KR-102964599-B1 - Method and System for Automatically Collecting Analysis Data of a Cat Litter Box

KR102964599B1KR 102964599 B1KR102964599 B1KR 102964599B1KR-102964599-B1

Abstract

The present invention relates to a method and system for automatically collecting analysis data for an automatic cat toilet, comprising a cat toilet and a service server including an entry/exit detection sensor, a camera, a motor system driving a scooping module, and an integrated control unit; wherein the method utilizes trigger information including the entry/exit time when a cat enters the cat toilet generated by the integrated control unit of the cat toilet to request partial image information regarding time intervals related to the cat's entry, defecation, and exit from an image storage server, and performs analysis related to defecation and condition, thereby improving data processing efficiency during the analysis process by not performing analysis on time intervals where analysis is unnecessary.

Inventors

주진명
김태현
박수상
백두산

Assignees

주식회사 밸리언텍스

Dates

Publication Date: 20260513
Application Date: 20250808

Claims (15)

As an automatic data collection system for analysis of automatic cat toilets, A cat toilet comprising an entry/exit detection sensor that detects the entry/exit of a cat, a camera that films the interior space, and an integrated control unit that receives a signal from the entry/exit detection sensor; and A service server connected to an external video storage server and requesting partial video information regarding a time interval related to cat defecation from the video storage server based on data received from the integrated control unit; The above integrated control unit is, Based on the signal received from the above-mentioned entry detection sensor, trigger information including information about the time of entry when the cat entered is transmitted to the service server, and The above service server is, An analysis unit that requests partial image information regarding a time interval related to cat defecation in the cat litter box from the image storage server based on the above trigger information, and inputs the partial image information into one or more deep learning-based learned analysis models to derive analysis information related to the cat's defecation and condition; and Includes an event information providing unit that provides event information including analysis information about cats to a user terminal; The above integrated control unit is, Receive an entry/exit detection signal from the above entry/exit detection sensor that turns ON/OFF depending on whether an object is identified in the interior space of the above cat toilet, and A trigger information is generated that includes information regarding: the entry point when the cat enters the cat toilet as the point when the entry detection signal is turned ON; and the exit point when the cat exits the cat toilet as the point when the entry detection signal is turned OFF after the ON state entry detection signal is turned OFF and a preset OFF maintenance time is exceeded. The above cat toilet includes a motor system that drives a scooping module for scooping cat excrement, and The above integrated control unit is, Receives an operation signal for driving the scooping module from the above motor system, and Generating trigger information including information on the start time of scooping by the above-mentioned scooping module, and The above analysis unit An automatic collection system for analysis data of an automatic cat toilet, which determines a time interval for partial video information to be analyzed among the video information based on trigger information including information on one or more of the entry time, exit time, and scooping start time, and requests the video storage server.
In claim 1, The above service server is, Receive a streaming request from a user terminal, and An automatic collection system for analysis data regarding an automatic cat toilet, comprising a streaming unit that provides to the user terminal a streaming video transmitted in real time to the video storage server by a camera of the cat toilet for which the user terminal requested streaming.
In claim 1, The above analysis unit is, An automatic collection system for analysis data regarding an automatic cat toilet, wherein, among the image information transmitted by the camera to the image storage server, analysis is not performed on image information that does not correspond to the partial image information.
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In claim 1, The above analysis unit is, An automatic collection system for analysis data of an automatic cat toilet, which distinguishes, in the above partial image information, a first partial image for a time interval before the cat covers the excrement with sand after defecating, and a second partial image for a time interval after the cat covers the excrement with sand.
In claim 6, The above cat toilet includes a motor system that drives a scooping module for scooping cat excrement, and The above analysis unit is, Based on the operation signal received from the above motor system, Automatic collection system for analysis data regarding an automatic cat toilet, which distinguishes the first partial image and the second partial image based on the point in time when the motor system drives the scooping module.
In claim 6, The above cat toilet includes a motor system that drives a scooping module for scooping cat excrement, and The above integrated control unit is, Based on the entry detection signal received from the above entry detection sensor, the above motor system is driven after a preset time from the time of entry when the cat enters the cat toilet, and The above analysis unit is, Automatic collection system for analysis data regarding an automatic cat toilet, distinguishing between the first partial image and the second partial image based on the point in time when a preset time has elapsed from the point of entry.
In claim 1, The above analysis model is, A deep learning-based first feces identification model trained to identify cat feces in an input image before they are covered with sand; and A deep learning-based trained first feces analysis model trained to receive an image of cat feces before it is covered with sand and to derive first feces state information including at least one of the amount of feces and the color of feces; The above analysis information is an automatic data collection system for an automatic cat toilet, including the above first defecation state information.
In claim 1, The above analysis model is, A second deep learning-based feces identification model trained to identify cat feces in a state after being covered with sand in an input image; and A deep learning-based trained second feces analysis model trained to receive an image of cat feces after being covered with sand and to derive second feces state information including at least one of the amount of feces and the form of feces; The above analysis information is an automatic collection system for analysis data regarding an automatic cat toilet, including the above second defecation state information.
In claim 1, The above analysis model is, An automatic collection system for analysis data of an automatic cat toilet, comprising: a deep learning-based trained urine analysis model trained to receive an image of cat excrement after it has been covered with sand and to derive urine condition information including information on the amount of urine.
In claim 1, The above event information providing unit is, An automatic data collection system for an automated cat toilet that derives statistical information regarding the number of defecations of a cat in a preset cycle, the scooping time from the time the cat enters the cat toilet until the time the scooping of cat excrement ends, and the time for defecation from the time the cat enters the cat toilet until the time the cat exits the cat toilet, and provides this information to a user terminal.
In claim 12, The above event information providing unit is, An automatic data collection system for an automatic cat toilet that derives the amount of sand consumed in the cat toilet based on the above defecation frequency and provides it to a user terminal.
In claim 1, The above service server, Images of one or more cats capable of using the above cat litter box are stored, and The above service server is, An automatic collection system for analysis data regarding an automatic cat toilet, which identifies which of one or more cats with stored images the cat identified in the above partial image information corresponds to.
As a method for automatically collecting analysis data on an automatic cat toilet performed by an automatic cat toilet system, The above automatic cat toilet system is, A cat toilet comprising an entry/exit detection sensor that detects the entry/exit of a cat, a camera that films the interior space, and an integrated control unit that receives a signal from the entry/exit detection sensor; and A service server connected to an external video storage server and requesting partial video information regarding a time interval related to cat defecation from the video storage server based on data received from the integrated control unit; The automatic collection method for analysis data regarding the above-mentioned automatic cat litter box is, A trigger information transmission step in which, by the integrated control unit above, trigger information including information about the time of entry when a cat entered is transmitted to a service server based on a signal received from the entry detection sensor; An analysis step in which, by means of the above service server, partial image information regarding a time interval related to cat defecation in the corresponding cat litter box is requested from the above image storage server based on the above trigger information, and the said partial image information is input into one or more deep learning-based learned analysis models to derive analysis information related to the cat's defecation and condition; and The above service server provides event information including analysis information about a cat to a user terminal, comprising an event information provision step. The above integrated control unit is, Receive an entry/exit detection signal from the above entry/exit detection sensor that turns ON/OFF depending on whether an object is identified in the interior space of the above cat toilet, and A trigger information is generated that includes information regarding: the entry point when the cat enters the cat toilet as the point when the entry detection signal is turned ON; and the exit point when the cat exits the cat toilet as the point when the entry detection signal is turned OFF after the ON state entry detection signal is turned OFF and a preset OFF maintenance time is exceeded. The above cat toilet includes a motor system that drives a scooping module for scooping cat excrement, and The above integrated control unit is, Receives an operation signal for driving the scooping module from the above motor system, and Generating trigger information including information on the start time of scooping by the above-mentioned scooping module, and The above analysis step is A method for automatically collecting analysis data for an automatic cat toilet, wherein, based on trigger information including information on one or more of an entry time, an exit time, and a scooping start time, a time interval for partial image information to be analyzed among the image information is determined and a request is made to the image storage server.

Description

Method and System for Automatically Collecting Analysis Data of a Cat Litter Box The present invention relates to a method and system for automatically collecting analysis data for an automatic cat toilet, comprising a cat toilet and a service server including an entry/exit detection sensor, a camera, a motor system driving a scooping module, and an integrated control unit; wherein the method utilizes trigger information including the entry/exit time when a cat enters the cat toilet generated by the integrated control unit of the cat toilet to request partial image information regarding time intervals related to the cat's entry, defecation, and exit from an image storage server, and performs analysis related to defecation and condition, thereby improving data processing efficiency during the analysis process by not performing analysis on time intervals where analysis is unnecessary. With the recent increase in the number of people raising cats at home, interest in managing feces and maintaining hygiene is growing. By nature, cats use litter boxes to relieve themselves, and owners need to clean them regularly to maintain hygiene. However, if the litter box is not kept clean due to reasons such as the owner being away for a long time, it can lead to problems such as foul odors, bacterial growth, and the cat refusing to defecate. Meanwhile, conventional cat litter boxes are designed so that owners must manually check and clean up the excrement, and they do not incorporate technology capable of observing the cat's bowel movements or accumulating data. Specifically, while the frequency and volume of defecation can be used to detect diseases such as cystitis and urinary stones early, no cat litter box equipped with technology to monitor and automatically clean up excrement has been released to date. For this reason, there is a growing need to develop a cat litter box equipped with a camera capable of recording the cat's entry and exit and defecation activities, as well as an entry detection sensor, to reliably monitor the cat's defecation activities and detect health abnormalities at an early stage. FIGS. 1a and 1b illustrate the components of an automatic data collection system for an automatic cat toilet according to one embodiment of the present invention. FIG. 2 illustrates a cat toilet according to one embodiment of the present invention. FIG. 3 illustrates components related to a streaming function according to an embodiment of the present invention. FIG. 4 illustrates components related to a function for deriving analysis information according to an embodiment of the present invention. FIG. 5 illustrates trigger information according to one embodiment of the present invention. FIG. 6 illustrates a first partial image and a second partial image according to an embodiment of the present invention. FIG. 7 illustrates an analysis model for analyzing defecation status according to one embodiment of the present invention. FIG. 8 illustrates an analysis model for urine condition analysis according to one embodiment of the present invention. FIG. 9 illustrates an analysis model for identifying cats according to one embodiment of the present invention. FIGS. 10a and FIGS. 10b illustrate an interface for providing event information according to an embodiment of the present invention. FIG. 11 schematically illustrates the internal configuration of a computing device according to one embodiment of the present invention. Hereinafter, various embodiments and/or aspects are disclosed with reference to the drawings. For illustrative purposes, numerous specific details are disclosed in the following description to aid in a general understanding of one or more aspects. However, it will also be recognized by those skilled in the art that these aspects may be practiced without such specific details. The following description and the accompanying drawings describe specific exemplary aspects of one or more aspects in detail. However, these aspects are exemplary, and some of the various methods in the principles of the various aspects may be used, and the description is intended to include all such aspects and their equivalents. In addition, various aspects and features will be presented by a system that may include multiple devices, components and/or modules, etc. It should also be understood and recognized that various systems may include additional devices, components and/or modules, etc., and/or may not include all of the devices, components, modules, etc. discussed in relation to the drawings. Terms such as “embodiment,” “example,” “aspect,” “example,” etc. as used herein may not be interpreted as implying that any aspect or design described is superior or more advantageous than other aspects or designs. Terms used below, such as “part,” “component,” “module,” “system,” “interface,” etc., generally refer to computer-related entities and may, for example, refer to hardware, a combination of hardware and software, or software