Drone Detection Masking Area and Sound Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing monitoring systems for pilotless flying objects face challenges in accurately detecting and visualizing the location of pilotless flying objects within an imaging area, as they often misidentify sound sources due to non-directional microphone limitations and struggle to present detailed sound volume information, leading to reduced detection accuracy and user confusion.
Innovation Solution
A monitoring system comprising a camera, microphone array, masking area setter, detector, and signal processor that sets a masking area to exclude unwanted detections, superimposes sound source visual images indicating sound volume on the camera's image, and adjusts threshold settings to enhance detection accuracy and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If audio detection is performed by setting all directions in the monitoring area as a monitoring target, then detection coverage is improved, but detection accuracy deteriorates due to false positives from loud sounds in masking areas
Solution Approach 1:
The monitoring area is segmented into multiple directional regions, with specific masking areas excluded from detection. This allows the system to focus detection resources on relevant directions while ignoring areas with frequent loud sounds that cause false positives, thereby maintaining detection coverage while improving accuracy.
Solution Approach 2:
Different quality settings are applied to different areas of the monitoring zone. Masking areas have detection disabled or reduced sensitivity, while other areas maintain full detection capability. This local differentiation allows the system to prioritize accurate detection in critical areas while tolerating reduced monitoring in areas with persistent noise interference.
2Productivity
If a masking area is set in advance to exclude certain directions, then detection speed is improved, but detection coverage is reduced
Solution Approach 1:
The masking area configuration is made dynamic and adjustable rather than fixed. Users can modify masking area settings based on changing environmental conditions and detection needs, allowing the system to optimize between detection speed and coverage area flexibly depending on operational requirements.
3Loss of information
If sound volume information is displayed without threshold adjustment, then information completeness is improved, but user comprehension deteriorates due to difficulty in ascertaining actual sound volumes
Solution Approach 1:
The system applies parameter transformation by converting raw sound volume data into threshold-adjusted visual representations. By comparing detected sound levels against configurable thresholds and displaying results in standardized visual formats (such as color-coded indicators or relative volume bars), the system preserves complete sound information while making it intuitively comprehensible to users.
Data Source
AI summary
In a pilotless flying object detection system, a masking area setter sets a masking area to be excluded from detection of a pilotless flying object which appears in a captured image of a monitoring area, based on audio collected by a microphone array. An object detector detects the pilotless flying object based on the audio collected by the microphone array and the masking area set by the masking area setter. An output controller superimpose sound source visual information, which indicates the volume of a sound at a sound source position, at the sound source position of the pilotless flying object in the captured image and displays the result on a first monitor in a case where the pilotless flying object is detected in an area other than the masking area.