Optical Rain Gauge Using AI Imaging to Avoid Clogging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing meteorological measurement devices require maintenance due to mechanical mechanisms, are prone to clogging from debris, and inaccurately measure precipitation due to evaporation or obstruction of detection units.
Innovation Solution
A maintenance-free device with a housing that uses a light source and imaging device to capture images of falling droplets, employing machine learning to estimate precipitation amounts based on detected images, without mechanical parts and clogging risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a mechanical mechanism with movable parts is used to measure precipitation, then the device can physically collect and measure rainwater, but maintenance is required and reliability decreases
Solution Approach 1:
The patent replaces the mechanical tipping bucket mechanism with an optical detection system. A light source irradiates the interior space, and an imaging device captures images of raindrops blocking the light. Machine learning algorithms then estimate precipitation amounts from these images, eliminating all movable mechanical parts and their associated maintenance requirements.
Solution Approach 2:
Instead of physically collecting and measuring rainwater with mechanical components, the patent creates optical copies (images) of raindrops as they fall through the illuminated space. These image copies are then processed by machine learning algorithms to determine precipitation amounts, replacing the need for physical mechanical measurement.
2Measurement precision
If a detection unit is designed to detect dripping rainwater, then precipitation can be measured, but the unit becomes clogged with leaves or debris obstructing detection
Solution Approach 1:
The patent replaces the physical drip section and mechanical detection unit with an optical detection system. Light irradiates the falling raindrops, and an imaging device captures their images. This optical approach eliminates the drip section that would otherwise collect leaves and debris, preventing clogging while maintaining detection accuracy.
Solution Approach 2:
The patent extracts the detection function from the physical water collection path. Instead of detecting rainwater after it drips through a vulnerable drip section, the system detects raindrops in mid-fall through optical imaging. This separates the detection function from the water collection path, eliminating the clogging problem at the drip section.
3Measurement precision
If the detection unit detects raindrops in a drip section, then precipitation measurement is possible, but small raindrops evaporate before detection
Solution Approach 1:
The patent performs detection before the raindrops reach the drip section where evaporation would occur. By capturing images of raindrops in mid-fall through the illuminated space, the system records precipitation data before the drops can evaporate, ensuring accurate measurement of even small raindrops.
Solution Approach 2:
The patent replaces the drip section detection method with optical imaging of falling raindrops. This substitution allows detection to occur throughout the fall path rather than at a single point where evaporation is problematic, preventing loss of small raindrops through evaporation before measurement.
4Adaptability or versatility
If an arm member with light-emitting and light-receiving mechanisms is rotatably supported, then the device can track precipitation, but mechanical complexity increases requiring maintenance
Solution Approach 1:
The patent replaces the rotatable arm member mechanism with a stationary housing containing the light source and imaging device. The optical system captures precipitation data from a fixed position, eliminating mechanical complexity while maintaining the ability to track and measure precipitation through continuous optical monitoring.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurate estimation of precipitation without maintenance needs, avoiding clogging and evaporation issues, and improved measurement accuracy through machine learning.
Implementation Method 1
detect an image of rain, snow, or fog droplets falling through the space via the top and blocking the light radiated from the light source
Data Source
AI summary
A maintenance-free meteorological measurement device that can accurately estimate the amount of falling rain, snow, or fog droplets without becoming clogged with debris or evaporation of water. A rain gauge includes a light guide plate and an infrared camera in a housing, and an AI computer that is an information processing device. The housing has a rectangular parallelepiped shape with an open top and an open bottom. The light guide plate unit is mounted on one side surface of the housing. The light guide plate unit includes an LED, a light guide plate, and a diffusion plate housed in a unit case. The infrared camera is on the other side surface of the housing that faces the one side surface across a space. The AI computer detects images of raindrops and estimates the amount of rainfall from the images of the raindrops using machine learning.