Infrared Depth Mapping for Mosquito Netting Gap Detection
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Solution Overview
Problem
Existing mosquito netting detection methods fail to effectively identify gaps that can allow mosquitoes to penetrate, posing a risk of mosquito-borne illnesses.
Innovation Solution
A system utilizing infrared sensors to create a depth map of the netting, identifying gaps by measuring the distance of each strand and detecting irregularities, with a notification system to alert users of potential entry points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mosquito netting is used to prevent mosquito bites, then protection against mosquito-borne illnesses is improved, but gaps in the netting can allow mosquitoes to penetrate
Solution Approach 1:
The patent replaces manual visual inspection of netting gaps with an automated optical detection system using a camera and image processing algorithms. The system captures images of the netting, processes them to identify gap locations and sizes, and provides automated feedback to users about potential mosquito penetration points, eliminating the need for manual checking.
Solution Approach 2:
The patent introduces an intermediary detection system between the netting and mosquitoes. The optical detection system acts as a mediator that monitors the netting condition and alerts users to gaps before mosquitoes can exploit them, providing an additional layer of protection without physically blocking mosquitoes.
2Measurement precision
If manual inspection of netting gaps is performed, then gap detection is possible, but detection accuracy and consistency are insufficient
Solution Approach 1:
The patent replaces manual visual inspection with an automated optical system that uses a camera to capture images and algorithms to detect gaps. This substitution provides consistent, repeatable measurements of gap locations and sizes without human error or fatigue, significantly improving detection accuracy while maintaining ease of use through automated operation.
Solution Approach 2:
The patent creates a digital copy of the netting structure through camera imaging. This optical copy allows for precise measurement and analysis of gap characteristics without physically touching or disturbing the netting, enabling accurate detection while keeping the inspection process simple and non-invasive.
3Object-affected harmful factors
If the netting structure is made more complex to prevent gaps, then mosquito penetration is reduced, but ease of installation and adjustment deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the optical detection system provides information about gap locations and sizes back to users. This feedback enables users to identify and repair specific problem areas without needing to redesign or complicate the netting structure, maintaining installation simplicity while effectively addressing penetration risks through targeted repairs.
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
The system accurately detects gaps in mosquito netting, reducing the risk of mosquito bites and contraction of mosquito-borne illnesses by ensuring the netting is properly sealed.
Implementation Method 1
an infrared detector that captures an infrared signal from objects within a field of view
Implementation Method 2
The detector is configured to capture electromagnetic signals from objects within a field of view
Data Source
AI summary
Systems and methods for detecting gaps in netting include constructing a depth map from electromagnetic signals associated with netting surrounding an area, the depth map including measurements of distance of each strand of the netting along an axis perpendicular to a plane formed by the netting relative to the detector. Each segment of netting is identified including each strand of the netting in a side of the netting facing the detector. Locations of gaps in the netting are identified according to the depth map. A user is alerted to the presence and locations of gaps by sending a communication to a computing device.