Brain Wave Image Generation for Autonomous Mobility Control
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Solution Overview
Problem
Current mobility systems lack the ability to autonomously determine and respond to a passenger's intentions for services or items based on brain wave signals, limiting their ability to provide personalized and efficient route changes or order placement during travel.
Innovation Solution
A method and apparatus that utilize brain wave signals collected from passengers to generate images using an artificial intelligence model, such as a generative adversarial network (GAN), to select and control mobility routes or order items from service points, by matching the generated images to predetermined lists of service points or items, and transmitting relevant information or orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If brain wave signals are collected and processed using AI models to generate images, then the ability to autonomously determine passenger intentions is improved, but the device complexity increases
Solution Approach 1:
The patent introduces an artificial intelligence model as an intermediary component that translates complex brain wave signals into interpretable images representing passenger intentions. This intermediary AI layer bridges the gap between raw neural signals and actionable intent recognition, enabling autonomous determination without requiring the control system to directly interpret complex physiological data
Solution Approach 2:
The patent replaces traditional mechanical or manual control interfaces with a brain-computer interface system that uses neural signals and AI processing. This substitution eliminates the need for physical interaction (steering, buttons, voice commands) and enables direct mind-to-vehicle control, significantly improving automation extent while the AI handles the complexity of signal processing
2Speed
If brain wave signals are processed in real-time to generate images, then the response speed to passenger needs is improved, but the energy consumption increases
Solution Approach 1:
The patent performs preliminary processing of brain wave signals by converting them into image representations using AI models before further analysis. This preliminary transformation organizes the data in a more efficient format that enables faster subsequent processing and decision-making, improving response speed while the AI optimization manages energy consumption during the conversion process
3Measurement precision
If multiple channels of brain wave signals are collected, then the precision of intention recognition is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent creates visual image copies or representations of the multi-channel brain wave signals through AI processing. Instead of directly analyzing complex multi-dimensional neural data, the system generates simplified image representations that preserve the essential intent information while being much easier to detect, measure, and interpret, thereby reducing measurement difficulty while maintaining recognition precision
Data Source
AI summary
An apparatus for generating an image using brain wave signals includes a sensor configured to collect brain wave signals of at least one passenger in a mobility from a plurality of channels for a predetermined time, and a controller configured to generate a first image from the brain wave signals collected from the plurality of channels using an artificial intelligence model, to select at least one second image included in a predetermined list based on the generated first image, and to control the mobility as a response to the selected second image.