Mobile App for Cyanobacteria Assessment via Satellite Data
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Solution Overview
Problem
Current methods for monitoring harmful algal blooms and water quality parameters are inadequate for timely decision-making, as they rely on complex satellite imaging software that requires scientific expertise and is not intuitive for daily use, leading to delayed and ineffective responses to rapidly changing water conditions.
Innovation Solution
A mobile application that processes and visualizes location-specific satellite imagery data for water quality parameters like turbidity, surface temperature, and chlorophyll concentration, allowing users to make informed decisions through intuitive data manipulation and prediction of harmful algae blooms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex satellite imaging software is used for monitoring harmful algal blooms, then measurement precision is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent introduces an intermediary processing system that receives complex satellite imagery data and transforms it into simplified visual products. The software acts as a mediator between the raw satellite data and the end user, performing automated analysis to generate intuitive visual representations of water quality parameters without requiring users to understand the underlying complex processing algorithms.
Solution Approach 2:
The patent creates simplified visual copies or representations of the complex satellite data. Instead of presenting raw satellite imagery requiring expert analysis, the system generates visual products that copy the essential information in an easily interpretable format, such as color-coded maps showing chlorophyll concentrations or turbidity levels.
2Measurement precision
If complex satellite imaging software is used for monitoring harmful algal blooms, then measurement precision is improved, but ease of operation worsens
Solution Approach 1:
The software serves as an intermediary that handles all complex processing automatically, presenting only simplified results to the user. The intermediary layer translates complex satellite data into user-friendly visual products with intuitive color codes and clear indicators of water quality conditions, eliminating the need for users to understand or manipulate complex parameters.
Solution Approach 2:
The system performs automated analysis and interpretation of satellite data without requiring user expertise. The software independently processes the imagery, identifies harmful algal blooms, and presents findings in an easily consumable format, allowing non-experts to obtain accurate water quality information through simple operations.
3Device complexity
If traditional monitoring methods relying on human reports and water sampling are used, then device complexity is reduced, but loss of time increases due to delayed detection
Solution Approach 1:
The satellite-based system performs preliminary detection and monitoring continuously over large water bodies, identifying harmful algal blooms before they reach beaches or affect water intakes. The system proactively detects conditions and provides advance warning, allowing authorities to take preventive actions before problems manifest at monitoring locations.
Solution Approach 2:
The patent transitions from point-based monitoring (water samples at specific locations) to area-wide satellite imagery analysis. This dimensional shift enables simultaneous monitoring of entire water bodies, providing comprehensive coverage and early detection capability that sample-based methods cannot achieve, while the automated processing keeps system complexity manageable.
Data Source
AI summary
Systems and methods are used to determine the location and severity of harmful algal blooms or other water quality parameters. GPS location information is transmitted from a mobile device and recent Satellite image data and water quality parameters are provided to the mobile device. Data regarding other locations, historical water quality parameters and algorithm based predictive results are provided for the end user. This provides for near-real time information allowing users to make decisions regarding fishing, beach closures, municipal water intake, etc. so as to avoid toxic effects of a harmful algal bloom.