suspiciously (e.g., loitering, slow movement, or avoiding traffic control points).
Suspicious Vehicle Alert:
Automatic alerts are sent to law enforcement for immediate intervention, with vehicle details (e.g., license plates, color, make/model) displayed in real-time.
3. Facial Recognition & Blacklist Integration:
God’s Eye Integration:
Integrates seamlessly with God’s Eye or other facial recognition systems to compare detected faces against a known blacklist of persons of interest, such as wanted suspects or high-risk individuals.
Real-Time Facial Matching:
When a subject enters a crowded area or approaches restricted zones, facial recognition can instantly compare their image to a database, alerting officers to the presence of a flagged individual.
4. FLIR (Thermal Imaging) Camera Integration:
Heat Signature Detection:
Integrates with FLIR cameras to detect abnormal heat signatures, such as hidden objects or persons attempting to conceal something dangerous. For example, a sudden increase in temperature may indicate a person hiding a weapon or an explosive device.
Risk Scoring Based on Heat Data:
The AI evaluates detected heat signatures against known risk patterns (e.g., carrying concealed devices) to assign a thermal risk score to each individual in the crowd.
5. AI Psychological Risk Analysis:
Psychological Behavioral Modeling:
Amygdala’s AI algorithms analyze a subject’s body language, facial expressions, and movements to assess emotional states such as agitation, stress, or hostility. This can indicate a subject’s likelihood of being involved in a violent confrontation or other criminal behavior.
Predictive Threat Modeling:
AI models integrate psychological profiles with real-time data to predict potential future actions based on the subject’s behavior and proximity to sensitive locations or individuals.
6. Automated Physical Barrier Control:
API-Controlled Barrier Systems:
Crowd Risk can be integrated with automated physical systems such as barriers, gates, or bollards. When the system identifies a potential threat, such as unauthorized vehicle access or suspicious movements in high-risk areas, barriers can be raised autonomously through API calls, ensuring that the public space is immediately secured.
Deployment Requirements:
Cameras & Sensors: 4K PTZ cameras with high optical zoom for vehicle detection, FLIR thermal cameras for heat signature analysis
AI Processing Infrastructure: GPU-accelerated processing nodes, capable of real-time AI analysis for large-scale environments (e.g., city streets, public events)
Communication Network: Low-latency, secure communications for real-time alerts and coordination with law enforcement (5G, dedicated private network, or encrypted radio communication)
Integration with Existing Systems: API for seamless integration with facial recognition (God’s Eye), vehicle databases, and crowd control systems
Data Storage & Privacy: Secure, encrypted cloud storage with compliance to data retention and privacy laws (e.g., GDPR, CJIS)
User Interface: Real-time monitoring dashboard for situational awareness and decision-making, with customizable alerts for officers
Operational Workflow:
Crowd Surveillance & Behavior Analysis:
AI continuously monitors the crowd for unusual movements or individuals exhibiting suspicious behavior (e.g., rapid movement, carrying bags).
Flagged individuals are tracked, and behavioral risk scores are calculated, with escalating alerts if a subject’s actions suggest an imminent threat.
Vehicle Detection & Monitoring:
AI scans for vehicles in restricted areas or behaving suspiciously. When a vehicle is flagged, real-time alerts are sent to law enforcement to coordinate an immediate response.
Facial & Blacklist Matching:
The AI cross-references facial data against a known blacklist and sends alerts if a high-risk individual is detected in the crowd.
Risk Mitigation & Response:
Based on real-time data analysis, automated barriers may be raised, and officers are dispatched to intervene with high-risk individuals or vehicles.
Psychological risk analysis assists officers in determining whether a subject poses a threat, enabling them to take preventive action before escalation.
Key Benefits:
Proactive Threat Mitigation:
AI detects potential threats in real-time, allowing officers to intervene before an incident escalates.
Optimized Resource Allocation:
By prioritizing high-risk subjects and vehicles, law enforcement can focus resources where they are most needed, improving overall response efficiency.
Enhanced Crowd Control:
Automated barrier control reduces the need for manual intervention and improves crowd safety during events or in urban environments.
Comprehensive Threat Detection:
Combining facial recognition, vehicle tracking, and psychological analysis ensures that all potential threats are assessed, regardless of how they attempt to disguise or avoid detection.
System Requirements: LINUX