Troubleshooting Friedland Vehicle Detection Failures
One of the most powerful features of modern Friedland security cameras is their ability to intelligently distinguish between different types of motion, such as people, pets, and vehicles. When vehicle detection is working correctly, it provides you with highly relevant alerts. However, when it fails, you might miss critical events, like a car arriving in your driveway.
This guide is designed to help you diagnose and fix issues with your Friedland camera's vehicle detection feature. We'll cover everything from basic settings checks to more advanced troubleshooting steps, helping you restore this important layer of your security.
## Why Isn't My Camera Detecting Vehicles?
The AI algorithm responsible for vehicle detection is complex. It analyses shapes, sizes, and movement patterns to identify a car, van, or lorry. A failure can occur for several reasons:
- Incorrect Configuration: The feature may simply be turned off or misconfigured in the app settings.
- Poor Camera Placement: The camera's angle, height, and field of view can significantly impact the AI's ability to see and recognise a vehicle.
- Obstructed View: Trees, walls, or even bright sunlight can obscure the view and prevent accurate detection.
- Outdated Firmware: The software on your camera might have a bug that a newer version has fixed.
- Incorrect Detection Zones: The area you've defined for monitoring might not cover the location where vehicles appear.
## A Step-by-Step Guide to Fixing Vehicle Detection
Follow these instructions to get your camera identifying vehicles again.
### Step 1: Check Your In-App Settings
First, let's ensure everything is configured correctly within the Friedland app.
- Enable Vehicle Detection: Navigate to your camera's settings and find the 'Motion Detection' or 'Smart Detection' menu. You should see separate toggles for different types of alerts. Make sure 'Vehicle Detection' is switched on.
- Adjust Smart Detection Sensitivity: Some models may have a separate sensitivity setting for AI detection. If it is set too low, the camera may not be confident enough to classify an object as a vehicle. Try increasing this setting incrementally.
- Review Notification Settings: Double-check that you have enabled push notifications for vehicle alerts. It's possible the camera is detecting them, but the app isn't telling you.
### Step 2: Optimise Camera Positioning and View
The camera's perspective is critical for the AI to work effectively.
- Angle and Height: The ideal position is from a slight height (e.g., first-floor level) and angled downwards. This gives the AI a clear view of the vehicle's shape. A camera positioned too low and straight-on may struggle.
- Clear Line of Sight: Ensure there are no obstructions. Trim back any tree branches or bushes that might block the view of your driveway or the street.
- Lighting Conditions: Very strong backlighting (e.g., pointing directly into the rising or setting sun) can create silhouettes, making it difficult for the AI to identify objects. Likewise, at night, ensure the area is sufficiently illuminated by the camera's infrared LEDs or external lighting.
### Step 3: Redefine Your Motion Detection Zones
An improperly drawn motion zone is a common reason for missed events.
- Cover the Entire Area: Go to the 'Motion Zone' settings. Ensure the grid you have drawn covers the entire path a vehicle would take. This includes the point where it first enters the frame to where it stops.
- Don't Be Too Restrictive: It's better to make the zone slightly larger than necessary than to risk cutting off the area where detection needs to happen.
### Step 4: Update and Reboot
Finally, some simple maintenance can often resolve software glitches.
- Check for Firmware Updates: In the device settings menu of the app, check if a firmware update is available for your camera. These updates often include improvements to the detection algorithms.
- Perform a Power Cycle: Reboot the camera by disconnecting it from its power source for at least 30 seconds. This can clear any temporary errors in its memory and force it to reload the detection software.
By carefully checking your settings, optimising the camera's physical placement, and ensuring your software is up to date, you can significantly improve the reliability of your Friedland camera's vehicle detection.