Pet Health Imaging for Automated Monitoring and Data Accuracy
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Solution Overview
Problem
Existing pet health monitoring systems are cumbersome, prone to errors, and expensive, making it difficult for pet owners to manage pet health data effectively, particularly for conditions like diabetes where diet and water intake are crucial.
Innovation Solution
A pet health monitoring auxiliary device with an imaging module, control module, and lighting module that captures images, recognizes detection information, and adjusts lighting parameters, using machine learning models to enhance data accuracy and convenience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional manual methods are used to monitor pet health data, then the process is simple and low-cost, but it is cumbersome, prone to errors, and inconvenient for long-term management
Solution Approach 1:
The system enables automated self-service monitoring where the pet health device automatically captures images, recognizes detection information, tracks target objects, and records data without requiring manual operation. The device autonomously performs health monitoring tasks, eliminating the need for owners to manually operate glucometers and test strips while maintaining high data accuracy.
Solution Approach 2:
The patent replaces manual mechanical operations with an automated imaging and recognition system. Instead of manually using glucometers and test strips, the system uses an imaging module to capture images and a control module with machine learning models to automatically recognize detection information, substituting mechanical manual processes with automated optical and computational systems.
2Extent of automation
If Bluetooth-enabled glucometers are used to automatically record data, then data recording is automated, but the devices are expensive and not suitable for average pet owners
Solution Approach 1:
The system uses image capture and recognition to create a digital copy of the detection process. Instead of requiring expensive Bluetooth-enabled glucometers, the imaging module captures images of test strips or monitoring devices, and the control module recognizes the detection information from these images, providing an automated but cost-effective alternative that replicates the functionality of expensive branded devices.
Solution Approach 2:
The patent employs disposable test strips or single-use monitoring components that are captured by the imaging system. Rather than investing in expensive reusable Bluetooth-enabled devices, the system uses inexpensive disposable elements that are imaged and processed, making automated monitoring accessible to average pet owners without requiring costly equipment.
3Adaptability or versatility
If multiple devices are used simultaneously for monitoring, then comprehensive data can be collected, but the process becomes complex and error-prone
Solution Approach 1:
The patent combines multiple monitoring functions into a single integrated device. The imaging module, control module with machine learning models, target object tracking, and data recording capabilities are merged into one unified system, eliminating the need to simultaneously operate multiple separate devices while maintaining comprehensive monitoring capabilities.
Solution Approach 2:
The device is designed with multi-functionality to handle various monitoring tasks through a single system. The control module can automatically switch between different device modes (blood glucose monitoring, insulin monitoring, weight recording, deworming recording) based on the target image, making the device universally applicable for multiple health monitoring needs without requiring separate specialized devices.
Data Source
AI summary
The embodiments of this specification provide a pet health monitoring auxiliary device, comprising: an imaging module, configured to capture target images during pet health monitoring; and a control module, configured to recognize detection information based on the captured target images and control a tracking of a target object by the imaging module.