Mobile Pollution Detecting Device Path Optimization
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Solution Overview
Problem
Current air pollution monitoring systems face challenges in achieving high spatial and temporal precision due to cost constraints, often resulting in low spatial or temporal precision due to insufficient coverage or large variance in air pollution over time and across areas.
Innovation Solution
A computer-implemented method and system that uses a mobile pollution detecting device to determine optimal searching paths based on historical pollution distribution data, prioritizing undiscovered areas and areas with high pollution levels, and adjusts paths dynamically based on threshold values and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed sites are used to monitor pollution in targeted areas, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent transitions from static fixed monitoring sites to a dynamic mobile monitoring system that can move through different areas. The mobile device changes its position and monitoring focus dynamically based on real-time pollution data and pre-defined paths, allowing comprehensive coverage without requiring multiple permanent fixed sites throughout the entire area.
Solution Approach 2:
The mobile pollution monitoring device serves multiple functions: it can monitor different sub-areas at different times, follow pre-defined paths for systematic coverage, respond to real-time pollution alerts, and provide both spatial and temporal pollution data. This single multi-functional device replaces the need for multiple specialized fixed monitoring sites.
2Quantity of substance
If mobile observations are used to reduce cost, then cost decreases, but spatial or temporal precision deteriorates
Solution Approach 1:
The system pre-defines multiple monitoring paths through the area before operation begins. These paths are calculated to ensure comprehensive spatial coverage. The mobile device follows these pre-planned routes systematically, guaranteeing that all sub-areas are visited at appropriate intervals, thereby maintaining spatial precision without requiring multiple expensive fixed sites.
Solution Approach 2:
The system continuously receives real-time pollution data from the mobile device and uses this feedback to dynamically adjust monitoring priorities. When high pollution levels are detected in a particular sub-area, the system can trigger alerts and adjust the mobile device's path to revisit that area, thereby maintaining measurement precision through adaptive response rather than relying solely on fixed predetermined locations.
3Quantity of substance
If mobile observations are used to reduce cost, then cost decreases, but temporal precision deteriorates
Solution Approach 1:
The mobile monitoring device operates continuously along its pre-defined paths, constantly collecting pollution data as it moves through different sub-areas. This continuous monitoring approach ensures that temporal variations in pollution levels are captured without gaps, maintaining temporal precision while using a single mobile device instead of multiple fixed sites that would be expensive to deploy and maintain.
Solution Approach 2:
The system implements periodic revisits to sub-areas based on the mobile device's scheduled path. Each sub-area is monitored at regular intervals as the device cycles through its route, ensuring temporal precision through systematic periodic measurement rather than continuous presence at every location. The period of revisits can be adjusted based on pollution levels and monitoring priorities.
Data Source
AI summary
A computer-implemented method includes receiving historical pollution distribution data indicating a pollution distribution in a target area, determining a first searching path for a mobile pollution detecting device that prioritizes subareas in the target area that have not been recently searched relative to other subareas, determining a second searching path for the mobile pollution detecting device that prioritizes subareas in the target area that have a high measure of pollution relative to other subareas, determining whether an amount of the historical pollution distribution data exceeds a threshold amount, and transmitting a signal causing the mobile pollution detecting device to search the target area for pollution based on the first searching path when the amount of the historical pollution distribution data is less than the threshold amount or the second searching path when the amount of the historical pollution distribution data is greater than or equal to the threshold amount.