Pet excrement health analysis method and system based on intelligent cat litter box and intelligent cat litter box

By employing a phased data collection and dynamic weighted fusion approach, the challenge of image acquisition during pet toileting was solved, enabling accurate identification and severity grading of hematuria in multi-pet environments, thus improving the robustness and applicability of pet health analysis.

CN122397627APending Publication Date: 2026-07-17SHANGHAI LIANCHONG INTELLIGENT TECH CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHANGHAI LIANCHONG INTELLIGENT TECH CO LTD
Filing Date
2026-04-17
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In existing technologies, pets' tendency to cover their bodies and bury their excrement during toileting makes it difficult to capture complete and clear images of the excretion area. This is especially true in environments where multiple pets are kept together, where the difficulty of image acquisition and analysis is further increased, affecting the accuracy of hematuria identification.

Method used

By collecting images of pet excrement during the toileting process in stages, including images during toileting, images from the time of toileting until leaving, and images during the automatic cleaning stage, and by assigning dynamic weights according to the confidence level of each stage, the health analysis results are fused to construct a health analysis model to identify hematuria.

Benefits of technology

It significantly improves the accuracy and robustness of hematuria identification, enabling accurate identification of hematuria and differentiation of different degrees of severity in multi-pet cohabitation scenarios, thereby enhancing personalized health monitoring capabilities.

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Abstract

本申请实施例提供了一种基于智能猫砂盆的宠物排泄物健康分析方法、系统及智能猫砂盆,包括:构建健康分析模型;采集宠物如厕过程中多个阶段的排泄物图像,包括:第一阶段,采集宠物如厕时的第一图像;第二阶段,采集宠物如厕后至离开前的第二图像;第三阶段,采集宠物离开后自动清理阶段的第三图像;将第一图像、第二图像和第三图像中的至少一个图像输入健康分析模型,输出健康分析结果;其中,健康分析模型的分析过程包括:健康分析模型分析各阶段的排泄物图像,得到各阶段对应的健康分析子结果;根据各阶段的排泄物图像的置信度,为各健康分析子结果分配权重;对加权后的各健康分析子结果进行融合,输出健康分析结果。
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