Pet identity-based feeding control method and device, electronic equipment and medium

Abstract

This application discloses a feeding control method, device, electronic device, and storage medium based on pet identity, including: detecting a pet's feeding demand signal to a pet feeder; extracting multi-dimensional dynamic feature information of the pet that emitted the feeding demand signal, identifying the multi-dimensional dynamic feature information to determine the target pet; and, based on baseline feeding information corresponding to the target pet, causing the pet feeder to deliver pet food to the target pet; wherein the multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet. This application can trigger the feeding process based on the pet's actual feeding demand and determine the pet's identity through accurate identification of multi-dimensional dynamic features, thus ensuring the accuracy of feeding from both the triggering and identification ends, aiming to achieve on-demand and precise feeding of pets.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, specifically to a feeding control method, device, electronic device, and storage medium based on pet identity. Background Technology

[0002] With the urbanization of society, the proportion of people living alone (such as unmarried / non-married individuals, empty-nest elderly, etc.), couples, and only children is increasing. To fulfill the spiritual need for companionship, more and more families are choosing to keep pets, with dogs and cats being the most common. As owners, one essential "service" they need to provide when keeping pets is feeding them.

[0003] Considering the objective problem that pet owners cannot guarantee they can feed their pets in a timely manner (such as during work hours), they usually choose to feed them in advance, such as placing 2-3 meals of pet food in the feeding bowl beforehand. However, feeding in advance can affect the freshness of the pet food to some extent, and assuming the pet lacks self-control, there is also the possibility of overfeeding. Therefore, using a pet feeder to automatically feed pets becomes an option.

[0004] A common scenario is that a family owns multiple pets, such as cats and dogs, or multiple cats of different breeds and ages. With the increasing diversity of pet food and the growing sophistication of pet owners' care, different pets often require different diets. In this case, if pet feeders are used at fixed times, feeding errors can occur. One solution is to equip pets with devices like Bluetooth modules and RFID tags, with corresponding Bluetooth modules and RFID readers on the pet feeders. This allows for identification of the pet by recognizing Bluetooth and RFID signals, enabling targeted feeding. However, this targeted feeding solution requires both pet and feeder components for identification, and the unpredictable behavior of pets outdoors makes these components prone to damage or loss. Another approach is to identify pets using image data for targeted feeding. This targeted feeding solution suffers from a noticeable error rate in identification. The error rate may arise because while pets with significantly different appearances (such as cats and dogs, large and small dogs, striped and gray cats) can be distinguished using image recognition, the differences are subtle for pets that are similar in breed, color, or size (these differences are often only known to the pet's owner). In such cases, image recognition may have a considerable error rate. Therefore, if the recognition is inaccurate, the feeding will be ineffective and could even harm the pet's health. Summary of the Invention

[0005] This application provides a feeding control method, electronic device, apparatus, and storage medium based on pet identity, aiming to solve the problem of invalid feeding caused by defects in the identification method and lack of targeted feeding triggers in existing automatic pet feeding, which leads to mismatch between pets and pet food. At the same time, it solves the problem of feeding response not matching the actual needs of pets in multi-pet scenarios, and realizes accurate and on-demand feeding based on pet identity.

[0006] In a first aspect, embodiments of this application provide a feeding control method based on pet identity, including: Detects signals indicating a pet's need for food from a pet feeder; Extract multi-dimensional dynamic feature information of the pet that emits the feeding demand signal, and identify the multi-dimensional dynamic feature information to determine the target pet; Based on the baseline feeding information corresponding to the target pet, the pet feeder dispenses pet food to the target pet. The multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet.

[0007] Optionally, in some embodiments of this application, the pet feeder is configured with a demand detection module and a feature acquisition module, and the detection of the feeding demand signal and the acquisition of multi-dimensional dynamic feature information are achieved through the following methods: When a trigger signal is detected indicating that a pet is near the pet feeder, the demand detection module is activated so that: The feeding demand signal of the pet is collected through the demand detection module; When a valid feeding demand signal is acquired, the feature acquisition module is activated so that: The feature acquisition module extracts multi-dimensional dynamic feature information of the pet.

[0008] Optionally, in some embodiments of this application, the pet feeder is equipped with a first guiding component, and the methods for detecting the feeding demand signal and obtaining multi-dimensional dynamic feature information include: When the pet feeder is in the feeding-ready mode, the first guide component is activated so that: Guide the pet toward the pet feeder; thereby: When a trigger signal is detected indicating that a pet is approaching the pet feeder, the demand detection module is activated to collect the pet's feeding demand signal; furthermore: When a valid feeding demand signal is collected, the feature acquisition module is put into operation in order to extract multi-dimensional dynamic feature information of the pet.

[0009] Optionally, in some embodiments of this application, the pet is equipped with a second guiding component, and the detection of the feeding demand signal and the acquisition of multi-dimensional dynamic feature information are performed as follows: When the pet feeder is in the feeding-ready mode, determine the pet's current activity status information; Based on the current activity status information, determine whether the second bootloader needs to be activated; If so, then the second boot component is activated so that: Guide the pet toward the pet feeder; thereby: When a trigger signal is detected indicating that a pet is approaching the pet feeder, the demand detection module is activated to collect the pet's feeding demand signal; furthermore: When a valid feeding demand signal is collected, the feature acquisition module is put into operation in order to extract multi-dimensional dynamic feature information of the pet.

[0010] Optionally, in some embodiments of this application, the control method includes, at the same time as, before, or after the second guiding component is started: Send a reminder message.

[0011] Optionally, in some embodiments of this application, when the pets include multiple pets, the feeding demand signal recognition thresholds corresponding to different pets may be the same or different.

[0012] Secondly, embodiments of this application provide a feeding control device based on pet identity, comprising: The detection module is used to detect the pet's feeding demand signal to the pet feeder; The extraction module is used to extract multi-dimensional dynamic feature information of the pet that sends the feeding request signal, and to identify the multi-dimensional dynamic feature information to determine the target pet. The feeding module is used to feed pet food to the target pet based on the baseline feeding information corresponding to the target pet. The multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet.

[0013] Accordingly, this application also provides an electronic device, including a memory, a processor, and a processor program stored in the memory and executable on the processor, wherein the processor executes the program as described in any of the methods above.

[0014] This application also provides a storage medium storing a processor program that, when executed by a processor, implements any of the methods described above.

[0015] This application provides a feeding control method, device, electronic device, and storage medium based on pet identity. The method detects a pet's feeding demand signal from a pet feeder; extracts multi-dimensional dynamic feature information of the pet that emitted the feeding demand signal; identifies the multi-dimensional dynamic feature information to determine the target pet; and, based on baseline feeding information corresponding to the target pet, causes the pet feeder to deliver pet food to the target pet. The multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet. In the feeding control scheme provided by this application, the feeding process can be triggered based on the pet's actual feeding demand, and the pet's identity can be determined through accurate identification of multi-dimensional dynamic features. This dual guarantee of feeding accuracy from both the triggering and identification ends aims to achieve on-demand and precise feeding of pets. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the feeding control method based on pet identity provided in an embodiment of this application; Figure 2 This is a schematic diagram of the feeding control device based on pet identity provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0019] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, components, features, and elements with the same names in different embodiments of this application may have the same meaning or different meanings, the specific meaning of which must be determined by its interpretation in that specific embodiment or further in conjunction with the context of that specific embodiment. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0020] In the following description, the use of suffixes such as "module," "part," or "unit" to denote elements is solely for the purpose of illustrative purposes and has no specific meaning in itself. Therefore, "module," "part," or "unit" may be used interchangeably.

[0021] The following describes in detail the embodiments involved in this application. It should be noted that the order of description of the embodiments in this application is not intended to limit the priority of the embodiments.

[0022] This application provides a method, apparatus, storage medium, and smart terminal for pet-identity-based feeding control. Specifically, the pet-identity-based feeding control method of this application can be executed by a smart terminal or a server, wherein the smart terminal can be a terminal. The terminal can be a smartphone, tablet computer, laptop computer, touch screen, game console, personal computer (PC), personal digital assistant (PDA), or other smart terminal. The terminal may also include a client, which can be a media playback client or a real-time pet-identity-based feeding control client, etc.

[0023] This application provides a feeding control method based on pet identity, which can be executed by an electronic device or a server. This application example illustrates a feeding control method based on pet identity executed by an electronic device. The electronic device includes a touchscreen display and a processor. The touchscreen display is used to present a graphical user interface (GUI) and receive operation commands generated by the user interacting with the GUI. When the user operates the GUI through the touchscreen display, the GUI can control the content locally on the electronic device in response to the received operation commands, or it can control the content on the server side in response to the received operation commands.

[0024] The pet identity-based feeding control scheme provided in this application can trigger the feeding process based on the pet's actual feeding needs, and accurately identify the pet's identity through multi-dimensional dynamic features. It ensures the accuracy of feeding from both the triggering and identification ends, aiming to achieve on-demand and precise feeding of pets.

[0025] It should be noted that the acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations and do not violate public order and good morals.

[0026] It should also be noted that all information (including but not limited to user location information, environmental information of the tour guide scene, user tour guide preference information, etc.), data (including but not limited to tour guide data used for analysis, stored resource data, displayed tour guide information, etc.) and signals involved in this application are authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0027] The following sections provide detailed descriptions of each example. It should be noted that the order in which the embodiments are described is not intended to limit the priority of the embodiments.

[0028] A feeding control method based on pet identity includes: detecting a pet's feeding demand signal to a pet feeder; extracting multi-dimensional dynamic feature information of the pet that emitted the feeding demand signal, identifying the multi-dimensional dynamic feature information to determine a target pet; and, based on baseline feeding information corresponding to the target pet, causing the pet feeder to deliver pet food to the target pet; wherein the multi-dimensional dynamic feature information and the pet have a preset unique mapping relationship.

[0029] In one possible implementation, the pet feeder is equipped with a demand detection module and a feature acquisition module. The demand detection module includes an infrared distance sensor, a touch sensor, and a sound collector to detect trigger signals indicating the pet's approach and its feeding demand signals. The feature acquisition module includes a high-definition dynamic camera, a voiceprint collector, and a gait sensor to extract the pet's facial dynamic features, voiceprint features, and gait features, forming multi-dimensional dynamic feature information. Based on this, a related terminal device can be associated with the pet feeder to set baseline feeding information and feeding demand signal recognition thresholds. The terminal device can be a mobile device, computer, or in-vehicle device, or any combination thereof. In this embodiment, the terminal device is the pet owner's mobile phone.

[0030] Pet owners can open the dedicated app on their mobile phones and set the following baseline feeding information and recognition thresholds on the corresponding interactive interface: The pets include a Ragdoll cat (Yuanbao) and a Corgi dog (Laifu). The pet feeder includes two separate feeding bowls and two storage bins. One feeding bowl and storage bin corresponds to the Ragdoll cat and stores kitten food, while the other corresponds to the Corgi dog and stores adult dog food.

[0031] The basic feeding information for Ragdoll cat Yuanbao is as follows: Enter the feeding waiting mode at 08:00, 14:00 and 20:00 every day, and feed 40g of kitten food each time; The feeding demand signal recognition threshold is: the touch sensor detects a slight pawing signal (signal value ≥20), or the cat stays within 1 meter of the feeder for ≥5 seconds.

[0032] The baseline feeding information for the Corgi Laifu is as follows: Enter the feeding waiting mode at 09:00 and 19:00 every day, and feed 200g of adult dog food each time; the feeding demand signal recognition threshold is: emit a unique eating bark (voiceprint feature matching degree ≥90%), or stay within 2 meters of the feeder for ≥8 seconds.

[0033] Meanwhile, the unique mapping relationship between multi-dimensional dynamic feature information and pets has been pre-entered into the APP. The facial dynamic features, exclusive vocalization features, and gait features of Ragdoll cats and the multi-dimensional dynamic features of Corgis form an independent feature library for identification.

[0034] Please see Figure 1 , Figure 1 This application provides a flowchart illustrating a feeding control method based on pet identity. The specific flow of this pet identity-based feeding control method is as follows: S101, The pet feeder enters the feeding mode for the corresponding pet, starts the first guiding component, and obtains the pet's current activity status information.

[0035] In one possible implementation, the current time is 08:00. The pet feeder enters the feeding mode for the Ragdoll cat Yuanbao, activates the first guiding component (flashing indicator light + soft music that the pet likes), and obtains Yuanbao's current activity status information from the server.

[0036] S103. Based on the pet's current activity status information, determine whether the second guiding component needs to be activated; if yes, proceed to S105; if no, proceed to S107.

[0037] For example, if the obtained location information of the baby is in the family living room (within 3 meters from the feeder) and is in motion, it is determined that there is no need to activate the second guide component, and the process proceeds directly to S107; if the location information of the baby is on the balcony (outside 8 meters from the feeder) and is in resting state, it is determined that the second guide component needs to be activated, and the process proceeds to S105.

[0038] S105. Activate the second guide component embedded in the pet collar, emit a unique guide voice, and send a reminder message to the pet owner's mobile APP (such as "Yuanbao is resting, the guide has been activated, come and take a look").

[0039] S107. Detect the trigger signal when the pet approaches the pet feeder. When the trigger signal is detected, start the demand detection module to collect the pet's feeding demand signal.

[0040] For example, when the infrared distance sensor detects that the baby has entered within 1 meter of the feeder, the demand detection module is activated, and the touch sensor and sound collector begin to collect the baby's behavioral signals.

[0041] S109. Determine whether the collected feeding demand signal reaches the preset recognition threshold. If it is a valid feeding demand signal, proceed to S111; if it is an invalid signal, return to S107.

[0042] For example, the touch sensor detects that the ingot is pawing at the feeder, and the signal value is 35, which reaches the preset threshold of 20. It is determined to be a valid feeding demand signal and proceeds to S111.

[0043] S111. Start the feature acquisition module to extract multi-dimensional dynamic feature information of the pet, identify the feature information and determine the target pet.

[0044] For example, after the feature acquisition module is started, the high-definition dynamic camera acquires the dynamic facial features of Yuanbao, the voiceprint collector acquires its vocal features, and the gait sensor acquires its gait features. The extracted multi-dimensional feature information is matched with the preset feature library. The matching degree reaches 95%, and the target pet is identified as the Ragdoll cat Yuanbao.

[0045] S113. Based on the target pet's baseline feeding information, the pet feeder dispenses a fixed amount of pet food into the corresponding feeding dish to complete the feeding.

[0046] For example, the pet feeder sends a feeding instruction to the corresponding food bin based on Yuanbao's baseline feeding information, and puts 40g of kitten food into the dedicated feeding dish.

[0047] S115. After the feeding is completed, send a feedback message to the pet owner's mobile APP (e.g., "08:00 Yuanbao's feeding is complete, 40g was fed this time").

[0048] As can be seen, in the pet-identity-based feeding control method of this invention, given the availability of baseline feeding information and feature mapping relationships, the feeding process is triggered by the pet's actual feeding demand signal. Combined with multi-dimensional dynamic feature information, pet identification is performed, ensuring the accuracy and targeting of the feeding. Furthermore, through the layered design of the first and second guiding components, personalized guidance is provided based on the pet's activity state. Even when the pet does not actively approach the feeder, the feasibility of the feeding can still be achieved. Simultaneously, the tiered wake-up design of the modules effectively reduces the device's energy consumption.

[0049] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effects of the present invention, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously or in other orders. Some steps can also be added, replaced or omitted. For example, depending on actual needs, only the first guide component or only the second guide component can be set. Alternatively, a step to detect the pet's eating status after feeding can be added to provide feedback to the owner on the pet's eating status.

[0050] In summary, based on the three types of descriptive information, the AI ​​agent is invoked to perform navigation reasoning on the user's navigation instructions, generating the first navigation interaction information. This ensures that the system can accurately locate the navigation interaction elements and resource points corresponding to the user's navigation instructions, avoiding ambiguous or erroneous navigation operations. Next, based on the first navigation interaction information and multiple candidate navigation actions, the AI ​​agent is invoked to generate the first navigation action information. This enables the selection of the optimal navigation action scheme according to different navigation scenarios and user needs, enhancing the system's flexibility and adaptability. Finally, the navigation target action is executed collaboratively in both the intelligent navigation interface and the physical navigation scenario. This not only ensures the immediacy of the navigation response but also achieves deep integration between the virtual interface and the physical scene, optimizing the user's navigation experience.

[0051] This application provides a feeding control method based on pet identity, which detects a pet's feeding demand signal to a pet feeder; extracts multi-dimensional dynamic feature information of the pet that emitted the feeding demand signal, identifies the multi-dimensional dynamic feature information to determine the target pet; and, based on the baseline feeding information corresponding to the target pet, causes the pet feeder to deliver pet food to the target pet. The multi-dimensional dynamic feature information and the pet have a preset unique mapping relationship. In the feeding control scheme provided by this application, the feeding process can be triggered based on the pet's actual feeding demand, and the pet's identity can be determined through accurate identification of multi-dimensional dynamic features. This provides dual assurance of feeding accuracy from both the triggering and identification ends, aiming to achieve on-demand and precise feeding of pets. To facilitate better implementation of the pet identity-based feeding control method of this application embodiment, this application embodiment also provides a pet identity-based feeding control device, wherein the meanings of the terms are the same as those in the above-described pet identity-based feeding control system, and specific implementation details can be found in the description of the system embodiment.

[0052] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a pet-identity-based feeding control device provided in an embodiment of this application. Specifically, the pet-identity-based feeding control device may include a detection module 401, an extraction module 402, and a feeding module 403, as follows: Detection module 201 is used to detect the pet's feeding demand signal to the pet feeder; Extraction module 202 is used to extract multi-dimensional dynamic feature information of the pet that sends the feeding demand signal, and to identify the multi-dimensional dynamic feature information to determine the target pet; The feeding module 203 is used to feed pet food to the target pet using a pet feeder based on the baseline feeding information corresponding to the target pet. The multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet.

[0053] This application provides a feeding control device based on pet identity. A detection module 201 detects a pet's feeding demand signal from a pet feeder; an extraction module 202 extracts multi-dimensional dynamic feature information of the pet that emitted the feeding demand signal, and identifies the target pet based on the multi-dimensional dynamic feature information; a feeding module 203, based on baseline feeding information corresponding to the target pet, causes the pet feeder to deliver pet food to the target pet; wherein the multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet. In the feeding control scheme provided in this application, the feeding process can be triggered based on the pet's actual feeding demand, and the pet's identity can be determined through accurate identification of multi-dimensional dynamic features, thus ensuring the accuracy of feeding from both the triggering and identification ends, aiming to achieve on-demand and precise feeding of pets. Furthermore, embodiments of this application also provide an electronic device, such as... Figure 3 As shown, it illustrates a structural schematic diagram of the electronic device involved in the embodiments of this application, specifically: The electronic device may include components such as a processor 301 with one or more processing cores, a memory 302 with one or more processor-readable storage media, a power supply 303, and an input unit 304. Those skilled in the art will understand that... Figure 3 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: Processor 301 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 302, and by calling data stored in memory 302, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Optionally, processor 301 may include one or more processing cores; preferably, processor 301 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless pet-based feeding control. It is understood that the modem processor may not be integrated into processor 301.

[0054] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and pet-identity-based feeding control methods by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device, etc. In addition, the memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0055] The electronic device also includes a power supply 303 that supplies power to various components. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 303 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0056] The electronic device may also include an input unit 304, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0057] Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in the embodiments of this application, the processing 301 in the electronic device loads the executable files corresponding to the processes of one or more applications into the memory 302 according to the following instructions, and the processing 301 runs the applications stored in the memory 302 to realize various functions, as follows: The system detects a pet's feeding demand signal from a pet feeder; extracts multi-dimensional dynamic feature information of the pet that emitted the feeding demand signal, identifies the multi-dimensional dynamic feature information to determine the target pet; and, based on the baseline feeding information corresponding to the target pet, causes the pet feeder to deliver pet food to the target pet; wherein the multi-dimensional dynamic feature information and the pet have a preset unique mapping relationship.

[0058] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0059] The embodiments of this application can trigger the feeding process based on the actual feeding needs of the pet, and determine the pet's identity through accurate identification of multi-dimensional dynamic features. This dual guarantee of feeding accuracy from both the triggering and identification ends aims to achieve on-demand and precise feeding of pets.

[0060] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a processor-readable storage medium and loaded and executed by a processor.

[0061] To this end, embodiments of this application provide a storage medium storing multiple instructions that can be loaded by a processor to execute steps in any of the pet-identity-based feeding control methods provided in this application. For example, the instructions can execute the following steps: The system detects a pet's feeding demand signal from a pet feeder; extracts multi-dimensional dynamic feature information of the pet that emitted the feeding demand signal, identifies the multi-dimensional dynamic feature information to determine the target pet; and, based on the baseline feeding information corresponding to the target pet, causes the pet feeder to deliver pet food to the target pet; wherein the multi-dimensional dynamic feature information and the pet have a preset unique mapping relationship.

[0062] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0063] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0064] Since the instructions stored in the storage medium can execute the steps of any of the pet identity-based feeding control methods provided in the embodiments of this application, the beneficial effects that any of the pet identity-based feeding control methods provided in the embodiments of this application can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0065] The above provides a detailed description of a feeding control method, device, electronic device, and storage medium based on pet identity provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A feeding control method based on pet identity, characterized in that, include: Detects signals indicating a pet's need for food from a pet feeder; Extract multi-dimensional dynamic feature information of the pet that emits the feeding demand signal, and identify the multi-dimensional dynamic feature information to determine the target pet; Based on the baseline feeding information corresponding to the target pet, the pet feeder dispenses pet food to the target pet. The multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet.

2. The feeding control method based on pet identity according to claim 1, characterized in that, The pet feeder is equipped with a demand detection module and a feature acquisition module. The methods for detecting the feeding demand signal and obtaining multi-dimensional dynamic feature information include: When a trigger signal is detected indicating that a pet is near the pet feeder, the demand detection module is activated so that: The feeding demand signal of the pet is collected through the demand detection module; When a valid feeding demand signal is acquired, the feature acquisition module is activated so that: The feature acquisition module extracts multi-dimensional dynamic feature information of the pet.

3. The feeding control method based on pet identity according to claim 2, characterized in that, The pet feeder is equipped with a first guiding component, and the methods for detecting the feeding demand signal and obtaining multi-dimensional dynamic feature information include: When the pet feeder is in the feeding-ready mode, the first guide component is activated so that: Guide the pet toward the pet feeder; thereby: When a trigger signal is detected indicating that a pet is approaching the pet feeder, the demand detection module is activated to collect the pet's feeding demand signal; furthermore: When a valid feeding demand signal is collected, the feature acquisition module is put into operation in order to extract multi-dimensional dynamic feature information of the pet.

4. The feeding control method based on pet identity according to claim 2 or 3, characterized in that, The pet is equipped with a second guiding component, and the method for detecting the feeding demand signal and obtaining multi-dimensional dynamic feature information is as follows: When the pet feeder is in the feeding-ready mode, determine the pet's current activity status information; Based on the current activity status information, determine whether the second bootloader needs to be activated; If so, then the second boot component is activated so that: Guide the pet toward the pet feeder; thereby: When a trigger signal is detected that a pet is approaching the pet feeder, the demand detection module is activated to collect the pet's feeding demand signal. and then: When a valid feeding demand signal is collected, the feature acquisition module is put into operation in order to extract multi-dimensional dynamic feature information of the pet.

5. The feeding control method based on pet identity according to claim 4, characterized in that, The control method includes, at the same time as, before, or after the activation of the second guiding component: Send a reminder message.

6. The feeding control method based on pet identity according to claim 1, characterized in that, When there are multiple pets, the threshold values ​​for recognizing feeding demand signals for different pets may be the same or different.

7. A feeding control device based on pet identity, characterized in that, include: The detection module is used to detect the pet's feeding demand signal to the pet feeder; The extraction module is used to extract multi-dimensional dynamic feature information of the pet that sends the feeding request signal, and to identify the multi-dimensional dynamic feature information to determine the target pet. The feeding module is used to feed pet food to the target pet based on the baseline feeding information corresponding to the target pet. The multi-dimensional dynamic feature information has a preset unique mapping relationship with the pet.

8. An electronic device, characterized in that, include: A memory, a processor, and a processor program stored in the memory and executable on the processor, wherein the processor executes the program as steps of the pet identity-based feeding control method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The computer processing program is stored in which it can be loaded by a processor and executed as described in any one of claims 1 to 6, based on the pet's identity, for feeding control.

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