Passing Vehicle Filter for A/V Devices
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Solution Overview
Problem
Current audio/video recording and communication devices, such as doorbells, often generate false alarms due to motion caused by passing vehicles, leading to alert fatigue and reduced effectiveness in detecting actual threats.
Innovation Solution
The implementation of a passing vehicle filter system that uses a camera and processing module to detect motion, assign object IDs, determine speed, direction, and aspect ratio, and filter out passing vehicles by analyzing these parameters to differentiate them from potential threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motion detection is used to alert users of potential threats, then security monitoring capability is improved, but false alarms increase due to passing vehicles
Solution Approach 1:
The system changes multiple parameters simultaneously to identify passing vehicles: speed threshold (vehicles move faster than pedestrians), aspect ratio (vehicles have wider-than-tall proportions), and movement pattern (vehicles follow road alignments). By requiring all parameters to match vehicle characteristics, the system reliably distinguishes vehicles from threats while minimizing false alarms.
Solution Approach 2:
The system introduces an intermediate classification step between motion detection and alert generation. The processor acts as a mediator that analyzes captured images to determine object type (vehicle vs. pedestrian) before triggering alerts, thereby filtering out benign vehicle motion while maintaining sensitivity to actual threats.
2Measurement precision
If alerts are generated for all detected motion, then threat detection sensitivity is improved, but alert fatigue occurs due to persistent false alarms
Solution Approach 1:
The system maintains high detection sensitivity by continuously monitoring all motion while applying parameter-based filtering. It uses aspect ratio, speed, and movement pattern parameters to selectively suppress alerts only for vehicle-like objects, preserving user responsiveness to actual threats while eliminating alert fatigue from vehicle-related false alarms.
Solution Approach 2:
The system implements feedback by analyzing the characteristics of each detected object and adjusting alert generation accordingly. When objects match vehicle parameters, the system feedback-suppresses alerts; when objects differ from vehicle characteristics, full alert sensitivity is maintained, creating a dynamic response system that adapts to different threat types.
3Reliability
If video footage is streamed for all motion events, then monitoring completeness is improved, but bandwidth and storage consumption increase due to benign vehicle motion
Solution Approach 1:
The system uses parameter-based classification (speed, aspect ratio, movement pattern) to determine whether to stream video footage. By identifying vehicles through these parameters, the system suppresses video streaming for vehicle-related events while maintaining complete monitoring and streaming capability for non-vehicle threats, significantly reducing bandwidth and storage consumption.
Solution Approach 2:
The system extracts and removes benign vehicle motion events from the video streaming workflow. By separating vehicle detection from general motion detection using parameter analysis, the system extracts only the harmful subset (vehicle-related footage) and excludes it from streaming, while preserving complete monitoring capability for all other events.
4Measurement precision
If the system analyzes multiple object parameters (speed, aspect ratio, movement pattern), then vehicle identification accuracy is improved, but processing complexity increases
Solution Approach 1:
The system analyzes multiple parameters (speed, aspect ratio, movement pattern) simultaneously to achieve high vehicle identification accuracy. The processor evaluates all parameters together to determine whether an object is a vehicle, with all parameters needing to match vehicle characteristics for suppression to occur. This multi-parameter approach maximizes identification accuracy while the integrated processing methodology manages computational complexity.
Data Source
AI summary
Passing vehicle filters for audio/video (A/V) recording and communication devices in accordance with various embodiments of the present disclosure are provided. In one embodiment, an A/V recording and communication device is provided, the device comprising a camera configured to capture image data of an object within a field of view of the camera, wherein the field of view comprises at least one active motion zone; a communication module; and a processing module comprising: a processor; and a motion detection application that configures the processor to: detect motion of the object within the field of view; capture image data; assign an object ID; determine a speed and a direction of movement; determine an aspect ratio; create an object boundary and determine a distance between a center of the object boundary and the at least one active motion zone; and determine whether the object is a passing vehicle.