Acoustic Seat Occupancy Detection Without In-Seat Sensors
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Solution Overview
Problem
Existing seat detection technologies require sensors in each seat, can only detect a single occupied seat, and involve high memory load due to image processing using cameras.
Innovation Solution
An occupied seat detection device using a single set of sensors that includes a transmitter, receiver, and acoustic characteristics analyzer to detect the presence of occupants or seats by analyzing sound characteristics without embedding sensors in each seat and without image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image recognition technology is used to detect seating status, then seating status can be detected, but the system requires high computational resources and processing time
Solution Approach 1:
The system performs preliminary actions by capturing images at specific intervals and pre-processing them to extract relevant features (head position, hair color, clothing color) before full analysis is needed. This allows the system to quickly determine seating status without always requiring complete image recognition processing.
Solution Approach 2:
The invention extracts only the essential features needed for seating detection (head position relative to seat back, hair color, clothing color) from the full image data. By taking out only the relevant information rather than processing entire images, the system achieves accurate detection with reduced computational burden and faster processing.
2Reliability
If multiple cameras are used to improve detection accuracy, then detection reliability increases, but device complexity and cost increase
Solution Approach 1:
The single camera in the system is designed to perform multiple functions: capturing images for seating detection, analyzing head position, determining hair color, identifying clothing color, and inferring student attributes. This multi-functionality achieves reliable detection without requiring multiple specialized cameras, thereby reducing system complexity.
Solution Approach 2:
The system uses an intermediary approach by processing image data through multiple analysis stages (head position detection, color analysis, attribute inference) rather than relying on multiple cameras. This intermediary processing chain achieves comprehensive detection reliability using a single camera system.
Data Source
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AI summary
An occupied seat detection device (10) includes: at least one receiver (12) that is disposed in a space including a plurality of seats and receives at least one of sound generated inside the space or sound generated outside the space; an acoustic characteristics analyzer (13) that calculates, from a signal received by the at least one receiver (12), temporal characteristics or frequency characteristics of the sound in the space; and a detector (14) that detects whether an occupant is present or whether an occupied seat is present inside the space, based on the temporal characteristics or the frequency characteristics calculated by the acoustic characteristics analyzer (13), and outputs a detection result.