CN112183783A - Intelligent garbage classification method and system - Google Patents

Intelligent garbage classification method and system Download PDF

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CN112183783A
CN112183783A CN202011104131.6A CN202011104131A CN112183783A CN 112183783 A CN112183783 A CN 112183783A CN 202011104131 A CN202011104131 A CN 202011104131A CN 112183783 A CN112183783 A CN 112183783A
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CN112183783B (en
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张良虎
刘强
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Mingzhe Group Co ltd
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Abstract

The embodiment of the invention provides an intelligent garbage classification method and system, and belongs to the technical field of garbage classification. The method includes identifying account information of a user to throw garbage; collecting a first image of garbage to be thrown which is to be thrown by a user; determining whether the classification of the garbage to be thrown is correct according to the first image; if not, sending out prompt information; if the user selects the required classification help, sending a first hash value carrying a first virtual object deduction instruction to a block chain platform for uplink storage, and outputting correct classification information according to a first image; acquiring a second image of the garbage to be thrown after the user reclassifies; and if the garbage classification corresponding to the second image is correct, controlling the opening of a barrel cover of the garbage barrel. The method and the device can enable the user to still keep a pleasant classification mood under a complex garbage classification scene, and can guide the user to perform garbage classification in a help seeking mode when the user is wrongly classified, so that the accuracy of garbage classification is improved.

Description

Intelligent garbage classification method and system
Technical Field
The invention relates to the technical field of garbage classification, in particular to an intelligent garbage classification method and system.
Background
With the rapid development of economy, the daily garbage generated by people is increasing day by day, and the garbage classification can reduce the garbage treatment amount and treatment equipment, reduce the treatment cost and reduce the consumption of land resources.
At present, in some big cities in China, garbage classification is forcibly carried out, household garbage is classified into four categories of recyclable, harmful garbage, wet garbage and dry garbage according to relevant regulations, however, due to the fact that the classification mode is complicated, generally, users classify the household garbage through online videos or publicized pictures. However, such cumbersome garbage classification can be annoying and easily unclear to the user, resulting in inaccurate classification.
Disclosure of Invention
It is an object of the present invention to provide an intelligent garbage classification method which can improve the above-mentioned problems.
The embodiment of the invention is realized by the following steps:
in a first aspect, the invention provides an intelligent garbage classification method, which is applied to a garbage monitoring terminal, wherein the garbage monitoring terminal is arranged close to a garbage can placement area, and the method comprises the following steps: identifying account information of a user who wants to throw garbage; collecting a first image of the garbage to be thrown which is to be thrown by the user; determining whether the classification of the garbage to be thrown is correct according to the first image; if not, sending a prompt message to prompt the user that the garbage classification is wrong and whether classification help is required or not; if the user selects the required classification help, sending a first hash value carrying a first virtual object deduction instruction to a blockchain platform for uplink storage so as to enable the blockchain platform to deduct a corresponding number of virtual objects of the account information, wherein the virtual objects are used for extracting electronic certificates and outputting correct classification information according to the first image so as to enable the user to reclassify the garbage to be thrown based on the correct classification information; acquiring a second image of the garbage to be thrown after the user reclassifies; and if the garbage classification corresponding to the second image is correct, controlling a garbage can cover of the garbage can to be opened, so that the user can put the reclassified garbage to be thrown into the corresponding garbage can.
In the implementation process, the method and the device can enable the user to still keep a pleasant classification mood under a complex garbage classification scene, and can guide the user to perform garbage classification in a help seeking mode when the user is wrongly classified, so that the accuracy of the garbage classification is improved, and the user with little knowledge about the garbage classification can still correctly complete the garbage classification.
Optionally, the method further comprises: if the classification of the garbage to be thrown is correct, controlling the opening of a garbage can cover of the garbage can; determining whether the garbage thrown into the garbage can by the user is matched with the type of the garbage to be thrown; if so, sending a second hash value carrying a virtual object adding instruction to a block chain platform so that the block chain platform adds virtual objects with the number corresponding to the second hash value on the account information; if not, sending alarm information to warn the user to take out the wrong and still garbage from the garbage can and put the garbage into the corresponding garbage can again; and sending a third hash value carrying a second virtual object deduction instruction to a blockchain platform so that the blockchain platform deducts a virtual object matched with the third hash value from the account information.
In the implementation process, after the user is determined to classify the garbage correctly, whether the user throws the garbage into the garbage can of the pair is monitored again, so that when the user throws the garbage in error, alarm information can be sent out to warn the user to take out the garbage which is still in error from the garbage can and put the garbage into the corresponding garbage can again; and sending a third hash value carrying a second virtual object deduction instruction to a blockchain platform so that the blockchain platform deducts a virtual object matched with the third hash value from the account information. And when the user throws the pair, the number of the virtual objects which can give the response is increased, so that the user can be satisfied, the user can better classify the garbage and correctly throw the garbage at the later stage, and the popularization of garbage classification is improved.
Optionally, the account information identifying the user to throw garbage includes: collecting a face image of the user who throws the garbage; extracting the face features of the face image; inputting the human face features into a neural network model to obtain a recognition result, wherein the neural network model is trained in advance; judging whether the recognition result is matched with a prestored face image, wherein the prestored face image is an image input by a user when the user creates a user account in the block chain platform, and the prestored face image is stored in the block chain platform and the garbage monitoring terminal; if not, sending card reading prompt information to prompt the user to insert a user identity card, wherein the user identity card is issued in advance and is bound with the garbage monitoring terminal; reading account information corresponding to the user identity card; and if the recognition result is matched with the prestored face image, determining account information matched with the recognition result.
In the implementation process, the identity of the user who throws the garbage is firstly identified to determine the account information of the user, if the user is the user corresponding to the account information, the account information of the user is determined directly according to the collected face image, and if the user is not the user who establishes the account information, the account information of the user who throws the garbage is accurately acquired by prompting the user who throws the garbage to read the card (for example, inserting the identity card or attaching the identity card to a card reading area of a garbage monitoring terminal), so that the account information which is wrongly matched is prevented from being matched with the user who throws the garbage, and the event which throws the garbage is conveniently managed.
Optionally, the method further comprises: displaying the current total virtual object of the account information; recommending corresponding electronic certificates according to the total virtual object, wherein the electronic certificates comprise certificates for extracting actual articles and certificates for extracting virtual articles, and the virtual articles comprise times for helping the user to perform garbage classification.
In the implementation process, after the user correctly throws away the garbage, the current total virtual object of the account information is displayed, and the corresponding electronic certificate is recommended to the user, so that the interest of the user in garbage classification can be improved, the user can be promoted to complete the expected target at an early point, the experience of the user in garbage classification is improved, and the user can perform garbage classification at will.
Optionally, the method further comprises: acquiring the wish item information of the account information; determining a second virtual object corresponding to the wish item information; determining a difference between the second virtual object and the total virtual object; and amplifying and displaying the difference value, and popping up incentive information to encourage a user corresponding to the account information to extract the electronic certificate corresponding to the wish item information.
In the implementation process, the difference value between the total virtual object under the account information and the second virtual object required by extracting the wish object information is given by acquiring the wish object information under the account information, the difference value is amplified and displayed, so that the user can view the difference more visually, the incentive information is popped up to encourage the user to make up the difference in the early days, and further the wish objects are extracted, so that the user can obtain the corresponding virtual object after finishing the garbage classification once correctly in the garbage classification process, the user can classify the garbage rapidly, and the interest of the user in garbage classification can be improved.
Optionally, the outputting correct classification information according to the first image includes: extracting a characteristic image of each rubbish in the first image; determining a preset classification type corresponding to each feature image, wherein the preset classification type is pre-stored classification information, and the classification information comprises dry garbage, wet garbage, kitchen garbage, harmful garbage and recoverable garbage; marking the preset classification type on the corresponding characteristic image to obtain a marked image; and displaying the marked image.
In the implementation process, the characteristic images of the first image are extracted, so that each characteristic image is labeled and classified, the labeled images are displayed, a user can rapidly finish garbage classification by referring to the labeled images, the classification time is saved, and the understanding of each type of garbage can be deepened.
Optionally, the method further comprises: receiving garbage classification help seeking information sent by a mobile terminal, wherein the garbage classification help seeking information carries account information; verifying whether the residual virtual objects in the account information are smaller than the help seeking payment virtual object corresponding to the garbage classification help seeking information; if not, sending response information to the mobile terminal, and receiving a junk image returned by the mobile terminal based on the response information; classifying and marking the garbage images to obtain marked garbage images; and sending the marked junk images to the mobile terminal to help a user to classify the junk based on the marked junk images.
In the implementation process, the user initiatively initiates the garbage classification help seeking information, so that the user can classify the garbage in a help seeking mode when the user does not know how to classify the garbage, the user does not need to feel fidgety to the garbage classification, and after the user initiates the garbage classification help seeking information, the user is encouraged to independently complete the garbage classification in a mode of deducting a help seeking payment virtual object, and the independent completion degree of the user on the garbage classification is further improved.
In a second aspect, the present application further provides an intelligent garbage classification method, where the method is applied to a blockchain platform, and the method includes: acquiring a first hash value which is sent by a garbage monitoring terminal and carries a first virtual object deduction instruction, wherein the first virtual object deduction instruction carries account information, a deduction virtual object and a deduction reason; analyzing the account information carried by the first hash value; deducting the number of virtual objects matched with the deduction virtual object from the account information; and performing uplink on the deduction reason and the residual virtual objects after deduction.
In the implementation process, the method encourages the user to classify the garbage in a mode of deducting or newly adding the virtual object so as to improve the interest degree of the user in garbage classification, so that the user can overcome the defect that the user does not feel bored under the complicated garbage classification, and the garbage can be accurately classified.
In a third aspect, the present application further provides an intelligent garbage classification system, where the system is applied to a garbage monitoring terminal, the garbage monitoring terminal is close to a garbage can placement area, and the system includes: the identification module is used for identifying account information of a user who wants to throw garbage; the collection module is used for collecting a first image of the garbage to be thrown, which is to be thrown by the user; the first processing module is used for determining whether the classification of the garbage to be thrown is correct or not according to the first image; the sending module is used for sending prompt information to prompt the user that the garbage classification is wrong or whether classification help is required if the garbage classification is not wrong; a second processing module, configured to send a first virtual object deduction instruction to a blockchain platform for uplink storage if the user selects a required classification help, so that the blockchain platform deducts a number of virtual objects in the account information corresponding to the first virtual object deduction instruction, where the virtual objects are used to extract an electronic certificate and output correct classification information according to the first image, so that the user reclassifies the garbage to be thrown based on the correct classification information; the acquisition module is used for acquiring a second image of the garbage to be thrown after the user reclassifies; and the control module is used for controlling the opening of a barrel cover of the garbage can if the garbage classification corresponding to the second image is correct, so that the user can put the reclassified garbage to be thrown into the corresponding garbage can.
In a fourth aspect, the present application further provides an intelligent garbage classification system, where the system is applied to a block chain platform, and the system includes: the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a first hash value which is sent by a garbage monitoring terminal and carries a first virtual object deduction instruction, and the first virtual object deduction instruction carries account information, a deduction virtual object and a deduction reason; the analysis unit is used for analyzing the account information carried by the first hash value; the processing unit is used for deducting the number of the virtual objects matched with the deduction virtual objects from the account information; and a cochain unit for cochaining the deduction reason and the remaining virtual objects after deduction.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of an intelligent garbage classification method according to an embodiment of the present invention;
fig. 2 is a flowchart of an intelligent garbage classification method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an intelligent garbage classification system according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an intelligent garbage classification system according to a fourth embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The first embodiment is as follows:
referring to a flowchart of an intelligent garbage classification method shown in fig. 1, the method is applied to a garbage monitoring terminal, the garbage monitoring terminal is arranged close to a garbage can placement area, and the method specifically includes the following steps:
in step S201, account information of a user who wants to throw garbage is identified.
Alternatively, the trash to be thrown is the trash that the user is about to throw into the trash. The litter may be sorted or unsorted or misclassified. Here, the number of the carbon atoms is not particularly limited.
The account information is a pre-established account, and certainly, an account may be created when it is verified that the user or its associated user does not register an account.
Optionally, the account information includes an account name and a virtual object.
Optionally, the virtual object comprises an integral.
Optionally, the virtual object comprises virtual currency. The virtual currency may be used to extract real items and/or virtual items.
For example, it is assumed that the spam monitoring terminal is installed in a corridor of a cell, and each owner has account information. If the spam monitoring terminal is installed in a public area, such as a roadside or a garden of a community, each user may have one account information, or of course, one owner may have one account information. Here, the number of the carbon atoms is not particularly limited.
As an embodiment, step S201 includes: collecting a face image of the user who throws the garbage; extracting the face features of the face image; inputting the human face features into a neural network model to obtain a recognition result, wherein the neural network model is trained in advance; judging whether the recognition result is matched with a prestored face image, wherein the prestored face image is an image input by a user when the user creates a user account in the block chain platform, and the prestored face image is stored in the block chain platform and the garbage monitoring terminal; if not, sending card reading prompt information to prompt the user to insert a user identity card, wherein the user identity card is issued in advance and is bound with the garbage monitoring terminal; reading account information corresponding to the user identity card; and if the recognition result is matched with the prestored face image, determining account information matched with the recognition result.
The identity card may be a virtual card, such as a two-dimensional code. For example, when a user reads a card, the two-dimensional code can be opened for the garbage monitoring terminal to read the card.
Of course, in actual use, the identity card may also be a physical card.
In the implementation process, the identity of the user who throws the garbage is firstly identified to determine the account information of the user, if the user is the user corresponding to the account information, the account information of the user is directly determined according to the collected face image, and if the user is not the user who establishes the account information, the account information of the user who throws the garbage is accurately obtained by prompting the user who throws the garbage to read the card (for example, inserting the identity card or attaching the identity card to a card reading area of a garbage monitoring terminal), so that the account information which is wrongly matched is prevented from being sent to the user who throws the garbage, and the event which throws the garbage is conveniently managed.
Step S202, collecting a first image of the garbage to be thrown which is to be thrown by the user.
As an embodiment, a camera on the garbage monitoring terminal may be utilized to capture a first image of garbage that a user is about to throw.
Alternatively, the first image may be a plurality of, for example, a plurality of first images of different angles.
Step S203, determining whether the classification of the garbage to be thrown is correct according to the first image.
As an embodiment, a first image is segmented (for example, segmented by convolution), the segmented sub-images are classified, and then the classified sub-images are confirmed according to a preset garbage classification to see whether all the garbage in the first image belongs to the same garbage classification, if yes, the classification is correct, otherwise, the classification is incorrect.
And step S204, if not, sending a prompt message to prompt the user that the garbage classification is wrong and whether classification help is required.
Optionally, the prompt information may be a prompt of the garbage monitoring terminal in a voice manner.
Of course, the prompt information may also be sent out by displaying on the display interface of the garbage monitoring terminal.
Optionally, the demand classification help includes descriptive information of "help classification", and/or descriptive information of "prompt classification".
For example, if the user selects "help classification", the garbage monitoring terminal will give the correct classification of the garbage to be thrown by the user, so that the user can quickly reclassify according to the given correct classification, thereby improving the user experience and saving time. If select "suggestion is categorised" later, rubbish monitoring terminal can give guide information to guide the user to carry out automatic reclassification, can cultivate the user to rubbish categorised further cognition, strengthen rubbish classification experience, make when throwing away rubbish, can also strengthen the study to rubbish classification, so that this user later stage can accurately treat to throw away rubbish and classify.
Step S205, if the user selects the required classification help, sending a first hash value carrying a first virtual object deduction instruction to a blockchain platform for uplink storage, so that the blockchain platform deducts a number of virtual objects corresponding to the account information, and outputting correct classification information according to the first image, so that the user reclassifies the garbage to be thrown based on the correct classification information.
Wherein the virtual object is used to extract electronic credentials. The electronic voucher is used to redeem or purchase an item.
Optionally, the number of virtual objects to be deducted by the first virtual object deduction instruction may be 1, or may be 2 or an integer greater than 2. Here, the number of the carbon atoms is not particularly limited.
Optionally, when the user creates account information, 100 virtual objects are automatically bound under the account information.
Of course, in actual use, the number of virtual objects bound to the account information during creation may be set according to actual requirements, and is not specifically limited herein.
In the implementation process, when the user newly creates account information, 100 virtual objects are bound to the account information, so that on one hand, for a user who does not know how to perform garbage classification, the user can better learn while performing a garbage throwing process by using the 100 virtual objects, the user is helped to perform garbage classification, and the cognition degree and the mastery degree of the user on the garbage classification are improved. On the other hand, the way that the electronic certificate can be extracted through the virtual object enables the user to be more interested in obtaining the virtual object, further the boring caused by garbage classification is avoided, and the user can throw garbage happily.
Optionally, the outputting correct classification information according to the first image includes: extracting a characteristic image of each rubbish in the first image; determining a preset classification type corresponding to each feature image, wherein the preset classification type is pre-stored classification information, and the classification information comprises dry garbage, wet garbage, kitchen garbage, harmful garbage and recoverable garbage; marking the preset classification type on the corresponding characteristic image to obtain a marked image; and displaying the marked image.
In the implementation process, the feature images of the first image are extracted, so that each feature image is labeled and classified, and the labeled images are displayed, so that a user can quickly finish garbage classification by referring to the labeled images, the classification time is saved, and the knowledge of each type of garbage can be deepened.
Step S206, acquiring a second image of the garbage to be thrown after the user reclassifies.
As an application scenario, after the user selects the required classification help, the garbage monitoring terminal re-collects the image (i.e., the second image) of the garbage to be thrown after the user reclassifies after a certain time.
The fixed time may be 10 minutes or 3 minutes.
Certainly, the time for actively triggering after the user reclassifies the classification of the garbage can be also used, for example, after the user classifies the garbage, the user clicks a display interface of the garbage monitoring terminal, and the garbage monitoring terminal actively acquires images after 3 seconds (a certain time) interval. Here, the number of the carbon atoms is not particularly limited.
Step S207, if the garbage classification corresponding to the second image is correct, controlling a can cover of the garbage can to be opened, so that the user can put the reclassified garbage to be thrown into the corresponding garbage can.
In a possible embodiment, the method for intelligently classifying garbage further includes: if the classification of the garbage to be thrown is correct, controlling the opening of a garbage can cover of the garbage can; determining whether the garbage thrown into the garbage can by the user is matched with the type of the garbage to be thrown; if so, sending a second hash value carrying a virtual object adding instruction to a block chain platform so that the block chain platform adds virtual objects with the number corresponding to the second hash value on the account information; if not, sending alarm information to warn the user to take out the wrong and still garbage from the garbage can and put the garbage into the corresponding garbage can again; and sending a third hash value carrying a second virtual object deduction instruction to a blockchain platform so that the blockchain platform deducts a virtual object matched with the third hash value from the account information.
Wherein determining whether the trash thrown into the trash can by the user matches the type of the trash to be thrown includes: and acquiring an image of the user throwing the garbage to be thrown into the garbage can, and determining whether the user correctly throws the garbage to be thrown into the garbage can matched with the garbage to be thrown according to the image.
For example, suppose the user correctly sorts the waste, e.g. wet waste is all bagged with the same garbage bag, but wet waste is thrown into a garbage can where dry waste is placed.
Optionally, the virtual object adding instruction is used to add a certain number of new virtual objects to the virtual object under the account information, for example, 2 virtual objects may be added, or 20 virtual objects may be added. Here, the number of the carbon atoms is not particularly limited.
Optionally, the second virtual object deduction instruction is configured to deduct a certain number of virtual objects from the virtual objects of the account information, for example, deduct 1 or more. Here, the number of the carbon atoms is not particularly limited.
Optionally, the number of virtual objects deducted by the second virtual object deduction instruction is smaller than the number of virtual objects deducted by the first virtual object deduction instruction.
In the implementation process, after the user is determined to classify the garbage correctly, whether the user throws the garbage into the garbage can of the pair is monitored again, so that when the user throws the garbage in error, alarm information can be sent out to warn the user to take out the garbage which is still in error from the garbage can and put the garbage into the corresponding garbage can again; and sending a third hash value carrying a second virtual object deduction instruction to a blockchain platform so that the blockchain platform deducts a virtual object matched with the third hash value from the account information. And when the user throws the pair, the number of the virtual objects which can give the response is increased, so that the user can be satisfied, the user can better classify the garbage and correctly throw the garbage at the later stage, and the popularization of garbage classification is improved.
In a possible embodiment, the method for intelligently classifying garbage further includes: displaying the current total virtual object of the account information; recommending corresponding electronic certificates according to the total virtual object, wherein the electronic certificates comprise certificates for extracting actual articles and certificates for extracting virtual articles, and the virtual articles comprise times for helping the user to perform garbage classification.
In the implementation process, after the user correctly throws away the garbage, the current total virtual object of the account information is displayed, and the corresponding electronic certificate is recommended to the user, so that the interest of the user in garbage classification can be improved, the user can be promoted to finish the expected target at an early point, the experience of the user on garbage classification is improved, and the user can perform garbage classification at will.
In a possible embodiment, the method for intelligently classifying garbage further includes: acquiring the wish item information of the account information; determining a second virtual object corresponding to the wish item information; determining a difference between the second virtual object and the total virtual object; and amplifying and displaying the difference value, and popping up incentive information to encourage a user corresponding to the account information to extract the electronic certificate corresponding to the wish item information.
Alternatively, the specific value of the second virtual object may be set according to actual requirements, for example, according to the importance degree of different articles, and is not limited specifically herein.
Optionally, the step of displaying the difference in an enlarged manner means displaying the difference in an enlarged manner on the display interface, for example, the difference may be displayed in an enlarged manner by 5 times, or may be displayed in an enlarged manner by other times, and the display is not limited specifically herein.
Optionally, the incentive information includes descriptive information describing "a difference from the obtained wish item information" and describing "a time from which the wish item information was obtained and/or a number of times the garbage classification is correctly completed" or the like.
In the implementation process, the difference value between the total virtual object under the account information and the second virtual object required by extracting the wish object information is given by acquiring the wish object information under the account information, the difference value is amplified and displayed, so that the user can view the difference more visually, the incentive information is popped up to encourage the user to make up the difference in the early days, and further the wish objects are extracted, so that the user can obtain the corresponding virtual object after finishing the garbage classification once correctly in the garbage classification process, the user can classify the garbage rapidly, and the interest of the user in garbage classification can be improved.
In a possible embodiment, the method for intelligently classifying garbage further includes: receiving garbage classification help seeking information sent by a mobile terminal, wherein the garbage classification help seeking information carries account information; verifying whether the residual virtual objects in the account information are smaller than the help seeking payment virtual object corresponding to the garbage classification help seeking information; if not, sending response information to the mobile terminal, and receiving a junk image returned by the mobile terminal based on the response information; classifying and marking the garbage images to obtain marked garbage images; and sending the marked junk images to the mobile terminal to help a user to classify the junk based on the marked junk images.
As an application scenario, a user may actively initiate the garbage classification help-seeking information before throwing garbage, that is, during garbage classification, through a mobile terminal (e.g., a mobile phone or a nearby or wearable device), or initiate the garbage classification help-seeking information after primarily completing classification.
In the implementation process, the user initiatively initiates the garbage classification help seeking information, so that the user can classify the garbage in a help seeking mode when the user does not know how to classify the garbage, the user does not need to feel fidgety to the garbage classification, and after the user initiates the garbage classification help seeking information, the user is encouraged to independently complete the garbage classification in a mode of deducting a help seeking payment virtual object, and the independent completion degree of the user on the garbage classification is further improved.
According to the intelligent garbage classification method, account information of a user who wants to throw garbage is identified; collecting a first image of the garbage to be thrown which is to be thrown by the user; determining whether the classification of the garbage to be thrown is correct according to the first image; if not, sending a prompt message to prompt the user that the garbage classification is wrong and whether classification help is required or not; if the user selects the required classification help, sending a first hash value carrying a first virtual object deduction instruction to a blockchain platform for uplink storage so as to enable the blockchain platform to deduct a corresponding number of virtual objects of the account information, wherein the virtual objects are used for extracting electronic certificates and outputting correct classification information according to the first image so as to enable the user to reclassify the garbage to be thrown based on the correct classification information; acquiring a second image of the garbage to be thrown after the user reclassifies; and if the garbage classification corresponding to the second image is correct, controlling a garbage can cover of the garbage can to be opened, so that the user can put the reclassified garbage to be thrown into the corresponding garbage can. Therefore, the users still keep a pleasant classification mood under the complicated garbage classification scene, and when the classification of the users is wrong, the users can be guided to perform garbage classification in a help seeking mode, so that the accuracy of the garbage classification is improved, and the users with little knowledge of the garbage classification can still correctly complete the garbage classification.
Example two:
referring to a flowchart of an intelligent garbage classification method shown in fig. 2, the method is applied to a blockchain platform, and specifically includes the following steps:
step S301, a first hash value carrying a first virtual object deduction instruction sent by the garbage monitoring terminal is obtained.
The first virtual object deduction instruction carries account information, a deduction virtual object and a deduction reason.
Optionally, the virtual object comprises an integral.
Optionally, the virtual object comprises virtual currency. The virtual currency may be used to extract real items and/or virtual items.
Step S302, the account information carried by the first hash value is analyzed.
Step S303, deduct the number of virtual objects matching the deducted virtual object from the account information.
Step S304, uplink is performed on the deduction reason and the remaining virtual objects after deduction.
According to the intelligent garbage classification method, the garbage is encouraged to be classified by the user in a mode of deducting or newly adding a virtual object, so that the interest degree of the user in garbage classification is improved, further the user can overcome the defect that the user does not feel bored under the complicated garbage classification, and the garbage can be accurately classified.
Example three:
referring to fig. 3, the system 400 is applied to a trash monitoring terminal, the trash monitoring terminal is disposed near a trash can placement area, and the system 400 includes:
an identification module 410 for identifying account information of a user to throw garbage.
A collecting module 420, configured to collect a first image of the garbage to be thrown by the user.
A first processing module 430, configured to determine whether the classification of the garbage to be thrown is correct according to the first image.
And the sending module 440 is configured to send a prompt message to prompt the user that the garbage classification is wrong and whether a classification help is required if the garbage classification is wrong.
A second processing module 450, configured to send a first virtual object deduction instruction to a blockchain platform for uplink storage if the user selects the required classification help, so that the blockchain platform deducts a number of virtual objects in the account information corresponding to the first virtual object deduction instruction, where the virtual objects are used to extract an electronic certificate and output correct classification information according to the first image, so that the user reclassifies the garbage to be thrown based on the correct classification information.
An obtaining module 460, configured to obtain a second image of the garbage to be thrown after the user reclassifies.
The control module 470 is configured to control the opening of the trash can cover of the trash can if the trash classification corresponding to the second image is correct, so that the user puts the reclassified trash to be thrown into the corresponding trash can.
It should be noted that, for specific functions of the intelligent garbage classification system 400 shown in this embodiment, reference may be made to the method flow shown in the first embodiment, and details are not described herein again.
Example four:
referring to fig. 4, an intelligent garbage classification system 500 is applied to a blockchain platform, and the intelligent garbage classification system 500 includes:
an obtaining unit 510, configured to obtain a first hash value that is sent by the spam monitoring terminal and carries a first virtual object deduction instruction, where the first virtual object deduction instruction carries account information, a deduction virtual object, and a deduction reason.
An analyzing unit 520, configured to analyze the account information carried by the first hash value.
A processing unit 530, configured to deduct, from the account information, the number of virtual objects matching the deducted virtual object.
A uplink unit 540, configured to uplink the deduction reason and the residual virtual objects after deduction.
It should be noted that, for specific functions of the intelligent garbage classification system 500 shown in this embodiment, reference may be made to the method flow shown in the second embodiment, and details are not described herein again.
Further, the present embodiment also provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processing device, the method for intelligently classifying garbage provided in the foregoing embodiment is performed.
Further, an embodiment of the present application further provides a computer program product of the method and system for intelligently classifying spam, which includes a computer-readable storage medium storing program codes, where instructions included in the program codes may be used to execute the method described in the foregoing method embodiment, and specific implementation may refer to the method embodiment, which is not described herein again.
It should be noted that the above functions, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The method for intelligently classifying the garbage is applied to a garbage monitoring terminal, the garbage monitoring terminal is arranged close to a garbage can placement area, and the method comprises the following steps:
identifying account information of a user who wants to throw garbage;
collecting a first image of the garbage to be thrown which is to be thrown by the user;
determining whether the classification of the garbage to be thrown is correct according to the first image;
if not, sending a prompt message to prompt the user that the garbage classification is wrong and whether classification help is required or not;
if the user selects the required classification help, sending a first hash value carrying a first virtual object deduction instruction to a blockchain platform for uplink storage so as to enable the blockchain platform to deduct a corresponding number of virtual objects of the account information, wherein the virtual objects are used for extracting electronic certificates and outputting correct classification information according to the first image so as to enable the user to reclassify the garbage to be thrown based on the correct classification information;
acquiring a second image of the garbage to be thrown after the user reclassifies;
and if the garbage classification corresponding to the second image is correct, controlling a garbage can cover of the garbage can to be opened, so that the user can put the reclassified garbage to be thrown into the corresponding garbage can.
2. The intelligent garbage classification method according to claim 1, further comprising:
if the classification of the garbage to be thrown is correct, controlling the opening of a garbage can cover of the garbage can;
determining whether the garbage thrown into the garbage can by the user is matched with the type of the garbage to be thrown;
if so, sending a second hash value carrying a virtual object adding instruction to a block chain platform so that the block chain platform adds virtual objects with the number corresponding to the second hash value on the account information;
if not, sending alarm information to warn the user to take out the wrong and still garbage from the garbage can and put the garbage into the corresponding garbage can again; and sending a third hash value carrying a second virtual object deduction instruction to a blockchain platform so that the blockchain platform deducts a virtual object matched with the third hash value from the account information.
3. The intelligent garbage classification method according to claim 1, wherein the account information for identifying the user to throw garbage comprises:
collecting a face image of the user who throws the garbage;
extracting the face features of the face image;
inputting the human face features into a neural network model to obtain a recognition result, wherein the neural network model is trained in advance;
judging whether the recognition result is matched with a prestored face image, wherein the prestored face image is an image input by a user when the user creates a user account in the block chain platform, and the prestored face image is stored in the block chain platform and the garbage monitoring terminal;
if not, sending card reading prompt information to prompt the user to insert a user identity card, wherein the user identity card is issued in advance and is bound with the garbage monitoring terminal;
reading account information corresponding to the user identity card;
and if the recognition result is matched with the prestored face image, determining account information matched with the recognition result.
4. The intelligent garbage classification method according to any one of claims 1-3, further comprising:
displaying the current total virtual object of the account information;
recommending corresponding electronic certificates according to the total virtual object, wherein the electronic certificates comprise certificates for extracting actual articles and certificates for extracting virtual articles, and the virtual articles comprise times for helping the user to perform garbage classification.
5. The intelligent garbage classification method according to claim 4, further comprising:
acquiring the wish item information of the account information;
determining a second virtual object corresponding to the wish item information;
determining a difference between the second virtual object and the total virtual object;
and amplifying and displaying the difference value, and popping up incentive information to encourage a user corresponding to the account information to extract the electronic certificate corresponding to the wish item information.
6. The intelligent garbage classification method according to claim 1, wherein the outputting correct classification information according to the first image comprises:
extracting a characteristic image of each rubbish in the first image;
determining a preset classification type corresponding to each feature image, wherein the preset classification type is pre-stored classification information, and the classification information comprises dry garbage, wet garbage, kitchen garbage, harmful garbage and recoverable garbage;
marking the preset classification type on the corresponding characteristic image to obtain a marked image;
and displaying the marked image.
7. The intelligent garbage classification method according to claim 1, further comprising:
receiving garbage classification help seeking information sent by a mobile terminal, wherein the garbage classification help seeking information carries account information;
verifying whether the residual virtual objects in the account information are smaller than the help seeking payment virtual object corresponding to the garbage classification help seeking information;
if not, sending response information to the mobile terminal, and receiving a junk image returned by the mobile terminal based on the response information;
classifying and marking the garbage images to obtain marked garbage images;
and sending the marked junk images to the mobile terminal to help a user to classify the junk based on the marked junk images.
8. An intelligent garbage classification method is applied to a blockchain platform, and comprises the following steps:
acquiring a first hash value which is sent by a garbage monitoring terminal and carries a first virtual object deduction instruction, wherein the first virtual object deduction instruction carries account information, a deduction virtual object and a deduction reason;
analyzing the account information carried by the first hash value;
deducting the number of virtual objects matched with the deduction virtual object from the account information;
and performing uplink on the deduction reason and the residual virtual objects after deduction.
9. The utility model provides an intelligent classification rubbish system, its characterized in that, the system is applied to rubbish monitor terminal, rubbish monitor terminal is close to the garbage bin and places regional setting, the system includes:
the identification module is used for identifying account information of a user who wants to throw garbage;
the collection module is used for collecting a first image of the garbage to be thrown, which is to be thrown by the user;
the first processing module is used for determining whether the classification of the garbage to be thrown is correct or not according to the first image;
the sending module is used for sending prompt information to prompt the user that the garbage classification is wrong or whether classification help is required if the garbage classification is not wrong;
a second processing module, configured to send a first virtual object deduction instruction to a blockchain platform for uplink storage if the user selects a required classification help, so that the blockchain platform deducts a number of virtual objects in the account information corresponding to the first virtual object deduction instruction, where the virtual objects are used to extract an electronic certificate and output correct classification information according to the first image, so that the user reclassifies the garbage to be thrown based on the correct classification information;
the acquisition module is used for acquiring a second image of the garbage to be thrown after the user reclassifies;
and the control module is used for controlling the opening of a barrel cover of the garbage can if the garbage classification corresponding to the second image is correct, so that the user can put the reclassified garbage to be thrown into the corresponding garbage can.
10. An intelligent garbage classification system, which is applied to a block chain platform, and comprises:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a first hash value which is sent by a garbage monitoring terminal and carries a first virtual object deduction instruction, and the first virtual object deduction instruction carries account information, a deduction virtual object and a deduction reason;
the analysis unit is used for analyzing the account information carried by the first hash value;
the processing unit is used for deducting the number of the virtual objects matched with the deduction virtual objects from the account information;
and a cochain unit for cochaining the deduction reason and the remaining virtual objects after deduction.
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Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20170109273A (en) * 2016-03-21 2017-09-29 김다은 Smart recycling bin
CN108839977A (en) * 2018-06-08 2018-11-20 湖南万容普联再生资源有限公司 A kind of system of Waste sorting recycle, method and device
CN109299792A (en) * 2018-08-21 2019-02-01 杭州复杂美科技有限公司 Garbage classification motivational techniques and device, equipment and storage medium
CN109299793A (en) * 2018-08-21 2019-02-01 杭州复杂美科技有限公司 Garbage classification motivational techniques and device, equipment and storage medium
CN109684979A (en) * 2018-12-18 2019-04-26 深圳云天励飞技术有限公司 A kind of refuse classification method based on image recognition technology, device and electronic equipment
CN110222676A (en) * 2019-07-04 2019-09-10 谷建勇 A kind of garbage classification learning system and its application method
US20190392403A1 (en) * 2018-06-22 2019-12-26 Antonio Alfredo Rainaldi Collecting and sorting garbage and managing recycling using sensing technology
CN110851866A (en) * 2019-11-12 2020-02-28 福建福链科技有限公司 Garbage classification method and system based on block chain
CN110902193A (en) * 2019-10-25 2020-03-24 西安西电链融科技有限公司 Face recognition-based garbage classification management system, method and device
CN110991524A (en) * 2019-11-29 2020-04-10 山东爱城市网信息技术有限公司 Garbage classification management method, device and medium based on block chain
JP2020064564A (en) * 2018-10-19 2020-04-23 株式会社アスカネット Learning server, learning system, and additional learning program
CN111498327A (en) * 2020-04-13 2020-08-07 广州东软科技有限公司 System and method for improving garbage classification accuracy based on block chain technology

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20170109273A (en) * 2016-03-21 2017-09-29 김다은 Smart recycling bin
CN108839977A (en) * 2018-06-08 2018-11-20 湖南万容普联再生资源有限公司 A kind of system of Waste sorting recycle, method and device
US20190392403A1 (en) * 2018-06-22 2019-12-26 Antonio Alfredo Rainaldi Collecting and sorting garbage and managing recycling using sensing technology
CN109299792A (en) * 2018-08-21 2019-02-01 杭州复杂美科技有限公司 Garbage classification motivational techniques and device, equipment and storage medium
CN109299793A (en) * 2018-08-21 2019-02-01 杭州复杂美科技有限公司 Garbage classification motivational techniques and device, equipment and storage medium
JP2020064564A (en) * 2018-10-19 2020-04-23 株式会社アスカネット Learning server, learning system, and additional learning program
CN109684979A (en) * 2018-12-18 2019-04-26 深圳云天励飞技术有限公司 A kind of refuse classification method based on image recognition technology, device and electronic equipment
CN110222676A (en) * 2019-07-04 2019-09-10 谷建勇 A kind of garbage classification learning system and its application method
CN110902193A (en) * 2019-10-25 2020-03-24 西安西电链融科技有限公司 Face recognition-based garbage classification management system, method and device
CN110851866A (en) * 2019-11-12 2020-02-28 福建福链科技有限公司 Garbage classification method and system based on block chain
CN110991524A (en) * 2019-11-29 2020-04-10 山东爱城市网信息技术有限公司 Garbage classification management method, device and medium based on block chain
CN111498327A (en) * 2020-04-13 2020-08-07 广州东软科技有限公司 System and method for improving garbage classification accuracy based on block chain technology

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
宦菁;: "智能让垃圾分类不再复杂", 风流一代, no. 03, pages 18 - 19 *
肖波雄;李博宇;张琼;黄波;: "智能垃圾桶与垃圾分类小程序结合的应用研究", 电脑知识与技术, no. 25, pages 108 - 110 *
赵刚;: ""五力"协同 创新垃圾分类现代管理模式――北京市东城区建国门街道探索垃圾分类区块链管理的实践", 城市管理与科技, no. 06, pages 74 - 76 *

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