AI-driven intelligent garbage identification and classification method and system

Abstract

The invention relates to the technical field of garbage recognition and classification management, in particular to an AI-driven intelligent garbage recognition and classification method and system. The method comprises the steps that working area distribution of an artificial intelligence system, recognition area distribution of face recognition equipment and area distribution of garbage can position placement are analyzed based on a voice recognition video scene. Through use of artificial intelligence, garbage classification delivery behaviors of users in a management area can be intelligently supervised, information propaganda is enhanced, and according to classification delivery conditions and times of the users on various recycled garbage categories and efficiency and habit conditions of the users in performing related delivery behaviors, the classification delivery behaviors of the users can be intelligently supervised. According to the method, feature recognition index evaluation of each recycled garbage category is carried out on the user, a paid return system is constructed to improve the recognition and classification enthusiasm of the user in the management area, the user garbage classification behavior is obviously improved, meanwhile, the safety protection of the system is improved, and the benefits of the user and investors are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of garbage identification and classification management, and specifically to an AI-driven garbage intelligent identification and classification method and system. Background Art

[0002] Garbage classification has gradually become an indispensable way of life, and many people have to face the problem of how to remember the classification standards correctly. There are many types of wet garbage, dry garbage, hazardous garbage, and other garbage, which are easy to confuse, and manual classification is more time-consuming and laborious. The garbage classification problem is an urgent task in today's society and is crucial to environmental protection and sustainable development. The traditional garbage classification method is easily interfered by subjective factors, has low classification accuracy, limited efficiency, and serious waste of resources; our artificial intelligence has shown great potential and application value in this field.

[0003] At present, traditional propaganda methods have a poor effect on guiding daily residents' garbage sorting behavior, which makes it difficult to promote the habit of garbage sorting. To this end, we propose an AI-driven garbage intelligent identification and classification method and system. Summary of the invention

[0004] The purpose of the present invention is to provide an AI-driven garbage intelligent identification and classification method and system, which has the advantage of good guiding effect and solves the problem that traditional propaganda methods have poor guiding effect on the garbage classification behavior of daily residents, making it difficult to promote the habit of garbage classification.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an AI-driven garbage intelligent identification and classification method, the method comprising:

[0006] Step S100: Delineating the management area of ​​the speech recognition video scene analysis artificial intelligence system based on the working area distribution of the speech recognition video scene analysis artificial intelligence system, the recognition area distribution of the face recognition device, and the area distribution of the trash can positions;

[0007] Step S200: popularizing knowledge of garbage classification to users in the management area, and determining the accuracy of personnel information and residential unit information in the management area;

[0008] Step S300: construct an AI intelligent garbage recognition model, and use the AI ​​intelligent garbage recognition model to determine the historical garbage delivery records generated by users using garbage bins in the management area to extract feature information and classify and sort them;

[0009] Step S400: construct an AI intelligent garbage recycling paid reward system, and use the AI ​​intelligent garbage recycling paid reward system to improve the enthusiasm of users in the management area for identification and classification;

[0010] Step S500: Conduct a comprehensive and real safety performance test on the artificial intelligence system to reduce the potential safety risks of the artificial intelligence system and ensure the security of user information and paid reward system;

[0011] Preferably, the step S100 includes:

[0012] Step S101: Obtain facial information and voice communication habits of people in the management area in the voice recognition video scene analysis artificial intelligence system to determine users to be served in the area;

[0013] Step S102: Determine the placement and distribution of trash cans in the management area, and use the facial recognition device to capture the best recognition point that meets the information recognition clarity requirement in front of the trash cans in the management area according to the placement and distribution of trash cans in the management area;

[0014] Step S103: Determine the maximum distance of the management area and install and debug the auxiliary equipment to the best state;

[0015] Preferably, the step S200 includes:

[0016] Step S201: Add voice propaganda equipment and post garbage classification propaganda posters in the management area, wherein the voice propaganda equipment avoids the user's rest period in the morning, noon and evening, and works after the user approaches the voice propaganda equipment at a set distance, posts the garbage classification propaganda posters in the propaganda column, and assists in expanding the propaganda by garbage classification brochures, etc.;

[0017] Step S202: clearly define the collection of user information in the management area, and take the identity information and time information when performing identity information verification, as well as the garbage image, garbage type and garbage classification conclusion information in the garbage bin, collect the corresponding identity information as the object, and sort the garbage image, garbage type and garbage classification conclusion information in the garbage bin according to the time information, and then count the number of consecutive times that the garbage classification conclusion information is correct, and bind the collected information with the user identity information and the residential unit information;

[0018] Preferably, the step S300 includes:

[0019] Step S301: Based on historical data acquisition, a garbage classification model for intelligent garbage identification and classification is constructed, and user classification placement information is imported into the garbage classification model to update model parameters, and a three-dimensional model of user information in the management area is obtained, and the model is imported into a convolutional neural network model for prediction, and prediction data of user classification placement of garbage locations is obtained, and the prediction data of user classification placement is imported into the three-dimensional model of user information in the management area to obtain the locations where users are accustomed to placing garbage in the management area, and whether the classification awareness is enhanced;

[0020] Step S302: Analyze the types of garbage that users are accustomed to placing in the management area, and obtain the living habits of relevant users;

[0021] Step S303: extracting feature information, filing and storing it, and importing it into a garbage classification model for intelligent garbage recognition and classification, so as to enhance the accuracy of using the garbage classification model for intelligent garbage recognition and classification;

[0022] Preferably, the step S400 includes:

[0023] Step S401: On the basis of the garbage classification model of intelligent garbage identification and classification, an AI intelligent garbage recycling paid reward system is constructed, weighing equipment and garbage category comparison display screen are added, the corresponding reward ratio is determined, and equivalent cash or virtual currency is issued to users;

[0024] Step S402: Establishing a mobile supermarket or a physical supermarket for the exchange of daily necessities, thereby forming an incentive mechanism to promote residents to actively participate in garbage sorting and recycling;

[0025] Preferably, the step S500 includes:

[0026] Step S501: Acquire original image data, generate malicious sample data based on the original image data, perform security testing on the artificial intelligence system based on the malicious sample data, and obtain security testing results of the artificial intelligence system to simulate security attacks on the artificial intelligence system in a real environment, thereby achieving comprehensive and real security performance testing on the artificial intelligence system and reducing security risks of the artificial intelligence system;

[0027] Step S502: Malicious sample data includes malicious violent destruction and malicious data intrusion, and synchronously associates warnings;

[0028] Step S503: Ensure the security of user information and paid reward system.

[0029] In order to better implement the above method, an identification and classification system is also proposed, which includes a regional division management module, a relevant knowledge popularization module, a user information determination module, a garbage identification module, a feature information extraction and sorting module, a paid reward module, and a safety detection module;

[0030] The area division management module includes a camera, a facial recognition module and a voice recognition module, which is used to delineate the management area of ​​the voice recognition video scene analysis artificial intelligence system according to the working area distribution of the voice recognition video scene analysis artificial intelligence system, the recognition area distribution of the facial recognition device and the regional distribution of the placement of the trash cans;

[0031] The relevant knowledge popularization module and the user information determination module are used to popularize knowledge of garbage classification to users in the management area and determine the accuracy of personnel information and residential unit information in the management area;

[0032] The garbage identification module includes identifying recyclable garbage, non-recyclable garbage and other garbage, and is used to build an AI intelligent garbage identification model, and use the AI ​​intelligent garbage identification model to determine the historical garbage delivery records generated by users using garbage bins in the management area to extract feature information and classify and organize them;

[0033] The feature information extraction and sorting module is used to analyze the types and characteristics of garbage, and help users analyze and explain the types of garbage;

[0034] The paid reward module includes an identification and weighing module and a category comparison module, which are used to build an AI intelligent garbage recycling paid reward system, and use the AI ​​intelligent garbage recycling paid reward system to improve the enthusiasm of users in the management area to identify and classify;

[0035] The security detection module is used to conduct comprehensive and real security performance tests on artificial intelligence systems, reduce potential security risks of artificial intelligence systems, and ensure the security of user information and paid reward systems.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] Through the use of artificial intelligence, the present invention can intelligently supervise the garbage classification and delivery behavior of users in the management area, strengthen information publicity, and evaluate the feature recognition index of each recycling garbage category of users based on the classification and delivery situation and frequency of users in each recycling garbage category and the efficiency and habits of users in performing related delivery behaviors, and build a paid reward system to improve the enthusiasm of users in the management area for identification and classification, which significantly improves users' garbage classification behavior. At the same time, it increases the security protection of the system and protects the interests of users and investors. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the process of the present invention;

[0039] Figure 2 Schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] See also Figure 1-Figure 2 As shown, the present invention provides a technical solution: an AI-driven garbage intelligent identification and classification method, the method comprising:

[0042] Step S100: Delineating the management area of ​​the speech recognition video scene analysis artificial intelligence system based on the working area distribution of the speech recognition video scene analysis artificial intelligence system, the recognition area distribution of the face recognition device, and the area distribution of the trash can positions;

[0043] Wherein step S100 comprises:

[0044] Step S101: Obtain facial information and voice communication habits of people in the management area in the voice recognition video scene analysis artificial intelligence system to determine users to be served in the area;

[0045] Step S102: Determine the placement and distribution of trash cans in the management area, and use the facial recognition device to capture the best recognition point that meets the information recognition clarity requirement in front of the trash cans in the management area according to the placement and distribution of trash cans in the management area;

[0046] Step S103: Determine the maximum distance of the management area and install and debug the auxiliary equipment to the best state;

[0047] Step S200: popularizing knowledge of garbage classification to users in the management area, and determining the accuracy of personnel information and residential unit information in the management area;

[0048] Step S200 includes:

[0049] Among them, step S201: add voice propaganda equipment and post garbage classification propaganda posters in the management area, wherein the voice propaganda equipment avoids the user's rest period in the morning, noon and evening, and works after the user approaches the voice propaganda equipment at a set distance, posts the garbage classification propaganda poster in the propaganda column, and assists in expanding the propaganda of garbage classification brochures, etc.;

[0050] Step S202: clearly define the collection of user information in the management area, and take the identity information and time information when performing identity information verification, as well as the garbage image, garbage type and garbage classification conclusion information in the garbage bin, collect the corresponding identity information as the object, and sort the garbage image, garbage type and garbage classification conclusion information in the garbage bin according to the time information, and then count the number of consecutive times that the garbage classification conclusion information is correct, and bind the collected information with the user identity information and the residential unit information;

[0051] Step S300: construct an AI intelligent garbage recognition model, and use the AI ​​intelligent garbage recognition model to determine the historical garbage delivery records generated by users using garbage bins in the management area to extract feature information and classify and sort them;

[0052] Wherein, step S300 includes:

[0053] Step S301: Based on historical data acquisition, a garbage classification model for intelligent garbage identification and classification is constructed, and user classification placement information is imported into the garbage classification model to update model parameters, and a three-dimensional model of user information in the management area is obtained, and the model is imported into a convolutional neural network model for prediction, and prediction data of user classification placement of garbage locations is obtained, and the prediction data of user classification placement is imported into the three-dimensional model of user information in the management area to obtain the locations where users are accustomed to placing garbage in the management area, and whether the classification awareness is enhanced;

[0054] Step S302: Analyze the types of garbage that users are accustomed to placing in the management area, and obtain the living habits of relevant users;

[0055] Step S303: extracting feature information, filing and storing it, and importing it into a garbage classification model for intelligent garbage recognition and classification, so as to enhance the accuracy of using the garbage classification model for intelligent garbage recognition and classification;

[0056] Step S400: construct an AI intelligent garbage recycling paid reward system, and use the AI ​​intelligent garbage recycling paid reward system to improve the enthusiasm of users in the management area for identification and classification;

[0057] Wherein, step S400 includes:

[0058] Step S401: On the basis of the garbage classification model of intelligent garbage identification and classification, an AI intelligent garbage recycling paid reward system is constructed, weighing equipment and garbage category comparison display screen are added, the corresponding reward ratio is determined, and equivalent cash or virtual currency is issued to users;

[0059] Step S402: Establishing a mobile supermarket or a physical supermarket for the exchange of daily necessities, thereby forming an incentive mechanism to promote residents to actively participate in garbage sorting and recycling;

[0060] Step S500: Conduct a comprehensive and real safety performance test on the artificial intelligence system to reduce the potential safety risks of the artificial intelligence system and ensure the security of user information and paid reward system;

[0061] Wherein, step S500 includes:

[0062] Step S501: Acquire original image data, generate malicious sample data based on the original image data, perform security testing on the artificial intelligence system based on the malicious sample data, and obtain security testing results of the artificial intelligence system to simulate security attacks on the artificial intelligence system in a real environment, thereby achieving comprehensive and real security performance testing on the artificial intelligence system and reducing security risks of the artificial intelligence system;

[0063] Step S502: Malicious sample data includes malicious violent destruction and malicious data intrusion, and synchronously associates warnings;

[0064] Step S503: Ensure the security of user information and paid reward system.

[0065] In order to better implement the above method, an identification and classification system is also proposed, which includes a regional division management module, a relevant knowledge popularization module, a user information determination module, a garbage identification module, a feature information extraction and sorting module, a paid reward module, and a safety detection module;

[0066] The area division management module includes a camera, a facial recognition module and a voice recognition module, which is used to delineate the management area of ​​the voice recognition video scene analysis artificial intelligence system according to the working area distribution of the voice recognition video scene analysis artificial intelligence system, the recognition area distribution of the facial recognition device and the regional distribution of the placement of the trash cans;

[0067] The relevant knowledge popularization module and the user information determination module are used to popularize knowledge of garbage classification to users in the management area and determine the accuracy of personnel information and residential unit information in the management area;

[0068] The garbage identification module includes identifying recyclable garbage, non-recyclable garbage and other garbage, and is used to build an AI intelligent garbage identification model, and use the AI ​​intelligent garbage identification model to determine the historical garbage delivery records generated by users using garbage bins in the management area to extract feature information and classify and organize them;

[0069] The feature information extraction and sorting module is used to analyze the types and characteristics of garbage, and help users analyze and explain the types of garbage;

[0070] The paid reward module includes an identification and weighing module and a category comparison module, which are used to build an AI intelligent garbage recycling paid reward system, and use the AI ​​intelligent garbage recycling paid reward system to improve the enthusiasm of users in the management area to identify and classify;

[0071] The security detection module is used to conduct comprehensive and real security performance tests on artificial intelligence systems, reduce potential security risks of artificial intelligence systems, and ensure the security of user information and paid reward systems.

[0072] It is important to note that the construction and arrangement of the present application shown in various exemplary embodiments are only exemplary. Although only a few embodiments are described in detail in this disclosure, it should be easily understood by those who refer to this disclosure.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. An AI-driven garbage intelligent identification and classification method, characterized in that: The method comprises: Step S100: Delineating the management area of ​​the speech recognition video scene analysis artificial intelligence system based on the working area distribution of the speech recognition video scene analysis artificial intelligence system, the recognition area distribution of the face recognition device, and the area distribution of the trash can positions; Step S200: popularizing knowledge of garbage classification to users in the management area, and determining the accuracy of personnel information and residential unit information in the management area; Step S300: construct an AI intelligent garbage recognition model, and use the AI ​​intelligent garbage recognition model to determine the historical garbage delivery records generated by users using garbage bins in the management area to extract feature information and classify and sort them; Step S400: construct an AI intelligent garbage recycling paid reward system, and use the AI ​​intelligent garbage recycling paid reward system to improve the enthusiasm of users in the management area for identification and classification; Step S500: Conduct a comprehensive and real safety performance test on the artificial intelligence system to reduce the potential safety risks of the artificial intelligence system and ensure the security of user information and paid reward system; The step S100 includes: Step S101: Obtain facial information and voice communication habits of people in the management area in the voice recognition video scene analysis artificial intelligence system to determine users to be served in the area; Step S102: Determine the placement and distribution of trash cans in the management area, and use the facial recognition device to capture the best recognition point that meets the information recognition clarity requirement in front of the trash cans in the management area according to the placement and distribution of trash cans in the management area; Step S103: Determine the maximum distance of the management area and install and debug the auxiliary equipment to the best state; The step S200 includes: Step S201: Add voice propaganda equipment and post garbage classification propaganda posters in the management area, wherein the voice propaganda equipment avoids the user's rest period in the morning, noon and evening, and works after the user approaches the voice propaganda equipment at a set distance, posts the garbage classification propaganda posters in the propaganda column, and assists in expanding the propaganda by garbage classification brochures, etc.; Step S202: clearly define the collection of user information in the management area, and take the identity information and time information when performing identity information verification, as well as the garbage image, garbage type and garbage classification conclusion information in the garbage bin, collect the corresponding identity information as the object, and sort the garbage image, garbage type and garbage classification conclusion information in the garbage bin according to the time information, and then count the number of consecutive times that the garbage classification conclusion information is correct, and bind the collected information with the user identity information and the residential unit information; The step S300 includes: Step S301: Based on historical data acquisition, a garbage classification model for intelligent garbage identification and classification is constructed, and user classification placement information is imported into the garbage classification model to update model parameters, and a three-dimensional model of user information in the management area is obtained, and the model is imported into a convolutional neural network model for prediction, and prediction data of user classification placement of garbage locations is obtained, and the prediction data of user classification placement is imported into the three-dimensional model of user information in the management area to obtain the locations where users are accustomed to placing garbage in the management area, and whether the classification awareness is enhanced; Step S302: Analyze the types of garbage that users are accustomed to placing in the management area, and obtain the living habits of relevant users; Step S303: extracting feature information, filing and storing it, and importing it into a garbage classification model for intelligent garbage recognition and classification, so as to enhance the accuracy of using the garbage classification model for intelligent garbage recognition and classification; The step S400 includes: Step S401: On the basis of the garbage classification model of intelligent garbage identification and classification, an AI intelligent garbage recycling paid reward system is constructed, weighing equipment and garbage category comparison display screen are added, the corresponding reward ratio is determined, and equivalent cash or virtual currency is issued to users; Step S402: Establishing a mobile supermarket or a physical supermarket for the exchange of daily necessities, thereby forming an incentive mechanism to promote residents to actively participate in garbage sorting and recycling; The step S500 includes: Step S501: Acquire original image data, generate malicious sample data based on the original image data, perform security testing on the artificial intelligence system based on the malicious sample data, and obtain security testing results of the artificial intelligence system to simulate security attacks on the artificial intelligence system in a real environment, thereby achieving comprehensive and real security performance testing on the artificial intelligence system and reducing security risks of the artificial intelligence system; Step S502: Malicious sample data includes malicious violent destruction and malicious data intrusion, and synchronously associates warnings; Step S503: Ensure the security of user information and paid reward system.

2. According to claim 1, the AI-driven garbage intelligent identification and classification method recognition and classification system is characterized in that: The system includes a regional division management module, a relevant knowledge popularization module, a user information determination module, a garbage identification module, a feature information extraction and sorting module, a paid reward module, and a safety detection module; The area division management module includes a camera, a facial recognition module and a voice recognition module, which is used to delineate the management area of ​​the voice recognition video scene analysis artificial intelligence system according to the working area distribution of the voice recognition video scene analysis artificial intelligence system, the recognition area distribution of the facial recognition device and the regional distribution of the placement of the trash cans; The relevant knowledge popularization module and the user information determination module are used to popularize knowledge of garbage classification to users in the management area and determine the accuracy of personnel information and residential unit information in the management area; The garbage identification module includes identifying recyclable garbage, non-recyclable garbage and other garbage, and is used to build an AI intelligent garbage identification model, and use the AI ​​intelligent garbage identification model to determine the historical garbage delivery records generated by users using garbage bins in the management area to extract feature information and classify and organize them; The feature information extraction and sorting module is used to analyze the types and characteristics of garbage, and help users analyze and explain the types of garbage; The paid reward module includes an identification and weighing module and a category comparison module, which are used to build an AI intelligent garbage recycling paid reward system, and use the AI ​​intelligent garbage recycling paid reward system to improve the enthusiasm of users in the management area to identify and classify; The security detection module is used to conduct comprehensive and real security performance tests on artificial intelligence systems, reduce potential security risks of artificial intelligence systems, and ensure the security of user information and paid reward systems.

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