Automated Litter Box Waste Identification Using Weight Sensing
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Solution Overview
Problem
Existing methods for distinguishing between urine and feces in pet litter boxes are inefficient, often requiring complex sensors or manual cleaning, and struggle with visibility issues due to waste covering and the need for separate waste collection.
Innovation Solution
A system using mass sensors, emitting sensors, and identification sensors integrated into an automated litter device to detect animal entry and exit, analyze weight changes during cleaning cycles, and execute algorithms to identify waste type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera and machine learning are used to detect waste type, then waste identification capability is improved, but device complexity and maintenance requirements worsen
Solution Approach 1:
The patent replaces optical detection systems (camera-based visual recognition) with a weight-based detection system using load cells. The system measures weight changes in the litter box to identify waste type, eliminating the need for cameras, image processing units, and associated complexity while achieving reliable waste identification.
Solution Approach 2:
The patent extracts the waste identification function from the complex visual recognition system and isolates it to a simple weight measurement mechanism. By focusing solely on weight changes rather than visual analysis, the system achieves the identification capability with minimal components.
2Measurement precision
If separate containers for urine and feces collection are used, then measurement precision of waste type is improved, but device complexity and cleaning complexity worsen
Solution Approach 1:
The patent merges the collection of urine and feces into a single litter box compartment, eliminating the need for separate containers. The weight-based detection system identifies waste type through weight change analysis rather than physical separation, simplifying the structure while maintaining identification accuracy.
Solution Approach 2:
The single litter box compartment serves multiple functions: collecting both urine and feces, and providing weight-based identification for both waste types. This multi-functional design eliminates the need for separate specialized containers for different waste types.
3Device complexity
If manual cleaning by pet owner is required, then device complexity is reduced, but productivity and convenience worsen
Solution Approach 1:
The patent implements an automated cleaning system that operates without manual intervention. The system includes sensors to detect when the litter box needs cleaning, automatically removes waste, and replenishes litter, enabling the device to service itself and eliminating the need for pet owners to manually clean.
Solution Approach 2:
The system uses weight sensors and other detectors to continuously monitor the litter box condition and provides feedback to the control system. When waste accumulation reaches a threshold, the system automatically initiates cleaning cycles, creating a closed-loop automated cleaning process.
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
Accurately identifies waste type with minimal complexity and maintenance, enabling automated waste separation and odor control in litter devices.
Implementation Method 1
one or more mass sensors... detect animal entry and exit, analyze weight changes during cleaning cycles
Data Source
AI summary
A method for identifying a type of waste eliminated by an animal in a litter device, the method including: a) automatically detecting entry of the animal into the litter device by one or more sensing devices, b) automatically detecting departure of the animal from the litter device by the one or more sensing devices; c) automatically accessing and executing one or more waste type identification algorithms by one or more processors to determine the type of waste eliminated by the animal; wherein the type of waste is identified based on one or more measured weight characteristics from the one or more mass sensors; and wherein the waste is identified either the cleaning cycle is executed, after the cleaning cycle is executed, or both.