Gun Detection

Gun detection is an AI video analytics capability that identifies visible firearms in live camera feeds and triggers instant alerts to security operators or first responders. In high-risk environments — schools, public transit, retail, government buildings — it can cut response time from minutes to seconds.

How It Works

Gun detection is a specialized object detection model trained on weapons:

1. Detection — a neural network scans each frame for firearm shapes (pistols, rifles, shotguns).
2. Classification — the detection is further classified by weapon type and orientation (carried, aimed, concealed).
3. Confidence filtering — only high-confidence detections trigger alerts to minimize false positives.
4. Multi-frame confirmation — the weapon must persist across several frames to rule out brief misdetections.
5. Alert — an automatic notification reaches operators, law enforcement, or public safety APIs.

Modern engines achieve sub-second detection and alert delivery when integrated with a VMS and communication platform.

Why It Matters

In active-shooter scenarios, response time is the dominant factor in casualty outcomes. Traditional surveillance depends on human operators spotting the weapon on a screen — which rarely happens in time. AI-based detection:

• Reduces response time from minutes to seconds.
• Works 24/7 without operator fatigue.
• Integrates with lockdown systems to trigger doors, alerts, and mass notifications.

IncoreSoft's Gun Detection module is deployed in schools, transit systems, and Safe City programs, often as part of a comprehensive weapon-response protocol.

Use Cases

• Schools and universities — active shooter early warning
• Transit and airports — weapons on platforms or in terminals
• Retail and commercial — armed robbery alerts
• Government and courthouses — weapon entry detection
• Critical infrastructure — perimeter weapon monitoring

Frequently Asked Questions

How accurate is gun detection?

Top systems exceed 95% precision on visible, unoccluded weapons in well-lit scenes. Concealed or partially hidden weapons are much harder. False positives are managed through multi-frame voting and confidence thresholds.

Can it distinguish a real gun from a toy or phone?

Yes, with domain-specific training. Common false positives (phones, umbrellas, tools) are specifically included as negative examples during training to reduce confusion.

Does gun detection replace metal detectors and walk-through scanners?

No — it's complementary. Metal detectors catch concealed weapons at entry points; video detection catches visible weapons anywhere on site. The two together create layered defense.