Road Surface Sensor Using Electrical Resistance for Ice Detection
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Solution Overview
Problem
Conventional traffic forecasting systems struggle to accurately predict traffic accidents on icy roads and fail to provide timely warnings, especially in high-risk areas like school zones and danger zones, due to limitations in sensing technology and delayed maintenance responses.
Innovation Solution
A traffic forecasting system that combines sensor data for road surface information, weather data, and traffic data to calculate the likelihood of traffic accidents within a specific distance, providing drivers with visual warnings and images corresponding to the accident risk level, using a dew point temperature calculation formula and weight-based risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional microwave or infrared monitoring methods are used to detect road surface state, then the monitoring coverage is broad, but the measurement precision is poor and cannot accurately distinguish between water and ice
Solution Approach 1:
The patent replaces conventional microwave or infrared monitoring methods with a sensor that measures electrical parameters (resistance, voltage, current) of the road surface. This substitution enables precise distinction between water and ice states through electrical property differences, achieving both broad monitoring coverage and high measurement precision simultaneously
Solution Approach 2:
The patent changes the detection parameter from electromagnetic radiation (microwave/infrared) to electrical properties (resistance, voltage, current). By measuring the electrical resistance of the road surface, the system can accurately identify ice formation since ice has different electrical properties compared to water, thus resolving the precision issue while maintaining coverage
2Ease of manufacture
If road managers visit road sites to check the state and perform maintenance, then the maintenance can be performed, but the response time is delayed and cannot check all road sites simultaneously
Solution Approach 1:
The patent implements a self-service monitoring system where sensors automatically detect road surface conditions and transmit data to a control unit. The system autonomously identifies hazardous conditions (ice, water) and triggers alerts without requiring manual road manager intervention for every check, enabling continuous monitoring of all road sites simultaneously and dramatically reducing response time
Solution Approach 2:
The patent establishes a feedback loop where sensor data from road surfaces is continuously transmitted to the control unit, which processes the information and provides real-time feedback about road conditions. This automated feedback mechanism enables immediate detection and response to hazardous conditions, eliminating the time delay inherent in manual inspection methods
3Device complexity
If conventional road forecasting systems are not installed in high-risk areas like school zones and danger zones, then the system complexity is reduced, but the reliability of traffic accident prevention is poor
Solution Approach 1:
The patent applies the local quality principle by enabling selective deployment of the forecasting system in specific high-risk areas such as school zones, silver zones, and danger zones. The system can be installed only where needed based on accident history and risk assessment, providing high reliability in critical locations while avoiding unnecessary complexity in low-risk areas. The control unit can process data from multiple sensors and prioritize alerts based on location importance
Data Source
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AI summary
Disclosed herein is a system of traffic forecasting a system for traffic forecasting which calculates a traffic accident incidence within a specific distance from road surface information sensed through a sensor, weather information and traffic information, thereby informing a driver of traffic accident incidence according to the speed and providing the driver with an image corresponding thereto. The system of traffic forecasting includes a sensor part for sensing at least one of a predetermined first information, a communication part for receiving a second information from at least one of weather related organizations and road traffic related organizations, a memory part for saving a plurality of images which are connected with the traffic accident incidence, a control part for calculating a traffic accident incidence within a specific distance from the system for traffic forecasting using the first and second information, and for determining an image corresponding to the traffic accident incidence from the plurality of images, and a display part for displaying the traffic accident incidence and the image according to the control of the control part.