Biometric Route Optimization for Passenger Stress Reduction
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Solution Overview
Problem
Current electronic mapping programs fail to account for a person's sense of urgency, personality, and stress levels when determining travel routes, leading to inadequate timing and route optimization for passengers.
Innovation Solution
A system that uses biometric sensors and IoT devices to monitor real-time emotional states of passengers, integrating this data with historical driving habits and environmental conditions to generate personalized travel routes that minimize stress and ensure timely arrival.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional electronic mapping programs are used to determine travel routes, then the routing process is simple and fast, but the routes do not account for passenger stress levels, personality, or sense of urgency resulting in inadequate optimization
Solution Approach 1:
The system segments the route optimization process into multiple independent modules: biometric data collection module, emotional state analysis module, personal profile generation module, and dynamic route planning module. Each module handles a specific aspect of the optimization process, allowing the system to process complex passenger-specific data without overwhelming computational burden.
Solution Approach 2:
The system performs preliminary actions by collecting biometric data and generating personal profiles for passengers before the actual travel begins. This advance preparation allows the system to have pre-computed stress sensitivity information and personality characteristics ready, enabling faster real-time route adjustments during travel without adding complexity to the core routing algorithm.
2Measurement precision
If biometric sensors and real-time monitoring are implemented to track emotional states, then personalized stress-reducing routes can be generated, but the device complexity and data processing requirements increase
Solution Approach 1:
The biometric sensor system is designed with multi-functionality to detect multiple physiological parameters (heart rate, skin conductance, respiratory rate, temperature) simultaneously using a single integrated sensor platform. This universal approach allows the system to infer various emotional states from multiple data streams without requiring separate specialized sensors for each parameter, thereby reducing overall device complexity while maintaining high measurement precision.
Solution Approach 2:
The system introduces an intermediary layer of emotional state inference algorithms that translate raw biometric sensor data into meaningful emotional indicators. This intermediary processing layer filters and interprets complex physiological signals, converting them into simplified stress level metrics that can be directly used for route optimization without requiring the full complexity of raw biometric data processing.
3Productivity
If dynamic route adjustments are made based on real-time stress levels, then passenger stress is reduced and arrival timing is optimized, but the computational load and processing time increase
Solution Approach 1:
The system implements periodic action by updating the travel route at predetermined intervals (e.g., every 5 minutes or at major decision points) rather than continuously adjusting based on every fluctuation in stress levels. This periodic update mechanism maintains travel efficiency by making necessary route adjustments while avoiding the excessive computational energy consumption that would result from continuous real-time recalculation at every moment of the journey.
Solution Approach 2:
The system employs feedback mechanisms where biometric data is continuously monitored and fed back to adjust route parameters incrementally rather than making large computational leaps. The feedback loop compares current stress levels against target thresholds and makes small, energy-efficient adjustments to the route, maintaining productivity while minimizing computational energy consumption through gradual optimization rather than exhaustive recalculation.
Data Source
AI summary
One or more processors identify an occupant of a passenger vehicle, and then receive biometric sensor readings from a biometric sensor that is monitoring the occupant in real time, where the biometric sensor readings indicate a real-time emotional state of the occupant. The processor(s) generate a personal profile for the occupant of the passenger vehicle based on the biometric sensor readings. The processor(s) receive a desired destination and travel schedule for the occupant of the passenger vehicle, as well as environmental sensor readings indicating a real-time environmental state of the passenger vehicle. The processor(s) then create a travel route for the passenger vehicle based on the biometric sensor readings, the personal profile of the vehicle occupant, the desired destination and travel schedule, and the real-time environmental state of the passenger vehicle. One or more processors then transmit, to the passenger vehicle, directions for the travel route.