Milesight![banner v]( "banner v")
CA 2.0 Technology
Next-Level Accuracy for Real-World Security
- Pain Point
- Milesight VCA 2.0
- How it Works
- Home
- AI Technology
- AI VCA 2.0
The Pain Point of False Alarms
Extremely High False
Alarm Rates
Studies show false alarm rates as high as 95–98% for typical intrusion detection systems using traditional video surveillance. That means nearly all alarms triggered are not caused by real threats — but by wind, shadows, animals, or minor environmental shifts.
Hidden But
Costly Consequences
Every false alert comes with a price. The average cost per incident ranges from tens to hundreds of dollars, including fines, staff response, and operational disruptions. A survey by Parks Associates found that two-thirds of security system owners have paid false alarm fines, averaging $150 per incident.
Low Accuracy =
Low Trust, High Risk
Too many false positives lead to team frustrated. Teams ignore warnings — only to risk missing the ones that matter. Worse still, outdated systems often fail to detect real intrusions, especially in long-range or crowded scenes, where critical details get lost.
How Milesight Solves It
Introducing Milesight VCA 2.0
Milesight VCA 2.0 is an upgraded, AI-powered video content analysis engine that integrates 8 essential VCA functions, purpose-built for essential security tasks. From intrusion to line crossing, it delivers precise, real-time detection — even in low light, rain, or fog — with dramatically reduced false alarms.
Advanced Motion
Detection
Region Entrance
Region Exiting
Intrusion Detection
Loitering
Line Crossing
Object Removed
Object Left
AI-Powered Filtering That Makes Every Alarm Count
Milesight's VCA 2.0 leverages advanced AI models and smart filtering mechanisms to distinguish between real threats and environmental noise. By learning from real-world data and context-aware analysis, Milesight VCA 2.0:
- Reduces false alarms caused by animals, lighting, rain, or subtle environmental changes
- Enhances object recognition even in long-range, crowded or complex scenes
- Keeps tracking consistent to avoid frame-breaking or Object ID loss
- Ensures critical events are captured, not overlooked
Ultra-low False Alarm Rate
Super Long AI
Detection Range
Small Object
Recognition
Multiple Object
Recognition
Human
Filtering
Vehicle / Vehicle
Types Filtering
How Milesight VCA 2.0 Ensures High Accuracy
Small Object Recognition
Enhanced Targets Tracking
Environmental Filtering
Traditional Algorithm
Distant people or vehicles occupy too few pixels, leading to missed detection or unstable recognition.
Milesight VCA 2.0
Employs purpose-built models trained on real-world scenes, specifically developed by Milesight to enhance sensitivity to small and distant targets—without compromising system stability.
Result:
Longer detection range and fewer missed events — reaching up to 75 meters even with fixed-lens cameras.
Traditional Algorithm
Performs poorly in busy scenes with multiple moving objects.
Common issues include:
- Broken detection boxes
- ID switching
- Targets disappearing from view
Milesight VCA 2.0
Uses enhanced matching logic to maintain stable ID tracking across frames.
Solves problems like:
- Tracking loss of jogging targets
- Tracking confusion in crowded scenes
- Missed alarms due to frame loss
Result:
Milesight VCA 2.0 minimizes tracking interruptions and significantly reduces the chance of missed detection — even in high-density and busy scenarios.
Traditional Algorithm
High false alarm rate caused by irrelevant movement, including raindrops within the view, swaying tree branches, or small animals crossing the scene. These typical interferences are often misclassified as human or vehicle movement.
Milesight VCA 2.0
- Begins with human/vehicle classification to focus only on meaningful targets and ignore irrelevant background motion.
- Specialize filtering logic by replacing bounding box shake detection with a center-point movement check. If the center-point barely moves, it's treated as harmless vibration — avoiding alarms caused by minor scene shifts, such as light flicker or bounding box shack caused by raindrops.
- Includes specialized algorithm training and optimization to handle common false alarm sources such as small animals, flying insects, lighting changes, spider webs, and extreme weather conditions.
Result:
By combining refined motion detection logic with scene-specific algorithm and scenario-trained models. Milesight VCA 2.0 significantly reduces false alarms caused by rain, lighting variation, insects, and so on.
