IP Camera Earthquake Detection via Visual Coupling Correction
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Solution Overview
Problem
Current earthquake detection systems lack real-time intensity measurement capabilities, relying on post-event questionnaires and arbitrary intensity scales, which hinders early warning systems and evacuation planning, while magnitude detection is not directly related to the effects of an earthquake on the surface.
Innovation Solution
A computer-implemented method using a network of IP cameras to detect abnormal shaking by processing visual inputs, applying coupling corrections, and employing AI models to infer earthquake location, magnitude, depth, and intensity through spectral analysis and pixel-wise changes, enabling real-time intensity assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional seismographs are used for magnitude detection, then detection capability is provided, but cost and device complexity increase
Solution Approach 1:
The patent uses visual copies from cameras instead of physical seismographs. Cameras capture images that are processed to detect earthquake effects, replacing the need for expensive seismograph hardware with more affordable camera systems that can be deployed in similar densities.
Solution Approach 2:
The patent replaces mechanical seismograph systems with an optical/electronic system. Instead of using mechanical sensors to detect ground motion, the system uses cameras to capture visual information and processes this data through algorithms to infer earthquake characteristics, substituting mechanical measurement with optical detection and computational analysis.
2Measurement precision
If post-event questionnaires are used for intensity measurement, then intensity data is collected, but real-time capability and response time are lost
Solution Approach 1:
The system performs preliminary actions by continuously monitoring camera feeds and processing visual data in real-time during the earthquake event. Instead of waiting for post-event questionnaires, the system proactively detects and measures intensity parameters during the ongoing seismic event, enabling immediate response.
Solution Approach 2:
The patent maintains continuous monitoring and processing of visual data throughout the earthquake event. The system continuously analyzes camera images to track intensity changes in real-time, ensuring that intensity measurement is an ongoing process rather than a one-time post-event survey, thus eliminating time delays.
3Measurement precision
If magnitude is used to characterize earthquakes, then energy release is quantified, but relationship to surface effects is indirect and inaccurate
Solution Approach 1:
The system uses feedback from visual observations to directly measure intensity parameters. By continuously analyzing camera data to observe actual surface effects such as shaking, damage, and environmental impacts, the system obtains direct feedback about earthquake effects, creating a closed-loop measurement system that directly correlates with real-world impacts rather than relying on indirect magnitude calculations.
Data Source
AI summary
From each of a plurality of cameras, a visual input of a location is received over a network. For each visual input from the plurality of cameras, a coupling correction is performed between a shaking of the camera with respect to the visual input by subtracting velocity vectors of the plurality of cameras from velocity vectors of pixels defining the visual input to provide a processed input. It is determined whether a shaking identified in the processed input is above a predetermined threshold based on the processed input, thereby detecting one or more anomalies. From the one or more anomalies, at least one of a location, magnitude, or depth of an earthquake are inferred based on the shaking identified in the processed input of each of the plurality of cameras.