Benefits of the Nakavision biometric alarm (AI human detection)

Biometric Shape Recognition Instead of Pixel Changes (Humanoid Detection)

Traditional cameras rely on simple pixel comparison (VMD – Video Motion Detection): if light or colour changes between frames, the system assumes movement.

In contrast, the AI processor built into Nakavision cameras performs real-time shape and silhouette analysis:

Recognition of biomechanical proportions:
The algorithm searches for characteristic human body forms (head-to-shoulder ratio, height-to-width proportions, limb dynamics) across video frames.
Filtering out environmental disturbances:
The system does not react to swaying branches, falling leaves, sheets of rain, car headlights, or small pets. This keeps false alarms up to 95–99% lower compared to traditional motion detection.
Precise zones and line crossing (Cordon & Alert Area): Users can set virtual boundary lines or protection zones in the app (e.g. iCSee). The camera can thus ignore traffic on a public pavement and only triggers an alert when someone crosses the line, approaches the gate, or enters the driveway.

Deep Learning and Continuous Adaptation: How Does the Algorithm Learn?

The neural network models of the Nakavision AI platform have been trained on vast image databases. This deep learning foundation enables the camera to recognise people:

In various postures: Standing, walking, running, or viewed from behind.
Across different clothing and seasons: In thick winter coats, hoods, carrying backpacks, or holding an umbrella.
Under changing lighting conditions: In bright sunshine, twilight, and in infrared or colour night vision modes alike.

In addition, the camera processor performs dynamic background segmentation: it frequently updates and assesses the static background image, ensuring that slowly shifting light conditions (e.g. passing clouds, setting sun) do not interfere with detection.

No Compromise, Protection Comes First!

The golden rule of premium security technology is simple: a missed intrusion is an unacceptable risk.

The artificial intelligence in Nakavision cameras does not simply monitor pixel shifts; it identifies real-time biometric shapes and human proportions. A rare situation may arise where a tree branch swaying in the wind, a bush, or a cast shadow temporarily resembles a human silhouette.

If such a pattern repeats multiple times, the algorithm errs on the side of caution. It cannot take the risk of misjudging an intruder lurking behind a hedge and sneaking in unusual clothing as a "harmless shadow". Once in a thousand times, the system would rather request a quick verification on your phone than let a genuine threat slip through.

Why is the Nakavision System Reliable?

Targeted filtering: Trained on millions of real-life scenarios, its model filters out everyday disturbances (rain, wind, insects, small pets).
Local adaptation: The camera processor continuously learns the environment, over time gaining an accurate understanding of the garden's typical features and play of light.
Continuous optimisation: False alarms are rare, and every firmware update further refines the decision accuracy of the neural network.

3 Tips for Greater Accuracy on Your Nakavision Camera

Ideal mounting height: The camera detects human proportions most accurately from a height of 2.4–3 metres at a slight downward angle. Mounting it too high creates an overhead angle that makes silhouette identification harder.
Use intrusion zones (Alert Area): Exclude public areas or neighbouring properties from the field of view, and focus solely on your own grounds.
Fine-tune sensitivity: If garden furniture, sprawling bushes, or specific light sources are in front of the camera, fine-tuning the sensitivity in the app will help you find the ideal balance.