Smart Mobility Risk Control Using GPS and Camera Obstacle Detection
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Solution Overview
Problem
Conventional smart mobility systems rely on user-dependent obstacle detection, which can lead to accidents when users are distracted or fail to respond promptly to warnings.
Innovation Solution
A system and method that utilize a GPS and a camera sensor to classify risk levels and control smart mobility, providing auditory feedback at lower risk levels, tactile feedback at moderate levels, and active control, including deceleration or braking, at higher risk levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If obstacle detection device outputs alarm sound and obstacle information through user's smart device, then user can control traveling direction and speed to prevent accidents, but user's cognitive ability or attention reduction leads to accidents despite alarm sound
Solution Approach 1:
The smart mobility device automatically detects obstacles using its mounted camera sensor and generates alarm sounds without requiring the user to actively monitor the environment or smartphone information. The system serves itself by autonomously detecting risks and warning the user, eliminating the need for continuous user attention and cognitive processing of obstacle information.
Solution Approach 2:
The system provides real-time feedback to the user through alarm sounds when obstacles are detected by the device's own sensors. This closed-loop feedback mechanism allows the device to monitor its environment continuously and immediately alert the user to dangers, removing the burden of environmental monitoring from the user while maintaining high accident prevention reliability.
2Reliability
If user relies on cognitive ability to respond to obstacle alarm, then user can control traveling to prevent accidents, but reduced attention leads to serious injury
Solution Approach 1:
The device performs the information processing function itself by using its onboard camera sensor to detect obstacles and determine their nature. Instead of requiring the user to cognitively process visual information and make judgments, the device autonomously analyzes the environment and translates it into actionable alarm signals, eliminating the loss of information through reduced user cognitive processing.
3Loss of information
If limited notification method is used through smart device, then obstacle information can be conveyed, but risky situation occurs when user is not looking ahead
Solution Approach 1:
The system implements continuous environmental feedback through the mounted camera sensor, automatically detecting obstacles and providing real-time alarm warnings. This eliminates the need for the user to actively look ahead or check smartphone information, as the device continuously monitors the environment and provides reliable safety warnings regardless of the user's attention state.
Data Source
AI summary
A system for controlling a smart mobility by risk level includes: an information collection unit to collect position and speed information of the smart mobility and camera sensing information including a front traffic sign or object; a front detection unit to detect a front obstacle or inclination using the camera sensing information and to output a detection result; a control unit to change a warning to a user and/or a method of controlling the smart mobility by risk level based on the information collected by the information collection unit and the detection result; and a warning unit to warn the user by changing a method by risk level under the control of the control unit.