Emotion-Based Vehicle Service System for Safe Driving
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Solution Overview
Problem
Current vehicle technologies lack the capability to automatically recognize and respond to a driver's emotions and vehicle conditions to prevent dangerous or criminal situations such as drunk driving, reckless driving, and drowsy driving, which are increasingly becoming social issues.
Innovation Solution
An emotion-based vehicle service system that utilizes a multi-emotion sensor node and emotion cognition processing apparatus to analyze bio and environmental signals from drivers and passengers, providing a safe driving service by controlling vehicle functions based on recognized emotions and conditions, including heart rate, skin reaction, voice, and vehicle parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If emotion cognition processing apparatus and multi-emotion sensor nodes are added to detect driver emotions and vehicle conditions, then safe driving service capability is improved, but device complexity increases
Solution Approach 1:
The system divides the vehicle into multiple sensor nodes (handle sensor node, driver seat sensor node, passenger seat sensor node, transmission sensor node, ceiling sensor node, front glass sensor node), each equipped with specific sensors to detect local conditions. This segmentation allows comprehensive emotion and condition detection while distributing system complexity across modular components.
Solution Approach 2:
The emotion cognition processing apparatus serves multiple functions: it processes data from various sensor types (heart rate sensor, skin reaction sensor, body temperature sensor, voice sensor, image sensor, acceleration sensor, slope sensor), analyzes both driver emotions and vehicle conditions, and generates comprehensive safe driving services. This multi-functionality consolidates diverse detection capabilities into a single processing unit.
2Measurement precision
If multiple sensors are integrated in each sensor node to detect various bio signals and vehicle parameters, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Different sensor types are grouped into specific sensor nodes based on their functional relationships. For example, bio sensors (heart rate, skin reaction, body temperature) are integrated into the driver seat sensor node, while vehicle condition sensors (acceleration, slope) are placed in the transmission sensor node. This segmentation organizes complexity while maintaining comprehensive detection precision.
Solution Approach 2:
Multiple sensors are merged within each sensor node to detect various parameters simultaneously. Each sensor node combines relevant sensors (e.g., handle sensor node may include voice sensor and image sensor) to create integrated detection units that reduce overall system complexity while maintaining high measurement precision through multi-parameter monitoring.
3Speed
If real-time emotion cognition and vehicle condition analysis are performed, then response speed for preventing dangerous situations is improved, but use of energy increases
Solution Approach 1:
The system continuously monitors driver emotions and vehicle conditions in real-time, performing preliminary detection and analysis before dangerous situations develop. By maintaining constant readiness through ongoing data collection from all sensor nodes, the system can respond immediately when threshold violations or dangerous patterns are detected, achieving fast response without requiring intensive processing only during critical events.
Solution Approach 2:
The emotion cognition processing apparatus performs periodic analysis of sensor data at optimized intervals, continuously monitoring driver state and vehicle conditions. This periodic processing approach balances real-time response requirements with energy efficiency by updating analyses at appropriate frequencies rather than continuously processing all sensor streams at maximum rate.
Data Source
AI summary
An emotion-based vehicle service system for safe driving includes a multi-emotion sensor node configured to sense emotion information of a driver and passenger in a vehicle and condition information of the vehicle. The emotion-based vehicle service system further includes an emotion cognition processing apparatus configured to analyze sensing information provided from the multi-emotion sensor node to generate emotion cognition information, and a safe driving service apparatus configured to provide an emotion-based safe driving service depending on the emotion cognition information.