Animal interpretation system and operation method thereof
By designing an animal interpretation system that integrates microphone and processor, using artificial neural network to analyze animal sound data and generate response messages, it solves the problem that pet owners find it difficult to identify pet needs, and achieves the effect of effectively meeting pet needs.
Patent Information
- Application Number
- CN202411661288.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-20
- Publication Date
- 2025-02-25
AI Technical Summary
Pet owners have difficulty identifying the pet's physical and emotional state, resulting in failure to meet the pet's specific needs and potentially harming the pet's overall health.
Design an animal interpretation system, including a microphone and a processor, reflects the needs of animals by collecting sound data from animals and using a typed artificial neural network to generate responses, such as displaying text messages on the screen or playing audio messages through speakers.
The system can help pet owners identify their pet needs, ensure their physical and mental health, and provide an effective way to meet their pet's specific needs.
Smart Images
Figure CN119517043A_ABST
Abstract
Description
[Technical field]
[0001] The invention relates to an animal interpretation system and an operating method thereof. [Background technology]
[0002] Each pet has its own unique personality, emotions, and communication style, which are often misunderstood by pet owners. As a result, pet owners may unknowingly fail to meet their pet's specific needs, potentially harming the pet's overall health. Therefore, a system is needed to help pet owners identify their pet's physical and emotional state and respond to their pet's needs in a way that ensures their physical and mental health. [Summary of the invention]
[0003] Disclosed herein is an animal interpretation system comprising: a microphone configured to collect sound data from an animal; and a processor configured to generate one of M pre-specified responses based on the sound data, wherein M is an integer greater than 1.
[0004] In one aspect, the animal interpretation system further comprises an attachment device configured to strap the microphone to the animal such that the microphone can pick up sounds made by the animal.
[0005] In one aspect, the attachment device is a collar configured to strap the microphone around the neck of the animal.
[0006] In one aspect, the animal interpretation system further comprises a screen on which each of the M pre-specified responses is displayed.
[0007] In one aspect, the screen is connected to the microphone.
[0008] In one aspect, the screen is not connected to the microphone.
[0009] In one aspect, the animal interpretation system further comprises a speaker, and each of the M pre-specified responses is played by the speaker.
[0010] In one aspect, the speaker is connected to the microphone.
[0011] In one aspect, the speaker is not connected to the microphone.
[0012] In one aspect, the processor is connected to the microphone.
[0013] In one aspect, the processor is not connected to the microphone.
[0014] In one aspect, the processor generates the one of the M pre-specified responses based on the sound data by implementing a categorical artificial neural network having the M pre-specified output results corresponding to the M pre-specified responses, respectively.
[0015] In one aspect, the processor implements a categorized artificial neural network in the following manner: extracting a sound sample from the sound data, the sound sample being the sound intensity of a certain sound frequency at a certain point in time; feeding the sound sample to the categorized artificial neural network to generate one of the M pre-specified output results; and generating the one of the M pre-specified responses that corresponds to the one of the M pre-specified output results.
[0016] In one aspect, the animal is a cat, dog, or bird.
[0017] The present invention discloses an operation method of an animal interpretation system, wherein the operation method comprises: using a microphone to collect sound data from an animal; and using a processor to generate one of M pre-specified responses based on the sound data, wherein M is an integer greater than 1.
Brief Description of the Drawings
[0018] Figure 1 An animal interpretation system according to an embodiment is schematically illustrated.
[0019] Figure 2 A flow chart outlining the operation of an animal interpretation system according to an embodiment is shown. [Specific implementation method]
[0020] Animal Interpretation System
[0021] Figure 1 Schematically, an animal interpretation system 100 according to an embodiment is shown. In one embodiment, the animal interpretation system 100 may include a microphone 110 and a processor 120.
[0022] In one embodiment, the processor 120 may be connected to the microphone 110. For example, the microphone 110 and the processor 120 may be located on a printed circuit board (PCB) 140 (eg, Figure 1 Therefore, the processor 120 is connected to the microphone 110 through the printed circuit board 140. Alternatively, the processor 120 may not be connected to the microphone 110.
[0023] In one embodiment, microphone 110 may collect sound data from animal 190 (eg, sounds from the animal's mouth) and may send the collected sound data to processor 120 for processing.
[0024] In one embodiment, animal 190 may be a pet, such as a cat, dog, or bird.
[0025] In one embodiment, microphone 110 may be placed close to animal 190 to be able to pick up sounds made by animal 190 .
[0026] In one embodiment, processor 120 may process sound data collected from animal 190 (collected by microphone 110 ) and may generate one of M pre-specified responses based on the collected sound data, where M is an integer greater than 1.
[0027] For example, one of the M pre-specified responses may include displaying a text message “I’m hungry!” on screen 130 of animal interpretation system 100. Another of the M pre-specified responses may include displaying a text message “I’m thirsty!” on screen 130.
[0028] In one embodiment, the screen 130 may be connected to the microphone 110. For example, the microphone 110 and the screen 130 may be located on a printed circuit board 140 (eg, Figure 1 Therefore, the screen 130 is connected to the microphone 110 through the printed circuit board 140.
[0029] Alternatively, the screen 130 may not be connected to the microphone 110. Thus, the screen 130 can be kept close to the owner of the animal 190, so that the owner can monitor the condition of the animal 190 remotely.
[0030] Flowchart outlining the operation of the animal interpretation system
[0031] Figure 2 shows a summary according to an embodiment Figure 1 Flowchart 200 of the operation of the animal interpretation system 100 .
[0032] In step 210, the operation may include using a microphone to collect sound data from the animal. For example, in the above embodiment, reference Figure 1 , microphone 110 collects sound data from animal 190.
[0033] In step 220, the operation may include using a processor to generate one of M pre-specified responses based on the sound data. For example, in the above embodiment, reference Figure 1 , the processor 120 generates one of M pre-specified responses based on the collected sound data.
[0034] Other embodiments
[0035] Attachment device
[0036] In one embodiment, reference Figure 1 , the animal interpretation system 100 may include a collar 150 configured to tie the microphone 110 around the neck of the animal 190. For example, the microphone 110 may be located on a printed circuit board 140, and the collar 150 may be connected to the printed circuit board 140 (e.g., Figure 1 Thus, the collar 150 can tie the microphone 110 around the neck of the animal 190.
[0037] Generally speaking, the animal interpretation system 100 may include an attachment device (not shown) that attaches the microphone 110 to the animal so that the microphone 110 can pick up sounds made by the animal 190 .
[0038] speaker
[0039] In one embodiment, reference Figure 1 One of the M pre-specified responses may include a speaker (not shown) of the animal interpretation system 100 playing an audio message “I’m hungry!” Another of the M pre-specified responses may include a speaker playing an audio message “I’m thirsty!”.
[0040] In one embodiment, the speaker may be connected to the microphone 110. For example, the microphone 110 and the speaker may be on the printed circuit board 140. Thus, the speaker is connected to the microphone 110 through the printed circuit board 140.
[0041] Alternatively, the speaker may not be connected to the microphone 110. Thus, the speaker can be kept close to the owner of the animal 190, allowing the owner to monitor the condition of the animal 190 remotely.
[0042] Screens and speakers are not exclusive
[0043] In one embodiment, reference Figure 1 , the animal interpretation system 100 may include both a screen 130 and a speaker. Therefore, in one embodiment, one of the M pre-specified responses may include displaying a text message "I'm hungry!" on the screen 130, and playing an audio message "I'm hungry!" on the speaker; another of the M pre-specified responses may include displaying a text message "I'm thirsty!" on the screen 130, and playing an audio message "I'm thirsty!" on the speaker.
[0044] In one embodiment, the animal interpretation system 100 may include a screen 130 but not a speaker. Alternatively, the animal interpretation system 100 may include a speaker but not a screen 130.
[0045] Artificial Neural Networks
[0046] In one embodiment, reference Figure 1 , the processor 120 may generate one of the M pre-specified responses based on the sound data collected from the animal 190 by implementing a categorized artificial neural network having M pre-specified output results corresponding to the M pre-specified responses, respectively.
[0047] For example, assume that M=2, and the first response of the two pre-specified responses is to display the text message "I'm hungry!" on the screen 130, and the second response of the two pre-specified responses is to display the text message "I'm thirsty!" on the screen 130. Therefore, a classification artificial neural network can be created, and the two output results 0 and 1 correspond to the first response and the second response specified above, respectively.
[0048] Next, in one embodiment, during the training phase, the classification artificial neural network can be trained using sound samples emitted by animals of the same species as the animal 190 (for example, if the animal 190 is a dog, the classification artificial neural network can be trained using sound samples emitted by the dog).
[0049] In one embodiment, after the classification artificial neural network is trained, in the prediction phase, the sound samples from the sound data collected by the microphone 110 from the animal 190 can be fed to the trained classification artificial neural network to generate an output result of 0 or 1. If the output result is 0, the processor 120 can generate a first response (i.e., the processor 120 displays a text message "I'm hungry!" on the screen 130). However, if the output result is 1, the processor 120 can generate a second response (i.e., the processor 120 displays a text message "I'm thirsty!" on the screen 130).
[0050] In one embodiment, each sound sample used in the training phase or the prediction phase may be the sound intensity of a certain sound frequency at a certain time point. Alternatively, each sound sample used in the training phase or the prediction phase may include multiple sound intensities of certain frequencies at certain time points.
[0051] Although various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for illustrative purposes and are not intended to be limiting, with the true scope and spirit being indicated by the appended claims.
Claims
1. An animal interpretation system, characterized in that: include: a microphone configured to collect acoustic data from the animal; as well as A processor is configured to generate one of M pre-specified responses based on the sound data, where M is an integer greater than 1.
2. The animal interpretation system according to claim 1, characterized in that: Also included is an attachment device configured to strap the microphone to the animal so that the microphone can pick up sounds made by the animal.
3. The animal interpretation system according to claim 2, characterized in that: The attachment device is a collar configured to strap the microphone around the neck of the animal.
4. The animal interpretation system according to claim 1, characterized in that: Also included is a screen, wherein each of the M pre-specified responses is displayed on the screen.
5. The animal interpretation system according to claim 4, characterized in that: The screen is connected to the microphone.
6. The animal interpretation system according to claim 4, characterized in that: The screen is not connected to the microphone.
7. The animal interpretation system according to claim 1, characterized in that: A speaker is also included, wherein each of the M pre-specified responses is played by the speaker.
8. The animal interpretation system according to claim 7, characterized in that: The speaker is connected to the microphone.
9. The animal interpretation system according to claim 7, characterized in that: The speaker is not connected to the microphone.
10. The animal interpretation system according to claim 1, characterized in that: The processor is connected to the microphone.
11. The animal interpretation system according to claim 1, characterized in that: The processor is not connected to the microphone.
12. The animal interpretation system according to claim 1, characterized in that: The processor generates the one of the M pre-specified responses based on the sound data by implementing a classified artificial neural network having the M pre-specified output results respectively corresponding to the M pre-specified responses.
13. The animal interpretation system according to claim 12, characterized in that: The processor implements the classification artificial neural network in the following manner: Extracting a sound sample from the sound data, wherein the sound sample is the sound intensity of a certain sound frequency at a certain time point; Feeding the sound sample to the classification artificial neural network to generate one of the M pre-specified output results; as well as The one of the M pre-specified responses corresponding to the one of the M pre-specified output results is generated.
14. The animal interpretation system according to claim 1, characterized in that: The animal is a cat, dog or bird.
15. A method for operating an animal interpretation system, characterized in that: The operation method comprises: Using microphones, collecting acoustic data from animals; and Using a processor, one of M pre-specified responses is generated based on the sound data, where M is an integer greater than one.