Crowdsourced Flood Data Distribution via GIS and Cloud Network
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Solution Overview
Problem
Current emergency alert systems are ineffective in providing real-time and accurate flood data at a local level, leading to user alert fatigue, communication disparities, and data deficiency, which results in inadequate flash flood warnings and inability to predict small yet intense floods.
Innovation Solution
A system and method for collecting and distributing user-reported flood data in real-time using a user interface and a central cloud network, incorporating a GIS database and notification trigger system, allowing users to report and view flood data, and receive location-specific alerts, enhancing existing flood prediction systems with crowdsourced data and image verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical systems couple meteorological data, overland physical parameters and underground flowage systems for flood prediction, then comprehensive flood modeling is achieved, but the system complexity and computational requirements increase significantly
Solution Approach 1:
The patent segments the flood prediction system into multiple independent modules: physical flood modeling components, semi-physical cell computation components, image processing components for analyzing satellite/radar/CCTV images, and crowdsourced data collection components. Each module processes specific types of data independently and contributes to the overall flood assessment, reducing system complexity while maintaining comprehensive modeling capability.
Solution Approach 2:
The patent merges multiple data sources and prediction methods into a unified flood prediction system. It combines physical model outputs, semi-physical cell computation results, image processing analysis, and crowdsourced real-time observations into an integrated framework that produces comprehensive flood predictions, achieving high accuracy without requiring any single component to be overly complex.
2Productivity
If crowdsourced data is collected through mobile applications for real-time flood information, then data availability and response time improve, but data quality control and verification become more difficult
Solution Approach 1:
The patent implements feedback mechanisms where crowdsourced flood reports are verified through multiple channels including image processing analysis of uploaded photos/videos, cross-validation with physical and semi-physical model predictions, and comparison with data from other crowd users in the same area. This feedback loop ensures data quality control while maintaining rapid data collection capabilities.
Solution Approach 2:
The patent introduces intermediary verification layers between crowdsourced data submission and final flood prediction output. Image processing algorithms act as intermediaries to automatically verify uploaded visual evidence, while the integrated prediction system serves as an intermediary that reconciles crowdsourced observations with scientific model predictions, ensuring data accuracy without slowing down collection.
3Area of stationary object
If traditional emergency alert systems broadcast flood warnings to wide areas, then coverage is maximized, but alert fatigue increases and message relevance decreases
Solution Approach 1:
The patent applies local quality by segmenting flood alerts into location-specific warnings based on precise flood risk modeling. Instead of broadcasting uniform alerts to entire regions, the system generates customized alerts for specific neighborhoods, streets, or buildings based on their individual flood vulnerability assessments from physical models, real-time observations, and historical data, thereby maximizing relevance and reducing alert fatigue.
Solution Approach 2:
The patent implements dynamic alert generation that adapts to changing flood conditions in real-time. As the flood situation evolves, the system dynamically updates which areas receive alerts and modifies alert content based on current water levels, flood velocity predictions, and real-time crowd observations, ensuring alerts remain accurate and relevant throughout the flood event lifecycle.
4Loss of time
If image processing methods use continuous input of real-time satellite or radar images for flood detection, then real-time monitoring capability is achieved, but data processing time and computational resources increase
Solution Approach 1:
The patent implements periodic image processing where satellite and radar images are analyzed at optimized intervals rather than continuously. The system determines appropriate processing frequencies based on flood development stage, historical data patterns, and current model predictions, processing images more frequently during rapid flood development and less frequently during stable conditions, thereby reducing computational resource consumption while maintaining real-time detection capability.
Data Source
AI summary
A method and system for a weather distribution adapted to collect, analyze and distribute user reported flood data, including a user interface adapted for a user to report flood data, receive a flood alert and view displayed analyzed reported flood data relevant to the user, and a central cloud network adapted to collect, analyze, and distribute the reported flood data to the user, the central cloud network including a report handler, wherein the report handler collects the reported flood data, analyzes the reported flood data and distributes the analyzed reported flood data to a memory database and a geographic information system (“GIS”) database, the memory database, wherein the memory database stores user information and locations, the GIS database, wherein the GIS database records the analyzed reported flood data, a notification trigger system, wherein the notification trigger system sends the user the flood alert and displays the analyzed reported flood data based on a user location, wherein the automatic updates display reported flood data in real-time.