Intelligent household garbage classifier and working method thereof

Abstract

The invention discloses an intelligent household garbage classifier and a working method thereof, and belongs to the technical field of garbage classification. The intelligent household garbage classifier comprises an external structure, an internal structure and a control system, the external structure comprises a shell and a pulley; the internal structure comprises an intelligent identification unit, a classification execution unit, a user interaction unit, a data management unit and an environmental protection design unit; the control system comprises a visual processing system, a shunting system, a voice interaction system, a mobile application control system and an energy recovery system. The garbage classifier realizes automatic identification and classification of garbage types, and improves the classification accuracy and efficiency; the user interactivity is enhanced; the system integration is optimized, the cost is reduced, and environmental protection and sustainability are emphasized.

Description

Technical Field

[0001] The present invention belongs to the technical field of garbage classification, and in particular relates to an intelligent household garbage classifier and a working method thereof. Background Art

[0002] With the continuous enhancement of environmental awareness, in order to reduce the pollution of garbage to the environment and promote the recycling of resources, garbage classification has been widely promoted. However, in actual operation, residents' knowledge of garbage classification is insufficient or the classification is inaccurate, and the implementation effect of garbage classification is not ideal. In addition, most existing trash cans are static containers, lack intelligent functions, and cannot automatically classify, store or process garbage. They also do not provide any form of user interaction or guidance, which greatly limits the efficiency and effectiveness of garbage classification.

[0003] Chinese patent CN211826963U (publication date: October 30, 2020) discloses an intelligent garbage sorter, which includes an M3505 core board, an ATS3505 main control chip, a WIFI module, a buck circuit, an audio acquisition module, a storage module, a speaker, a light-emitting LED light group, and a control detection IO module. The utility model supports voice interaction, and the user can directly communicate with the device by voice. Under the guidance of the device's voice, the garbage can be correctly classified. It is simple and easy to use.

[0004] Chinese patent CN212891995U (publication date: April 6, 2021) discloses a one-stop intelligent garbage sorter, including a box rack, a classification box, and a wash basin. The surface of the classification box is provided with a stabilizing plate, and the surface of the stabilizing plate is symmetrically provided with slide rails. The slide rails are provided with sliders, and the top of the slider is provided with a support plate. The support plate is provided with a placement mechanism, and the placement mechanism includes two fixed blocks, two slide rods, and a placement plate. A spring is provided inside the fixed block, and a cover plate is provided on the placement plate. Limiting columns are provided at the corners of the cover plate, and eight limiting blocks are provided on the classification box; the garbage is placed on the placement plate, and the position of the placement plate is easy to adjust, which is convenient for placing garbage, and the process of placing garbage is relatively easy and labor-saving. The cover plate plays a blocking role to prevent garbage from falling during the placement process. The shielding cloth covers the wash basin to prevent dust and impurities from accumulating on the wash basin, thereby increasing the water consumption for cleaning the wash basin, thereby saving water for cleaning the wash basin.

[0005] Chinese patent CN219839014U (publication date: October 17, 2023) discloses an infrared intelligent garbage sorter, which relates to the field of garbage sorting technology, including a fixed seat, a rotating column is rotatably connected to the top of the fixed seat, the rotating column is driven by a steering gear, a placement device is fixed on the surface of the rotating column, a conveyor belt is provided on the top of the placement plate, the inner wall of the conveyor belt is meshed with the roller shaft, and the side of the roller shaft is rotatably connected with a fixing part, the roller shaft is driven by a motor, and a switch button is arranged in an array on the surface of the fixed plate. The utility model adopts an infrared intelligent garbage sorter. The infrared detector detects the human body and outputs a switching signal to the transmission module. The transmission module transmits the signal to the external motor. When the box cover is opened, the switch button outputs a switching signal to the drive module. The drive module transmits the signal to the steering gear and the motor. The steering gear drives the rotating column to rotate rapidly, and at the same time, the motor drives the roller shaft to rotate. When the placement device rotates to the top of the corresponding trash can, the garbage is transported into the trash can through the conveyor belt. The whole process is automated and very convenient.

[0006] At present, there are some trash cans with basic intelligent functions, such as the ability to automatically open the lid or a certain compression function, but these devices usually only stay at the simple automated operation level, and have problems such as lack of intelligence, poor user interactivity, and low classification accuracy. It is difficult to meet the needs of modern families for intelligent and efficient garbage sorting. Summary of the invention

[0007] In order to solve the above technical problems, the purpose of the present invention is to provide a smart home garbage sorter that can realize intelligent identification, classification and storage processing of garbage, improve the efficiency and accuracy of garbage classification, and enhance user participation and environmental awareness.

[0008] In order to achieve the above technical objectives, the present invention proposes a smart home garbage sorter, including an external structure, an internal structure and a control system;

[0009] The external structure includes a housing and a pulley;

[0010] The housing is located above the pulley;

[0011] The internal structure includes an intelligent recognition unit, a classification execution unit, a user interaction unit, a data management unit and an environmental design unit;

[0012] The intelligent recognition unit includes a high-definition camera;

[0013] The classification execution unit includes an adaptive mechanical arm and a storage area;

[0014] The user interaction unit includes a touch display screen, a breathing light and a sound emission hole;

[0015] The data management unit includes a maintenance panel and a cloud storage;

[0016] The environmentally friendly design unit includes a solar panel, an automatic sensing device, a heat dissipation system, a power interface and a backup battery compartment;

[0017] The touch display screen, storage area and breathing light are located on the front of the smart home garbage sorter;

[0018] The sound emission hole, power interface, maintenance panel and backup battery compartment are located on the side of the smart home garbage sorter;

[0019] The cloud storage stores a cloud database;

[0020] The heat dissipation system is located at the back of the smart home garbage sorter;

[0021] The solar panel and automatic sensing device are located on the top surface of the smart home garbage sorter;

[0022] The control system includes a visual processing system, a diversion system, a voice interaction system, a mobile application control system and an energy recovery system.

[0023] Preferably, the storage area adopts a drawer-type or flip-top design;

[0024] Preferably, the heat dissipation system comprises heat dissipation holes or heat dissipation grilles.

[0025] Preferably, the visual processing system includes a trained convolutional neural network (CNN) model.

[0026] A working method of a smart home garbage sorter comprises the following steps:

[0027] Step S1, placing garbage;

[0028] Step S2, the intelligent recognition unit starts recognition;

[0029] Step S3, the classification execution unit performs classification;

[0030] Step S4: the data management unit performs data recording and analysis;

[0031] Step S5: the user interaction unit provides feedback;

[0032] Step S6: The environmental design unit performs energy management.

[0033] Furthermore, the step S1 includes the following steps:

[0034] Step S101: The user puts garbage into the input port of the smart home garbage sorter;

[0035] Step S102: Start the smart home garbage classifier.

[0036] Furthermore, the step S2 comprises the following steps:

[0037] Step S201: Camera capture, a high-definition camera captures images of garbage in real time;

[0038] Step S202: image preprocessing, preprocessing the captured image, including resizing, normalization, and enhancement, to improve the accuracy of the recognition model;

[0039] Step S203, deep learning recognition, inputting the image preprocessed in step S202 into a trained convolutional neural network (CNN) model to perform feature extraction and classification judgment;

[0040] Step S204: output recognition results. The CNN model outputs garbage type labels, including recyclables, hazardous waste, wet garbage, and dry garbage.

[0041] Furthermore, step S3 includes the following steps:

[0042] Step S301, receiving the recognition result, the classification execution unit receives the recognition result outputted in step S204;

[0043] Step S302: operate the robotic arm, and according to the recognition result outputted in step S204, the adaptive robotic arm moves the garbage from the delivery port to the corresponding storage area according to the preset path and force;

[0044] Step S303: Cooperate with the diversion system, which ensures that the robot arm puts the garbage into the corresponding classification area and handles fault tolerance.

[0045] Furthermore, the step S4 comprises the following steps:

[0046] Step S401, collecting data, the data management unit collects various data in the garbage classification process in real time, including classification accuracy, user behavior patterns, etc.;

[0047] Step S402: storing data, uploading the collected data to a cloud database of a cloud storage device for storage;

[0048] Step S403: Analyze the data to analyze the stored data to optimize system performance, improve classification accuracy, and provide personalized classification suggestions for users.

[0049] Furthermore, the step S5 comprises the following steps:

[0050] Step S501: operate the touch screen, and the user views classification guidance, system status, classification records and other information through the touch screen;

[0051] Step S502: voice interaction, the user interacts through the voice interaction system to obtain real-time feedback;

[0052] Step S503, mobile application, the user remotely monitors and manages the smart home garbage classifier through the mobile application control system, and views the classification records and statistical information;

[0053] Step S504, instant feedback: the smart home garbage classifier instantly feeds back the classification results through the sound emission hole and the touch display screen, including confirmation of successful classification and prompt of incorrect classification.

[0054] Furthermore, step S6 includes the following steps:

[0055] Step S601: solar power supply, solar panels provide the main energy source, reducing the dependence on external power supply;

[0056] Step S602, energy recovery, the energy recovery system converts the waste heat and residual energy during the operation of the smart home garbage sorter into electrical energy.

[0057] Compared with the prior art, the advantages and effects of the present invention are as follows:

[0058] 1. The present invention realizes rapid and accurate identification and effective classification of garbage types through the integrated application of internal structure and control system, greatly improving the efficiency and accuracy of garbage classification.

[0059] 2. The present invention improves user participation and interest through the user interaction unit, and at the same time enhances user awareness of garbage classification through real-time feedback and personalized suggestions, thereby enhancing user participation and environmental awareness.

[0060] 3. The present invention can continuously optimize performance and user experience through the data management unit, provide more intelligent and personalized services, and improve classification accuracy and efficiency.

[0061] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application so that it can be implemented in accordance with the contents of the specification, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following is a detailed description of the preferred embodiments of the present application in conjunction with the accompanying drawings as follows.

[0062] Based on the detailed description of the specific embodiments of the present application in combination with the accompanying drawings below, those skilled in the art will become more aware of the above and other objects, advantages and features of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings without creative work. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale.

[0064] in:

[0065] Figure 1 This is the front elevation view of the smart home garbage sorter;

[0066] Figure 2 This is the back elevation of the smart home garbage sorter;

[0067] Figure 3 This is a top view of a smart home waste sorter;

[0068] Figure 4 Workflow diagram for smart home garbage sorter.

[0069] Explanation of the accompanying drawings: 1-touch screen; 2-storage area; 3-pulley; 4-breathing light; 5-sound emission hole; 6-cooling system; 7-power interface; 8-maintenance panel; 9-spare battery compartment; 10-solar panel; 11-automatic sensing device; 21-dropping port. DETAILED DESCRIPTION

[0070] To make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, rather than all of the embodiments. In the following description, specific details such as specific configuration and components are provided only to help fully understand the embodiments of the present application. Therefore, it should be clear to those skilled in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, for clarity and brevity, the description of known functions and structures is omitted in the embodiment.

[0071] It should be understood that the references to "one embodiment" or "this embodiment" throughout the specification mean that the specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present application. Therefore, the references to "one embodiment" or "this embodiment" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0072] In addition, the present application may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplicity and clarity, and does not in itself indicate the relationship between the various embodiments and / or settings discussed.

[0073] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" in this article describes another type of association object relationship, indicating that there can be two relationships. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the previous and next associated objects are in an "or" relationship.

[0074] The term "at least one" in this article is merely a description of the association relationship of associated objects, indicating that there may be three relationships. For example, at least one of A and B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0075] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusions.

[0076] Example 1

[0077] This embodiment shows the structure and composition of a smart home garbage classifier.

[0078] Please refer to Figure 1-3 , a smart home garbage sorter, including an external structure, an internal structure and a control system;

[0079] The external structure includes a housing and a pulley 3;

[0080] The housing is located above the pulley 3;

[0081] The internal structure includes an intelligent recognition unit, a classification execution unit, a user interaction unit, a data management unit and an environmental design unit;

[0082] The intelligent recognition unit includes a high-definition camera;

[0083] The classification execution unit includes an adaptive mechanical arm and a storage area 2;

[0084] The user interaction unit includes a touch display screen 1, a breathing light 4 and a sound emission hole 5;

[0085] The data management unit includes a maintenance panel 8 and a cloud storage;

[0086] The environmentally friendly design unit includes a solar panel 10, an automatic sensing device 11, a heat dissipation system 6, a power interface 7 and a backup battery compartment 9;

[0087] The touch screen 1, storage area 2 and breathing light 4 are located on the front of the smart home garbage sorter;

[0088] The sound emission hole 5, power interface 7, maintenance panel 8 and backup battery compartment 9 are located on the side of the smart home garbage sorter;

[0089] The cloud storage stores a cloud database;

[0090] The heat dissipation system 6 is located at the back of the smart home garbage sorter;

[0091] The solar panel 10 and the automatic sensing device 11 are located on the top surface of the smart home garbage sorter;

[0092] The control system includes a visual processing system, a diversion system, a voice interaction system, a mobile application control system and an energy recovery system.

[0093] Preferably, the storage area 2 is designed in a drawer or flip-top style;

[0094] Preferably, the heat dissipation system 6 includes heat dissipation holes or heat dissipation grilles.

[0095] Preferably, the visual processing system includes a trained convolutional neural network (CNN) model.

[0096] The technical effect of this embodiment is as follows: the present invention realizes rapid and accurate identification and effective classification of garbage types through the integrated application of the internal structure and the control system, thereby greatly improving the efficiency and accuracy of garbage classification; the user interaction unit improves the user's participation and interest, while the real-time feedback and personalized suggestions enhance the user's awareness of garbage classification, user participation and environmental awareness; the data management unit can continuously optimize performance and user experience, provide more intelligent and personalized services, and improve classification accuracy and efficiency.

[0097] Example 2

[0098] This embodiment introduces the intelligent identification unit of a smart home garbage classifier.

[0099] An intelligent identification unit of an intelligent household garbage sorter, comprising a high-definition camera;

[0100] The intelligent recognition unit uses a high-definition camera in conjunction with a visual processing system in the control system to capture garbage images through the high-definition camera, and the visual processing system analyzes the garbage images to achieve accurate recognition of various types of garbage such as recyclables, hazardous garbage, wet garbage, dry garbage, etc.

[0101] The visual processing system includes a trained convolutional neural network (CNN) model;

[0102] The convolutional neural network (CNN) is used as the core recognition algorithm. By training a large amount of labeled garbage image data, it can realize the automatic recognition and classification of various types of garbage, such as recyclables, hazardous garbage, wet garbage, dry garbage, etc. Through its unique hierarchical structure, CNN can effectively extract key features in the image and abstract them at multiple levels, thereby improving the accuracy and robustness of the recognition model.

[0103] The convolutional neural network CNN model usually includes an input layer, multiple convolutional layers, a pooling layer, a fully connected layer and an output layer. The convolution layer is used to extract local features in the image, and slides the convolution kernel or filter on the image to perform feature mapping. The pooling layer is used to reduce the feature dimension, reduce the amount of calculation, and improve the model's ability to resist overfitting. The fully connected layer nonlinearly combines the features learned by the convolution layer and the pooling layer and outputs them to the final classifier. The output layer usually uses a softmax function for classification and outputs the probability distribution of each type of garbage. The CNN model is trained using labeled garbage image data, and the model parameters are optimized through the back propagation algorithm to reduce prediction errors. Strategies such as cross-validation are used during training to avoid overfitting, and data enhancement technology is used to improve the generalization ability of the model.

[0104] Technical effect of this embodiment: The intelligent recognition unit of the smart home garbage classifier continuously trains and updates the model by constantly adding new garbage types and image data, so that it can adapt to more complex garbage classification scenarios.

[0105] Example 3

[0106] This embodiment introduces the classification execution unit of the smart home garbage classifier.

[0107] The classification execution unit includes an adaptive mechanical arm and a storage area 2;

[0108] The classification execution unit uses the adaptive mechanical arm to cooperate with the diversion system in the control system, and accurately controls the mechanical arm to place the garbage into the corresponding storage area according to the recognition result of the intelligent recognition unit. The diversion system is a system that guides or cooperates with the mechanical arm to accurately place different types of garbage into their corresponding storage areas according to the recognition result of the intelligent recognition unit, including guidance function, diversion logic, fault tolerance mechanism and system integration.

[0109] Guidance function: Ensure that the robot arm can accurately reach the corresponding storage area along the preset path when grabbing and moving garbage. This may include a series of mechanical guidance structures, such as guide rails, sliders, etc., to ensure the stability and accuracy of the robot arm's movement.

[0110] Diversion logic: Based on the output of the intelligent recognition unit, the diversion system is responsible for controlling the opening or closing of different channels to ensure that each type of garbage is sent to the correct classification area. This usually involves the logic programming of the control mechanism to quickly respond to the recognition results and adjust the status of the diversion channel.

[0111] Fault tolerance mechanism: In the process of garbage sorting, there may be identification errors or mechanical failures. The diversion system needs to have a certain fault tolerance capability, such as emergency stop mechanism, misplaced recycling function, etc., to ensure that even if errors occur, the impact can be minimized.

[0112] System integration: The diversion system needs to be closely integrated with other modules such as the intelligent identification unit and adaptive robotic arm to achieve real-time information exchange and synchronization. This requires the diversion system to be highly flexible and scalable to adapt to different types of garbage sorting needs and system architectures.

[0113] Technical effect of this embodiment: The classification execution unit robotic arm of the smart home garbage sorter moves the garbage from the delivery port to the corresponding storage drawer or container according to the preset path and force, thereby realizing automatic classification.

[0114] Example 4

[0115] This embodiment introduces the user interaction unit of a smart home garbage classifier.

[0116] The user interaction unit includes a touch display screen 1, a voice interaction system and a mobile application control system, providing an intuitive operation interface and diversified interaction methods.

[0117] Users can view information such as sorting instructions, system status, and sorting records through the touch screen, and can also interact with the system through voice commands. In addition, the mobile application control system enables users to remotely monitor and manage the garbage sorter.

[0118] Technical effect of this embodiment: The user interaction unit of the smart home garbage classifier provides users with personalized classification suggestions and feedback.

[0119] Example 4

[0120] This embodiment introduces the data management unit of a smart home garbage classifier.

[0121] The data management unit utilizes Internet of Things technology to collect the operating data of the garbage classifier in real time, and stores and analyzes it through a cloud database.

[0122] The data collected by the data management unit include garbage classification accuracy, user behavior patterns, etc., which are used to optimize system performance, improve classification accuracy, and provide users with personalized classification suggestions.

[0123] Technical effect of this embodiment: The data management unit of the smart home garbage classifier provides users with customized classification solutions and optimization suggestions.

[0124] Example 5

[0125] Based on the above-mentioned embodiment 1, this embodiment is a working method of a smart home garbage classifier.

[0126] A working method of a smart home garbage sorter comprises the following steps:

[0127] Step S1, placing garbage;

[0128] Step S2, the intelligent recognition unit starts recognition;

[0129] Step S3, the classification execution unit performs classification;

[0130] Step S4: the data management unit performs data recording and analysis;

[0131] Step S5: the user interaction unit provides feedback;

[0132] Step S6: The environmental design unit performs energy management.

[0133] Furthermore, the step S2 comprises the following steps:

[0134] Step S201: Camera capture, a high-definition camera captures images of garbage in real time;

[0135] Step S202: image preprocessing, preprocessing the captured image, including resizing, normalization, and enhancement, to improve the accuracy of the recognition model;

[0136] Step S203, deep learning recognition, inputting the image preprocessed in step S202 into a trained convolutional neural network (CNN) model to perform feature extraction and classification judgment;

[0137] Step S204: output recognition results. The CNN model outputs garbage type labels, including recyclables, hazardous waste, wet garbage, and dry garbage.

[0138] Furthermore, step S3 includes the following steps:

[0139] Step S301, receiving the recognition result, the classification execution unit receives the recognition result outputted in step S204;

[0140] Step S302, operating the robotic arm, according to the recognition result outputted in step S204, the adaptive robotic arm moves the garbage from the delivery port 21 to the corresponding storage area 2 according to the preset path and force, so as to realize automatic classification;

[0141] Step S303: Cooperate with the diversion system, which ensures that the robot arm puts the garbage into the corresponding classification area and handles fault tolerance.

[0142] Furthermore, the step S4 comprises the following steps:

[0143] Step S401, collecting data, the data management unit collects various data in the garbage classification process in real time, including classification accuracy, user behavior patterns, etc.;

[0144] Step S402: storing data, uploading the collected data to a cloud database for storage;

[0145] Step S403: Analyze the data to analyze the stored data to optimize system performance, improve classification accuracy, and provide personalized classification suggestions for users.

[0146] Furthermore, the step S5 comprises the following steps:

[0147] Step S501, operate the touch screen 1, the user checks the classification guidance, system status, classification records and other information through the touch screen 1;

[0148] Step S502: voice interaction, the user interacts through the voice interaction system to obtain real-time feedback;

[0149] Step S503, mobile application, the user remotely monitors and manages the smart home garbage classifier through the mobile application control system, and views the classification records and statistical information;

[0150] Step S504, instant feedback, the smart home garbage classifier instantly feeds back the classification results through the sound emission hole 5 and the touch display screen 1, including confirmation of successful classification and prompt of incorrect classification.

[0151] Furthermore, step S6 includes the following steps:

[0152] Step S601: solar power supply, the solar panel 10 provides the main energy source, reducing the dependence on external power supply;

[0153] Step S602, energy recovery, the energy recovery system converts the waste heat and residual energy during the operation of the smart home garbage sorter into electrical energy.

[0154] The technical effect of this embodiment: The present invention provides instant feedback on classification results through the sound emission hole and the touch display screen, including confirmation of successful classification and prompts of incorrect classification, enhanced user feedback, and enhanced user participation and accuracy; through data recording and analysis, the recognition algorithm and classification strategy are continuously optimized to improve classification accuracy and efficiency. At the same time, personalized classification suggestions are provided based on the user's classification habits and preferences; users can remotely view device status, classification records and statistical information through mobile phone applications to achieve remote management and monitoring. In addition, it also supports automatic alarm functions, such as timely notification of users when the storage area is overflowing or the equipment fails.

[0155] To summarize, the present invention provides a smart home garbage classifier and a working method thereof. The smart home garbage classifier realizes precise control of the garbage delivery path and force through the integration of machine vision and deep learning, a high-precision, adaptive robotic arm system, diversified interaction methods and real-time collection and analysis of data. The recognition model has higher self-learning ability and optimization space, and provides users with customized classification schemes and optimization suggestions. The invention is original and innovative.

[0156] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A smart home garbage sorter, characterized in that: The smart home garbage sorter includes an external structure, an internal structure and a control system; The external structure comprises a housing and a pulley (3); The housing is located above the pulley (3); The internal structure includes an intelligent recognition unit, a classification execution unit, a user interaction unit, a data management unit and an environmental design unit; The intelligent recognition unit includes a high-definition camera; The classification execution unit includes an adaptive mechanical arm and a storage area (2); The user interaction unit comprises a touch display screen (1), a breathing light (4) and a sound emission hole (5); The data management unit comprises a maintenance panel (8) and a cloud storage device; The environmentally friendly design unit comprises a solar panel (10), an automatic sensing device (11), a heat dissipation system (6), a power interface (7) and a backup battery compartment (9); The touch display screen (1), the storage area (2) and the breathing light (4) are located on the front side of the smart home garbage sorter; The sound emission hole (5), the power interface (7), the maintenance panel (8) and the backup battery compartment (9) are located on the side of the smart home garbage sorter; The heat dissipation system (6) is located at the back of the smart home garbage sorter; The solar panel (10) and the automatic sensing device (11) are located on the top surface of the smart home garbage sorter; The cloud storage stores a cloud database; The control system includes a visual processing system, a diversion system, a voice interaction system, a mobile application control system and an energy recovery system.

2. The smart home garbage sorter according to claim 1, characterized in that: The storage area (2) comprises a delivery port (21); The storage area (2) is designed in a drawer or flip-top style; The heat dissipation system (6) comprises heat dissipation holes or heat dissipation grilles.

3. The smart home garbage sorter according to claim 2, characterized in that: The visual processing system includes a trained convolutional neural network (CNN) model.

4. The working method of the smart home garbage sorter according to any one of claims 1 to 3, characterized in that: The following steps are involved: Step S1, placing garbage; Step S2, the intelligent recognition unit starts recognition; Step S3, the classification execution unit performs classification; Step S4: the data management unit performs data recording and analysis; Step S5: the user interaction unit provides feedback; Step S6: The environmental design unit performs energy management.

5. The working method according to claim 4, characterized in that: The step S1 comprises the following steps: Step S101, the user puts garbage into the input port (21) of the smart home garbage sorter; Step S102: Start the smart home garbage classifier.

6. The working method according to claim 5, characterized in that: The step S2 comprises the following steps: Step S201: Camera capture, a high-definition camera captures images of garbage in real time; Step S202: image preprocessing, preprocessing the captured image, including resizing, normalization, and enhancement, to improve the accuracy of the recognition model; Step S203, deep learning recognition, inputting the image preprocessed in step S202 into a trained convolutional neural network (CNN) model to perform feature extraction and classification judgment; Step S204: output recognition results. The CNN model outputs garbage type labels, including recyclables, hazardous waste, wet garbage, and dry garbage.

7. The working method according to claim 6, characterized in that: The step S3 comprises the following steps: Step S301, receiving the recognition result, the classification execution unit receives the recognition result outputted in step S204; Step S302, operating the robotic arm, according to the recognition result outputted in step S204, the adaptive robotic arm moves the garbage from the delivery port (21) to the corresponding storage area (2) according to a preset path and force; Step S303: Cooperate with the diversion system, which ensures that the robot arm puts the garbage into the corresponding classification area and handles fault tolerance.

8. The working method according to claim 7, characterized in that: The step S4 comprises the following steps: Step S401, collecting data, the data management unit collects various data in the garbage classification process in real time, including classification accuracy and user behavior patterns; Step S402: storing data, uploading the collected data to a cloud database on a cloud storage device for storage; Step S403: Analyze the data to analyze the stored data to optimize system performance, improve classification accuracy, and provide personalized classification suggestions for users.

9. The working method according to claim 8, characterized in that: The step S5 comprises the following steps: Step S501, operate the touch screen (1), the user checks the classification guidance, system status, and classification record information through the touch screen (1); Step S502: voice interaction, the user interacts through the voice interaction system to obtain real-time feedback; Step S503, mobile application, the user remotely monitors and manages the smart home garbage classifier through the mobile application control system, and views the classification records and statistical information; Step S504, instant feedback, the smart home garbage classifier instantly feeds back the classification results through the sound emission hole (5) and the touch display screen (1), including confirmation of successful classification and prompt of incorrect classification.

10. The working method according to claim 9, characterized in that: The step S6 comprises the following steps: Step S601, solar power supply, the solar panel (10) provides the main energy source, reducing the dependence on external power supply; Step S602, energy recovery, the energy recovery system converts the waste heat and residual energy during the operation of the smart home garbage sorter into electrical energy.

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