Litter Box Load-Sensor Monitoring for Early Animal Health Detection
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Solution Overview
Problem
Existing animal health monitoring systems, such as cameras and RFID collars, provide one-dimensional information and require expert interpretation, often failing to detect subtle health issues in pets and disrupting normal behavior, while relying on invasive methods like microchips and specific litter types.
Innovation Solution
An animal monitoring system with multiple load sensors under the litter box, using machine learning classifiers to analyze load data and identify behaviors without cameras or collars, providing early indicators of health conditions like renal, urinary, and mental health issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cameras and video recording devices are used to track litter box activity, then basic behavioral information can be captured, but the information remains one-dimensional and requires qualified behaviorist interpretation
Solution Approach 1:
The patent segments the monitoring system into multiple independent sensor types (load sensors, moisture sensors, temperature sensors, cameras) that each capture specific aspects of litter box activity. This segmentation allows comprehensive behavioral information to be collected through multiple dimensions while the automated processing system eliminates the need for expert interpretation of each individual data stream.
Solution Approach 2:
The monitoring system is designed with multi-functionality, integrating various sensing capabilities (weight measurement, moisture detection, temperature monitoring, visual recording) into a single unified platform. This universal system can detect multiple types of health indicators simultaneously, providing comprehensive behavioral information without requiring separate specialized devices for each function.
2Reliability
If microchips and specific litter types are used for monitoring, then health tracking is enabled, but normal behavior is disrupted and invasive methods are applied
Solution Approach 1:
The patent extracts the monitoring function from invasive elements (microchips, specialized litter) and places it in the environment where the animal already interacts naturally (the litter box). Load sensors and moisture sensors are positioned to detect animal presence and behavior without requiring the animal to wear or ingest any monitoring devices, thereby eliminating behavioral disruption while maintaining reliable health tracking.
Solution Approach 2:
The system allows the animal to interact with the monitoring environment in its natural way - entering the litter box for elimination activities. The sensors automatically detect and record the animal's weight, moisture levels, and behavior patterns during these self-service activities, enabling reliable health tracking without interfering with the animal's normal routines or requiring invasive procedures.
3Loss of information
If visual indicators from litter box use are monitored, then health information can be detected, but symptoms only appear in mid- to late-stages of disease
Solution Approach 1:
The system performs preliminary detection of health issues by continuously monitoring subtle changes in litter box parameters (weight variations, moisture levels, temperature, visit frequency) before visible symptoms appear. The sensors detect early deviations from normal patterns, allowing health issues to be identified in initial stages rather than waiting for mid- to late-stage visual indicators.
Solution Approach 2:
The monitoring system provides continuous feedback on litter box usage patterns, weight changes, and environmental conditions. This feedback loop allows for real-time detection of abnormal patterns and enables early intervention before symptoms become apparent, addressing the timing issue by providing ongoing data rather than periodic visual assessment.
4Measurement precision
If multiple load sensors are used to track animal behavior, then detailed behavioral insights are obtained, but device complexity increases
Solution Approach 1:
The patent combines multiple load sensors into a unified monitoring platform that shares common processing and data analysis infrastructure. By merging the sensor inputs and using integrated algorithms to interpret the combined data, the system achieves detailed behavioral measurement precision while managing device complexity through shared components and centralized processing rather than independent analysis of each sensor.
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 offers detailed behavioral insights, differentiating between animals in multi-cat households and predicting health conditions proactively, minimizing disruption and avoiding invasive methods, while using existing litter types.
Implementation Method 1
individual load sensors of the three or more load sensors are separated from one another and receive pressure input from the platform independent of one another
Data Source
Figure 1A
Figure 1B~1C
Figure 1D~1E
AI summary
The present disclosure provides systems and methods for animal health monitoring. Load data can be obtained from an animal monitoring device including three or more load sensors associated with a platform carrying contained litter thereabove, wherein individual load sensors of the three or more load sensors are separated from one another and receive pressure input from the platform independent of one another, wherein the three or more load sensors individually sample loads at from 2.5 Hz to 110 Hz. An animal behavior property associated with the animal can be recognized if it is determined based on load data that the interaction with the contained litter was due to the animal interaction with the contained litter. The animal behavior property can be classified into an animal classified event using a machine learning classifier.