Passenger Motion Sickness Estimation Using Multi-Sensor Detection
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Solution Overview
Problem
Existing travel sickness estimation systems fail to accurately predict the onset of travel sickness in individuals, potentially triggering the condition in passengers who do not show initial symptoms, and lack personalized prevention measures.
Innovation Solution
A travel sickness estimation system that uses a combination of sensors (acceleration, angular velocity, odor, pressure, camera, infrared, millimeter wave, terahertz wave, and breath sensors) to assess passenger conditions and vehicle information, predicting the likelihood of travel sickness onset and providing personalized prevention strategies through adjustments to the vehicle environment and passenger comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a motion sickness reduction apparatus induces quasi-driver head motion to all passengers regardless of their current state, then passengers showing signs of motion sickness may receive relief, but passengers without symptoms may trigger the onset of motion sickness
Solution Approach 1:
The system performs preliminary detection of motion sickness symptoms using multiple sensors (acceleration sensors, angular velocity sensors, odor sensors, pressure sensors, cameras, infrared sensors, millimeter wave sensors, terahertz wave sensors, and breath sensors) before applying countermeasures. This allows the system to identify which passengers actually need intervention and apply quasi-driver head motion only to them, avoiding triggering motion sickness in healthy passengers while still providing relief to those showing symptoms
Solution Approach 2:
The system continuously monitors passenger conditions using multiple sensors and adjusts the application of quasi-driver head motion based on real-time feedback. The estimation unit processes sensor data to determine the likelihood of motion sickness onset, and the notification unit provides feedback to passengers about their motion sickness risk level, allowing dynamic adjustment of prevention measures
2Measurement precision
If multiple types of sensors are used to accurately detect passenger conditions, then the precision of motion sickness estimation is improved, but the complexity of the system increases
Solution Approach 1:
The system employs multiple types of sensors (acceleration, angular velocity, odor, pressure, camera, infrared, millimeter wave, terahertz wave, and breath sensors) that can detect various physiological and environmental parameters. Each sensor serves multiple functions in comprehensive passenger monitoring, and the estimation unit integrates data from all sensors to provide a unified motion sickness risk assessment, reducing the need for separate specialized systems
Solution Approach 2:
The patent combines multiple sensor types and their detection functions into a single integrated estimation unit that processes all sensor data together. The notification unit also integrates information from multiple sources to provide unified feedback to passengers. This merging approach simplifies the overall system architecture despite using diverse sensor technologies
Data Source
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AI summary
The problem to be solved is to provide a travel sickness estimation system, a moving vehicle, a travel sickness estimation method, and a travel sickness estimation program, all of which are configured or designed to reduce the chances of triggering the onset of travel sickness. A travel sickness estimation system (10) includes an estimation unit (312) and an output unit (313). The estimation unit (312) is configured to perform estimation processing of estimating, based on person information indicating conditions of a person who is on board a moving vehicle, whether or not the person is in circumstances that would cause travel sickness for him or her. The output unit (313) is configured to output a result of the estimation processing performed by the estimation unit (312).