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Practical Guide

Video Analytics Use Cases for Public Safety

The 8 main video analytics use cases in command centers and public safety — with performance metrics, infrastructure requirements, and how each integrates with CAD dispatch and GIS.

8 Video Analytics Use Cases for Command Centers

🔒

Perimeter Intrusion Detection

Automatic alerts when vehicles or people cross virtual lines, enter restricted zones, or loiter in sensitive areas. Applies to airports, ports, critical infrastructure, and municipal perimeters.

< 2s alert latency
🚗

License Plate Recognition (LPR)

Real-time identification of stolen, wanted, or blacklisted vehicles as they cross any camera in the network. Integrated with CAD dispatch for immediate unit assignment.

95%+ recognition rate
👥

Crowd Counting and Density

Occupancy monitoring in plazas, public transit, stadiums, and mass events. Preventive alerts before density reaches risk levels. Real-time data for dispatch decisions.

±5% accuracy in real time
⚠️

Behavioral Anomaly Detection

AI models trained to detect extended loitering, abandoned objects, sudden crowd surges, aggressive behavior, and risk situations before they escalate to incidents.

1-5% false positive rate
🔍

Forensic Analysis and Retroactive Search

Retroactive search across hours or days of recordings by visual attributes: clothing color, vehicle type, direction of travel, geographic zone. Reduces investigations from days to minutes.

10-100x faster than manual review
🚦

Traffic Incident Management

Automatic detection of accidents, stalled vehicles, wrong-way drivers, and lane violations. Coordinated alerts between K-Traffic and K-Safety for integrated traffic-emergency response.

Detection in < 30s
🔥

Smoke and Fire Detection

Specialized models detecting visible smoke and flames on outdoor cameras before interior smoke sensors activate. Especially relevant for critical infrastructure and industrial zones.

Early detection 2-5 min ahead
📊

CAD Dispatch Correlation

Direct integration of video alerts with the CAD system — the nearest camera to the incident is automatically linked to the dispatch record. Operator evaluates video and dispatches units from one screen.

20-40% response time reduction

How Video Analytics Integrates with the Command System

In an isolated system, video analytics generates alerts that no one reviews. In a unified platform, every alert triggers a complete operational flow: the event is geolocated on the GIS map, the nearest camera is linked to the CAD record, and the dispatcher has full visual context in seconds — without switching screens.

01

Alert detected

Video analytics detects the event and generates an alert with GPS coordinates and video clip.

02

GIS map updated

The event appears on the command center operational map with the linked camera and zone history.

03

Dispatch in one screen

The dispatcher reviews the video, checks available resources, and dispatches the nearest unit — all from K-Safety.

K-Video
VMS + AI analytics
K-Safety
Operational GIS map
K-Dispatch
CAD dispatch

Frequently Asked Questions

What are the most common video analytics use cases in public safety?

The most common use cases in public safety are: (1) perimeter intrusion detection — alerts when vehicles or people cross restricted zones; (2) license plate recognition (LPR) — real-time identification of stolen or wanted vehicles; (3) crowd density counting — monitoring occupancy in public spaces and mass events; (4) behavioral anomaly detection — loitering, abandoned objects, crowd surges; (5) forensic analysis — retroactive search for suspects by visual attributes; (6) CAD dispatch correlation — linking video alerts directly to unit assignment in the dispatch system.

How does video analytics improve emergency response time?

Video analytics reduces response time in two ways: first, by detecting incidents automatically before anyone calls 911 — perimeter breaches, wrong-way vehicles, fallen persons — and sending immediate alerts to the dispatcher. Second, by providing visual context to the dispatcher at the moment of the incident: the nearest camera to the event is automatically linked to the incident record in the CAD, reducing evaluation time and improving dispatch accuracy. Centers integrating video analytics with CAD report 20-40% reductions in response times.

Can video analytics work with existing cameras?

Yes. Modern video analytics systems like KabatOne process the RTSP/ONVIF stream from any existing camera — no hardware replacement needed. Analytics run on a central server (or in the cloud) on top of already-installed video infrastructure. The exception is functions requiring edge computing on the camera itself (like very low-latency detection) which do need cameras with embedded AI chips. For most command center use cases, centralized processing is sufficient and more flexible.

What is the difference between video analytics and facial recognition?

Video analytics is the broad term covering all types of automated image analysis: motion detection, people counting, object classification, vehicle tracking — and facial recognition. Facial recognition is a specific subset that identifies individuals by comparing biometric facial features against a database. Other types of analytics (LPR, intrusion detection, behavioral analysis) do not require individual identification and face fewer regulatory restrictions than facial recognition.

What infrastructure does a municipal-scale video analytics system require?

For 200-500 cameras with real-time analytics: GPU servers for processing (8-16 GPU cores per 100 concurrent streams), network with 2-4 Mbps per camera at 1080p/30fps, storage for retention (30-90 days), and a management platform that unifies alerts, GIS map, and CAD. Sizing varies significantly based on the complexity of AI models applied. KabatOne scales from small municipalities with 50 cameras to state-level C5 centers with 10,000+ concurrent streams.

How does video analytics integrate with a C5 or CIOPS command center?

In a C5 or CIOPS, video analytics alerts are not isolated notifications — they integrate directly into the GIS operational map as geolocated events. The operator sees the alert on the map with the linked camera, reviews the live feed, and can dispatch a unit from the same screen. KabatOne automatically correlates the video alert with that zone's incident history, nearest available resources, and active LPR alerts — delivering complete context in seconds.

Related Resources

What Is Video Analytics?VMS Software GuideWhat Is a Real-Time Crime Center?What Is Situational Awareness Software?

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