Laser Scan Sensor Intruder Detection False Alarm Reduction
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Solution Overview
Problem
Existing laser scan sensors fail to accurately detect intruders in surveillance areas when harmless objects like automobiles or obstacles are introduced, leading to continuous false detection and inefficiencies in high-traffic areas or during renovations.
Innovation Solution
A laser scan sensor configuration that includes a laser range finder, scanning mechanism, distance-information acquiring unit, installation-state storage, detection area-information storage, human-body determining unit, and alert-signal output unit, which updates detection area information based on installation state and movement analysis to differentiate between intruders and non-intruder objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the laser scan sensor continuously monitors the surveillance area, then intruder detection capability is improved, but false detection increases when harmless objects like automobiles or obstacles are present
Solution Approach 1:
The sensor dynamically updates the detection area information to adapt to changes in the surveillance environment. When objects like automobiles are parked or obstacles are installed, the system learns and adapts to these new conditions, adjusting the detection parameters accordingly. This dynamic adaptation allows the system to maintain high intruder detection accuracy while reducing false alarms from stationary harmless objects.
Solution Approach 2:
The system changes detection parameters based on the presence and characteristics of objects in the surveillance area. By analyzing the reflection time, position, and movement patterns of detected objects, the system adjusts detection thresholds and parameters to distinguish between intruders and harmless objects, thereby reducing false detection while maintaining reliable intruder detection.
2Measurement precision
If the sensor detects all moving objects, then detection sensitivity is improved, but false alarms increase in high-traffic areas
Solution Approach 1:
The system applies different detection criteria and sensitivity levels to different regions and object types within the surveillance area. By analyzing the specific characteristics (reflection time, position, movement pattern) of each detected object, the system locally adjusts detection parameters to maintain high sensitivity for potential intruders while tolerating normal traffic patterns in high-traffic areas, thus reducing false alarms without compromising detection precision.
3Stability of the object's composition
If the detection area is fixed after initial setup, then system stability is improved, but adaptability to environmental changes deteriorates
Solution Approach 1:
The detection area is implemented as a dynamic rather than static configuration. The system continuously monitors the surveillance environment and automatically updates the detection area information when changes are detected, such as new obstacles or permanent objects. This dynamic approach maintains system stability for normal operation while adapting to environmental changes, resolving the contradiction between fixed detection areas and environmental adaptability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The sensor accurately detects intruders while minimizing false alarms by updating detection area information and distinguishing between human bodies and other objects, even in dynamic environments like high-traffic areas or during changes in the surveillance area.
Implementation Method 1
a laser range finder configured to measure a distance to an object based on a time after a laser beam emits before a reflected light returns from the object present in a direction of the emission
Data Source
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AI summary
The configuration includes a laser range finder (110), a scan mechanism (120), a distance-data acquiring unit (130), a memory (160), which stores installation state information and detection-area information for each measurement direction, a human-body determining unit (140), a detection area-information updater (140), which updates detection-area information under a predetermined condition, and the alert-output control unit (150). The human-body determining unit (140) extracts a portion that possibly corresponds to a human body in an object that has invaded or moved, which is found out by comparison with the detection-area information based on the acquired distance information, and determines whether or not a rest of the respective extracted portions is a human body based on a movement state of each of the extracted portion in chronological order. The rest of the extracted portions excludes the extracted portions where a movement distance within a predetermined time is within a predetermined distance.