Drowsiness Estimation Using Camera and Room Environment Sensors
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Solution Overview
Problem
Existing drowsiness estimation techniques fail to accurately determine a user's drowsiness condition due to factors beyond fatigue, such as room environment, and struggle to account for individual differences in age and sex.
Innovation Solution
A drowsiness estimation device incorporating an imager, sensor, and estimator that takes images of users and senses room environment information, including CO2 concentration and temperature, to accurately estimate drowsiness, while also considering user age and sex, and adjusts air-conditioning operations to improve estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only camera and handle movement are used for drowsiness detection, then the device complexity is low, but the measurement precision of drowsiness condition is insufficient
Solution Approach 1:
The patent combines multiple detection methods (camera-based facial analysis, handle movement detection, CO2 concentration sensing, and temperature measurement) into a unified drowsiness estimation system. The estimator integrates data from all these sources to comprehensively determine drowsiness conditions, resolving the contradiction by merging simple individual sensors into a complex but accurate system.
Solution Approach 2:
The camera serves multiple functions: capturing facial images for drowsiness analysis, determining user age and sex, and monitoring user presence. The air conditioner unit integrates drowsiness estimation, environmental sensing, and climate control functions. This multi-functionality improves measurement precision without proportionally increasing device complexity.
2Measurement precision
If room environment information is added to drowsiness estimation, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The drowsiness estimation system is segmented into independent functional modules: facial image acquisition, handle movement detection, CO2 concentration sensing, temperature measurement, and integrated estimation. Each module operates independently and feeds data to the estimator, allowing the system to achieve high precision while managing complexity through modular architecture.
Solution Approach 2:
The estimator acts as an intermediary that processes and integrates data from multiple sensors (camera, handle sensor, CO2 sensor, temperature sensor) to produce a unified drowsiness assessment. This intermediary component coordinates the information flow between diverse sensors, improving overall measurement precision while managing system complexity through centralized data fusion.
3Measurement precision
If user age and sex are determined from image to improve drowsiness estimation, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The camera and image processing system serve multiple purposes: detecting facial expressions for drowsiness analysis, determining user age, and identifying user sex. By making the image processing system multi-functional, the patent improves drowsiness estimation accuracy (by incorporating age and sex factors) without requiring separate dedicated sensors for each measurement, thus managing device complexity.
4Measurement precision
If multiple sensors and processing functions are added, then the measurement precision of drowsiness condition improves, but the ease of operation decreases
Solution Approach 1:
The air conditioner system automatically performs drowsiness estimation and adjusts operating parameters without requiring user input or intervention. The camera continuously monitors facial expressions, the CO2 sensor tracks air quality, and the estimator automatically determines drowsiness conditions, allowing the system to self-adjust based on detected user states, thereby maintaining ease of operation despite increased measurement precision capabilities.
Data Source
AI summary
A camera (26) takes an image of at least one user (U1, U2, U3). A room environment information sensor (13) senses room environment information relating to an environment of a room (r1) in which the at least one user (U1, U2, U3) is present. The estimator (66) estimates a drowsiness condition of the at least one user (U1, U2, U3) based on the image of the at least one user (U1, U2, U3) taken by the camera (26) and the room environment information sensed by the room environment information sensor (13).