Camera-Based Fog Droplet Detection and Characterization
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Solution Overview
Problem
Existing methods for detecting fog and calculating fog characteristics are expensive, difficult to install, and maintain, and lack cost-effective solutions for real-time monitoring and data generation.
Innovation Solution
A method using a digital camera and optical lens to capture fog images, convert them to grayscale, binarize, filter, and calculate fog droplet characteristics such as size, number, and visibility, generating time-series data at low costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive specialized fog observation equipment (e.g., DMT's FM-120) is used, then fog detection accuracy and characteristic analysis capability are improved, but device cost and installation complexity increase significantly
Solution Approach 1:
The patent uses a digital camera to capture images of fog droplets, creating a visual copy of the fog structure that can be analyzed through image processing. This replaces the need for complex specialized sensors while maintaining measurement capability through photographic documentation of droplet characteristics
Solution Approach 2:
The patent replaces complex mechanical fog observation equipment with an optical system (camera and lens) combined with digital image processing. The mechanical complexity of specialized fog instruments is substituted by a simpler optical-mechanical system paired with computational analysis of captured images
2Measurement precision
If specialized fog observation equipment is deployed, then fog characteristic analysis capability is improved, but equipment cost increases to several tens or hundreds of million won
Solution Approach 1:
The patent employs inexpensive digital cameras and standard optical lenses instead of expensive specialized fog observation equipment. These common, affordable components are used to achieve fog detection and characterization, dramatically reducing the cost from tens or hundreds of million won to a fraction of that amount while maintaining functional capability
3Reliability
If existing fog detection methods are used, then fog monitoring is achieved, but real-time processing speed and responsiveness are limited
Solution Approach 1:
The system captures images at regular intervals and processes them through automated image analysis algorithms. This periodic capture and processing enables real-time monitoring capabilities, with the frequency of image capture and processing cycles determining the responsiveness of fog detection and characteristic analysis
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
Enables real-time identification and monitoring of fog characteristics, providing accurate and timely weather information and services without the need for expensive equipment.
Implementation Method 1
set a digital camera and an optical lens at magnification capable of identifying fog droplets
Data Source
AI summary
Provided is a method for detecting fog droplets and calculating fog characteristics based on camera images, which can set a digital camera and an optical lens at magnification capable of identifying fog droplets, thereby detecting fog droplets from photographed images and calculating various characteristics related to fog.