Garbage classification recycling excitation method and system

Abstract

The invention discloses a garbage classification recycling excitation method and system. The weight, classification accuracy, classification participation frequency and variety diversity of garbage are comprehensively considered. The weight of the garbage is the most direct influence factor, the classification accuracy of the garbage reflects the accuracy degree of garbage classification of the user, the classification participation frequency of the garbage reflects the enthusiasm and continuity of the user participating in garbage classification, and the variety diversity of the garbage reflects the recognition and treatment capacity of the user on different types of garbage. The four factors jointly influence an integral calculation value in garbage classification and recovery excitation, so that the accuracy and the fairness of integral calculation are improved, garbage classification behaviors of the user can be comprehensively evaluated, and the user is excited to more actively participate in garbage classification and recovery activities.

Description

Technical Field

[0001] The present invention belongs to the field of garbage classification and recycling, and in particular relates to a garbage classification and recycling incentive method and system. Background Art

[0002] With the acceleration of urbanization and population growth, the amount of domestic waste has increased dramatically, bringing great pressure to the environment. As an effective way to solve the problem of domestic waste, waste sorting has been widely promoted around the world. However, in actual operation, due to the complex waste sorting standards and low citizen participation, the effect of waste sorting is not ideal. Therefore, how to effectively motivate citizens to actively participate in waste sorting has become a problem that needs to be solved urgently.

[0003] Traditional methods of incentivizing garbage sorting rely on government subsidies, publicity and education, but these methods often have limited coverage and unsustainable effects. In recent years, with the rapid development of technologies such as the Internet of Things, big data, and artificial intelligence, new ideas have been provided for incentivizing garbage sorting. By using these technologies, real-time monitoring and point rewards for garbage sorting and recycling can be achieved, thereby stimulating citizens' enthusiasm for participating in garbage sorting. However, the existing methods of incentivizing garbage sorting and recycling only reward points based on the type and weight of garbage, and the considerations are not comprehensive enough, and the accuracy and fairness of the point calculation are not high. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for motivating waste sorting and recycling, so as to consider more factors and improve the accuracy and fairness of the calculation of incentive points.

[0005] In a first aspect, the garbage classification and recycling incentive method of the present invention comprises:

[0006] Get the identity information of the user who placed the garbage at that time.

[0007] Get the weight Z of the i-th type of garbage placed by the user at that time i , the classification accuracy rate A for the i-th type of garbage i , the frequency of participation in classification of the i-th type of garbage F i and the number of garbage types n; where i takes all integers from 1 to n.

[0008] Based on the number n of garbage types placed by the user at that time, a garbage type diversity score D is calculated.

[0009] Using formula: I i =(w 1 +m i )×Z i +w 2 ×k×A i +w3 ×r×F i , calculate the integral value I of the i-th type of garbage i Among them, w 1 Indicates the preset weight, w 2 Represents the preset accuracy weight, w 3 represents the preset participation frequency weight, k represents the preset accuracy coefficient, k>1, r represents the preset participation frequency coefficient, r>1; m i represents the balance coefficient of the i-th type of garbage. If the i-th type of garbage is recyclable, then m i =1-w 1 , otherwise (for example, when the i-th type of garbage is wet garbage, dry garbage or hazardous garbage) m i =0.

[0010] Using the formula: Calculate the total points I obtained by the user for the garbage disposal all .

[0011] The total score I all The total value of the points that can be used to redeem rewards is obtained by adding it to the points value (previously) stored in the user's account.

[0012] The total points value is stored in the user's account. The user can redeem the corresponding reward using the total points value.

[0013] Preferably, the radio frequency sensing module of the intelligent garbage recycling station is used to identify the RFID tag of the user who puts the garbage at that time to obtain the identity information of the user who puts the garbage at that time (the identity information includes the user's account, the stored points value in the account, and the stored calculation frequency f of the i-th type of garbage). i ). Each user is assigned a unique RFID tag, which can be identified by the radio frequency induction module without contact, making it easy to identify, highly resistant to pollution, and long in service life.

[0014] Preferably, the camera of the smart garbage recycling station is used to identify the identity QR code of the user who puts the garbage at that time to obtain the identity information of the user who puts the garbage at that time (the identity information includes the user's account, the stored points value in the account, and the stored calculation frequency f of the i-th type of garbage i ). Each user is assigned a unique identity QR code (obtained by user registration), which can be identified by camera without contact, making identification easy and long-lasting.

[0015] Preferably, the weight Z of the i-th type of garbage dropped by the user at that time is weighed by a weighing module in the i-th type of garbage bin (i.e., the garbage bin for storing the i-th type of garbage) of the intelligent garbage recycling station. i , which ensures the accuracy and real-time nature of weight data collection.

[0016] Preferably, the classification accuracy rate A for the i-th type of garbage is i Ways to obtain include:

[0017] The image recognition module in the i-th type of trash can of the intelligent garbage recycling station is used to identify the amount x of the i-th type of garbage placed by the user at that time. c_i and the total amount of garbage put into the i-th type of garbage bin x t_i .

[0018] Using the formula: Calculate the classification accuracy A for the i-th type of garbage i The classification accuracy reflects the accuracy of the user's garbage classification. Taking the classification accuracy as a consideration factor can better motivate users to pay attention to the correctness of garbage classification when disposing of garbage, which helps to reduce classification errors caused by human factors.

[0019] Preferably, the classification participation frequency F for the i-th type of garbage i Equal to the stored frequency f of the i-th type of garbage i The calculation frequency f of the i-th type of garbage i It will be updated regularly. Calculate the frequency f using the stored i-th type of garbage i As the classification participation frequency F i , which can make the classification participation frequency F within a cycle i It remains unchanged, avoiding the real-time calculation of the classification participation frequency and taking up too much computing power, and also avoiding the inaccurate integral calculation caused by sudden changes in the classification participation frequency.

[0020] Preferably, the frequency f of the i-th type of garbage calculation is i Update via:

[0021] At the end of the jth cycle, count the number of times the user puts garbage into the i-th type of garbage bin during the cycle. e_i_j and the total number of times d that the i-th type of trash can in the smart garbage recycling station is put into the trash can a_i_j (including the user and other users). For example, one week is a cycle, two weeks is a cycle, or one month is a cycle.

[0022] Using the formula: Calculate the calculated frequency value f of the i-th type of garbage at the end of the j-th cycle i_j .

[0023] Calculate the frequency f of the i-th type of garbage i The value of is updated to the calculated frequency value f of the i-th type of garbage at the end of the j-th cycle i_j, and store; where j≥1, the frequency of the calculation of the i-th type of garbage is f i The initial value is equal to the preset frequency f 0 (f 0 are known parameters).

[0024] The frequency of participation in classification reflects the enthusiasm and persistence of users in participating in garbage classification. Taking the frequency of participation in classification as a consideration factor can better stimulate the enthusiasm and persistence of users in participating in garbage classification.

[0025] Preferably, the formula: D = w 4 ×log 2 n, calculate the garbage type diversity score D; where w 4 represents the preset diversity weight, w 1 +w 2 +w 3 +w 4 = 1. The diversity of garbage types reflects the user's ability to identify and handle different types of garbage. As a scoring factor, the diversity of garbage types can better inspire users to learn garbage classification knowledge and classify garbage more accurately.

[0026] In a second aspect, the waste classification and recycling incentive system of the present invention comprises an intelligent waste recycling station, and a cloud server terminal connected to the intelligent waste recycling station, the waste collection and transportation terminal, and the user terminal via a wireless network, wherein the cloud server terminal comprises a communication module, a controller, and a memory. The memory is used to store data. The controller is configured to execute the above-mentioned waste classification and recycling incentive method.

[0027] Preferably, a position sensor for detecting whether the height of the garbage has reached the overflow position is installed in the i-th type of garbage can of the intelligent garbage recycling station, and the position sensor is connected to the main control module of the intelligent garbage recycling station. When the height of the garbage in the i-th type of garbage can reaches the overflow position, the intelligent garbage recycling station sends the overflow information of the i-th type of garbage can to the cloud server terminal, and the cloud server terminal sends the overflow information of the i-th type of garbage can to the garbage collection and transportation terminal, reminding the garbage collection and transportation department to arrange the collection and transportation work in time. In this way, it can not only effectively avoid the environmental pollution problem caused by excessive overflow of the garbage can, but also improve the efficiency and quality of garbage collection and transportation.

[0028] The present invention has the following effects:

[0029] (1) Comprehensively consider the weight, classification accuracy, classification participation frequency and type diversity of garbage. The weight of garbage is the most direct influencing factor. The accuracy of garbage classification reflects the accuracy of the user's garbage classification. The frequency of garbage classification participation reflects the user's enthusiasm and persistence in participating in garbage classification. The type diversity of garbage reflects the user's ability to identify and handle different types of garbage. These four factors jointly affect the calculation value of points in the garbage classification and recycling incentive, which not only improves the accuracy and fairness of the point calculation, but also can comprehensively evaluate the user's garbage classification behavior and encourage users to participate more actively in garbage classification and recycling activities.

[0030] (2) When calculating the integral value of recyclable waste (w 1 +m i =1), directly giving it a score equal to the weight of recyclable garbage, and when calculating the score values ​​of the other three types of garbage, the preset weight w is used. 1 Multiplying the weight of the garbage to convert it into points can better encourage users to recycle garbage and increase their enthusiasm.

[0031] (3) Every time a user disposes of garbage, he or she will accumulate points, which will be stored in the user's account. The points in the user's account are updated in a timely manner, and the user can view the total value of the points by logging into the account, making it easier for the user to redeem the points for his or her favorite material rewards and / or spiritual incentives in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a principle block diagram of the garbage classification and recycling incentive system in an embodiment of the present invention.

[0033] Figure 2 This is a flow chart of the garbage classification and recycling incentive method in an embodiment of the present invention.

[0034] Figure 3 The frequency f of the i-th type of garbage is calculated in the embodiment of the present invention. i Update flowchart for . DETAILED DESCRIPTION

[0035] In order to enable a more detailed understanding of the features and technical contents of the embodiments of the present invention, the implementation of the embodiments of the present invention is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not intended to limit the embodiments of the present invention.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

[0037] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0038] In the embodiment of the present invention, garbage is divided into four categories, namely, recyclable garbage, wet garbage, dry garbage and hazardous garbage. The garbage put out by the user each time may be 1, 2, 3 or 4 of the four categories of garbage, and the number of types of garbage put out by the user at that time, n, may be equal to 1, 2, 3 or 4. Specifically, i in the i-th category of garbage is all integers from 1 to n.

[0039] like Figure 1 As shown, the garbage classification and recycling incentive system in the embodiment of the present invention includes an intelligent garbage recycling station, and a cloud server terminal connected to the intelligent garbage recycling station, the garbage collection and transportation terminal, and the user terminal through a wireless network. The cloud server terminal includes a communication module, a controller, and a memory, the memory is used to store data, and the controller is used to obtain data for point calculation and store the points in the corresponding user account in the memory.

[0040] The intelligent garbage recycling station includes a communication module, a main control module, a first-class garbage can (i.e., a garbage can for storing recyclable garbage), a second-class garbage can (i.e., a garbage can for storing wet garbage), a third-class garbage can (i.e., a garbage can for storing dry garbage), a fourth-class garbage can (i.e., a garbage can for storing hazardous garbage) and a radio frequency sensing module. The communication module and the radio frequency sensing module are connected to the main control module. The radio frequency sensing module is used to identify the user's RFID tag by induction to obtain the identity information of the user who puts out the garbage at that time.

[0041] In some embodiments, the smart garbage recycling station further includes a camera connected to the main control module, the camera is used to scan and identify the user's identity QR code to obtain the identity information of the user who puts the garbage at that time. The radio frequency identification method and the scanning code identification method can be selected by the user.

[0042] The first category trash can, the second category trash can, the third category trash can, and the fourth category trash can are all equipped with weighing modules, image recognition modules, and position sensors connected to the main control module. The weighing module is used to weigh the weight of the garbage in the i-th category trash can (based on the weight of the garbage before and after the garbage is placed, the weight of the i-th category of garbage placed at that time is calculated). The image recognition module is used to identify the type of garbage placed by the user in the i-th category trash can at that time. The position sensor is used to detect whether the height of the garbage has reached the overflow position. When the height of the garbage in the i-th category trash can reaches the overflow position, the main control module sends the overflow information of the i-th category trash can to the cloud server terminal through the communication module, and the cloud server terminal sends the overflow information of the i-th category trash can to the garbage collection and transportation terminal, reminding the garbage collection and transportation department to arrange the collection and transportation work in time. In this way, it can not only effectively avoid environmental pollution problems caused by excessive overflow of the garbage can, but also improve the efficiency and quality of garbage collection and transportation.

[0043] The cloud server terminal includes a communication module, a controller and a memory. The memory is used to store data, and the controller is used to obtain data for point calculation and store the points in the memory corresponding to the user's account.

[0044] like Figure 2 , Figure 3 As shown, the garbage classification and recycling incentive method in the embodiment of the present invention is executed by a controller and specifically includes the following steps:

[0045] The first step is to obtain the identity information of the user who placed the garbage at that time. The identity information includes the user's account, the points value stored in the account, and the stored calculation frequency f of the i-th type of garbage i .

[0046] In some embodiments, the radio frequency sensing module is used to identify the user's RFID tag by induction, obtain the identity information of the user who puts out the garbage at that time, and transmit it to the main control module. In some embodiments, the camera is used to scan the QR code of the user's identity to obtain the identity information of the user who puts out the garbage at that time, and transmit it to the main control module. The main control module uploads the identity information of the user who puts out the garbage at that time to the cloud server terminal through the communication module.

[0047] Step 2: Get the weight Z of the i-th type of garbage that the user has placed. i , the classification accuracy rate A for the i-th type of garbage i , the frequency of participation in classification of the i-th type of garbage F i and the number of garbage types n.

[0048] In some embodiments, the weight of the garbage in the i-th garbage bin is weighed by a weighing module. Specifically, the weight of the garbage after the garbage is put in is subtracted from the weight of the garbage before the garbage is put in, so as to obtain the weight of the i-th garbage put in at that time. The weight of the i-th garbage put in at that time weighed by the weighing module is transmitted to the main control module, and the main control module uploads it to the cloud server terminal through the communication module.

[0049] In some embodiments, the classification accuracy A for the i-th type of garbage i Ways to obtain include:

[0050] The controller first uses the image recognition module in the i-th trash can of the intelligent garbage recycling station to identify the amount of i-th trash that the user has put in at that time. c_i and the total amount of garbage put into the i-th type of garbage bin x t_i .

[0051] The image recognition module can identify the type of garbage placed by the user in the i-th garbage bin. The main control module controls the image recognition module to cumulatively identify (i.e., identify and count) the number of i-th garbage placed by the user in the i-th garbage bin. c_i and the total amount of garbage that the user puts into the i-th trash can at that time x t_i The main control module will x c_i 、x t_i Upload to the cloud server terminal through the communication module. If the user classifies the i-th type of garbage accurately, then x c_i =x t_i ; If the user does not classify the i-th type of garbage accurately, then x c_i <x t_i .

[0052] Controller reuse formula: Calculate the classification accuracy A for the i-th type of garbage i .

[0053] In some embodiments, the frequency of participation in the classification of the i-th type of garbage is F i Equal to the stored frequency f of the i-th type of garbage i The calculation frequency f of the i-th type of garbage i Will be updated regularly.

[0054] like Figure 3 As shown, the frequency f is calculated for the i-th type of garbage i Update via:

[0055] First, at the end of the jth cycle, count the number of times the user puts garbage into the i-th trash can in the cycle. e_i_j and the total number of times d that the i-th type of trash can in the smart garbage recycling station is put into the trash can a_i_j(including this user and other users). For example, take 2 weeks as a cycle.

[0056] In some embodiments, the main control module counts the number of times the user puts garbage into the i-th type of garbage bin within a period based on the number of times the radio frequency sensing module recognizes the user's RFID tag or the number of times the camera recognizes the user's identity QR code. e_i_j and the total number of times d that the i-th type of trash can is put into a cycle a_i_j , and through the communication module d e_i_j ,d a_i_j Upload to the cloud server terminal.

[0057] Then, using the formula: Calculate the calculated frequency value f of the i-th type of garbage at the end of the j-th cycle i_j .

[0058] Finally, the frequency f of the i-th type of garbage is calculated i The value of is updated to the calculated frequency value f of the i-th type of garbage at the end of the j-th cycle i_j (Even if f i =f i_j ), and store; where j≥1, the frequency of the i-th type of garbage calculation f i The initial value is equal to the preset frequency f 0 (f 0 is a known parameter, such as 0.005).

[0059] In some embodiments, the main control module determines the number of types of garbage placed by the user at that time (ie, the value n) based on the fact that the weight of the garbage placed in the garbage bin at that time is not zero, and uploads n to the cloud server terminal through the communication module.

[0060] The third step is to calculate the garbage type diversity score D based on the number n of garbage types placed by the user at that time.

[0061] Specifically: using the formula: D = w 4 ×log 2 n, and calculate the garbage type diversity score D. Among them, w 4 Indicates the preset diversity weight.

[0062] Step 4: Use formula: I i =(w 1 +m i )×Z i +w 2 ×k×A i +w 3 ×r×F i , calculate the integral value I of the i-th type of garbage i Among them, w 1Indicates the preset weight, w 2 Represents the preset accuracy weight, w 3 represents the preset participation frequency weight, w 1 +w 2 +w 3 +w 4 =1, k represents the preset accuracy coefficient, k>1, r represents the preset participation frequency coefficient, r>1; m i represents the balance coefficient of the i-th type of garbage. If the i-th type of garbage is recyclable, then m i =1-w 1 , otherwise m i =0.

[0063] Step 5: Use the formula: Calculate the total points I obtained by the user for this garbage disposal all .

[0064] Step 6: Total score I all Add the points value stored in the user's account to obtain the total value of the user's points that can be used to redeem rewards.

[0065] Step 7: The total points value is stored in the user's account. The user can redeem the corresponding rewards using the total points value.

[0066] The following example uses Ms. Zhang as the user who disposed of the garbage at that time.

[0067] Assume that Ms. Zhang put out three types of garbage (i.e. n = 3), namely: recyclable garbage (i.e. type 1 garbage), wet garbage (i.e. type 2 garbage) and dry garbage (i.e. type 3 garbage). Then the garbage type diversity score D = w 4 ×log 2 3=0.23775; where w 4 =0.15.

[0068] Assume that the weight of the recyclable garbage thrown by Ms. Zhang is 0.5kg, the weight of the wet garbage is 1kg, and the weight of the dry garbage is 0.3kg.

[0069] Assume that the amount of recyclable garbage Ms. Zhang put out this time is x c_1 =7, the total amount of garbage put into the first type of garbage bin x t_1 =8 (i.e., 7 pieces are recyclable and 1 piece is not recyclable), then the classification accuracy rate of recyclable waste is A 1 =0.875. Assume that the amount of wet garbage Ms. Zhang put out this time is x c_2 =2, the total amount of garbage put into the second type of garbage bin x t_2=2 (i.e. both pieces are wet garbage), then the classification accuracy rate of wet garbage is A 2 = 1. Assume that the amount of dry garbage Ms. Zhang put out this time is x c_3 =5, the total amount of garbage put into the third type of garbage bin x t_3 =6 (that is, 5 pieces are dry garbage and 1 piece is not dry garbage), then the classification accuracy rate of dry garbage is A 3 =0.833.

[0070] Assume that Ms. Zhang's frequency of participation in the classification of recyclable waste in the current period is F 1 =0.02, for the frequency of participation in the classification of wet garbage F 2 =0.05, for the frequency of participation in the classification of dry garbage F 3 =0.06. 1 =0.5, w 2 =0.2, w 3 =0.15, k=2, r=10.

[0071] Then the integral value I of Ms. Zhang's recycling waste is calculated. 1 =0.88, the integral value of wet garbage I 2 =0.975, the integral value of dry garbage I 3 =0.5732.

[0072] The total points Ms. Zhang received for this garbage disposal:

[0073] I all =D+I 1 +I 2 +I 3 =0.23775+0.88+0.975+0.5732=2.66595.

[0074] Assuming that the community has set the point redemption standard as 1 point for every 0.5 yuan of material rewards or spiritual incentives, then the total points Ms. Zhang obtained from this garbage disposal can be redeemed for a reward of 1.332975 yuan.

[0075] The above-mentioned points calculation process not only takes into account the weight and classification accuracy of the garbage, but also comprehensively considers the user's classification participation frequency and type diversity factors. This point calculation method can comprehensively evaluate the user's garbage classification behavior and encourage users to participate more actively in garbage classification and recycling activities. By updating points in real time and providing rewards, it can effectively improve citizens' environmental awareness and participation.

[0076] Users can check the points balance and redemption record in their accounts through user terminals (such as mobile APP or websites), and select corresponding material rewards (such as environmentally friendly shopping bags, green plants, discount coupons, etc.) or spiritual incentives (such as environmental medals, certificates of honor, etc.) for redemption. After receiving the user's redemption request, the cloud server terminal will review it (i.e., determine whether the redemption conditions are met) and notify the user of the redemption result (i.e., information on whether the redemption is successful) through the user terminal. The way users use points to redeem rewards belongs to the prior art and will not be repeated here. In addition, the points reward rules and redemption standards can be updated regularly to maintain the continued effectiveness and attractiveness of the incentive mechanism.

[0077] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for motivating garbage classification and recycling, characterized in that: include: Obtain the identity information of the user who placed the garbage at that time; Get the weight Z of the i-th type of garbage placed by the user at that time i , the classification accuracy rate A for the i-th type of garbage i , the frequency of participation in classification of the i-th type of garbage F i and the number of garbage types n; where i is all integers from 1 to n; Calculating a garbage type diversity score D based on the number of garbage types n; Using formula: I i =(w1+m i )×Z i +w2×k×A i +w3×r×F i , calculate the integral value I of the i-th type of garbage i ; Wherein, w1 represents the preset weight, w2 represents the preset accuracy weight, w3 represents the preset participation frequency weight, k represents the preset accuracy coefficient, k>1, r represents the preset participation frequency coefficient, r>1; m i represents the balance coefficient of the i-th type of garbage. If the i-th type of garbage is recyclable, then m i =1-w1, otherwise m i =0; Using the formula: Calculate the total points I obtained by the user for the garbage disposal all ; The total score I all Adding the points stored in the user's account to the total points value of the user that can be used to redeem rewards; The total points value is stored in the user's account.

2. The method for encouraging waste classification and recycling according to claim 1, characterized in that: The radio frequency sensing module of the intelligent garbage recycling station is used to identify the RFID tag of the user to obtain the identity information of the user.

3. The method for encouraging waste classification and recycling according to claim 1 is characterized in that: The camera of the smart garbage recycling station is used to identify the user's identity QR code to obtain the user's identity information.

4. The method for encouraging waste classification and recycling according to claim 1, characterized in that: The weight Z of the i-th type of garbage placed by the user at that time is weighed by the weighing module in the i-th type of garbage bin of the intelligent garbage recycling station. i .

5. The method for encouraging waste classification and recycling according to claim 1, characterized in that: The classification accuracy rate A for the i-th type of garbage i Ways to obtain include: The image recognition module in the i-th type of trash can of the intelligent garbage recycling station is used to identify the amount x of the i-th type of garbage placed by the user at that time. c_i and the total amount of garbage put into the i-th garbage bin x t_i ; Using the formula: Calculate the classification accuracy A for the i-th type of garbage i .

6. The method for encouraging waste classification and recycling according to claim 1, characterized in that: The frequency of participation in the classification of the i-th type of garbage F i Equal to the stored frequency f of the i-th type of garbage i .

7. The method for encouraging waste classification and recycling according to claim 6, characterized in that: The frequency f of the calculation of the i-th type of garbage i Update via: At the end of the jth cycle, count the number of times the user puts garbage into the i-th type of garbage bin during the cycle. e_i_j and the total number of times d that the i-th type of trash can in the smart garbage recycling station is put into the trash can a_i_j ; Using the formula: Calculate the calculated frequency value f of the i-th type of garbage at the end of the j-th cycle i_j ; Calculate the frequency f of the i-th type of garbage i The value of is updated to the calculated frequency value f i_j , and store; where j≥1, the frequency of the calculation of the i-th type of garbage is f i The initial value is equal to the preset frequency f0.

8. The method for incentivizing waste classification and recycling according to any one of claims 1 to 7, characterized in that: The garbage type diversity score D is calculated using the formula: D=w4×log2 n; wherein w4 represents a preset diversity weight, and w1+w2+w3+w4=1.

9. A garbage classification and recycling incentive system, comprising an intelligent garbage recycling station, and a cloud server terminal connected to the intelligent garbage recycling station, the garbage collection and transportation terminal, and the user terminal through a wireless network, wherein the cloud server terminal comprises a communication module, a controller, and a memory; characterized in that: The controller is configured to execute the garbage sorting and recycling incentive method as described in any one of claims 1 to 8.

10. The waste classification and recycling incentive system according to claim 9, characterized in that: A position sensor for detecting whether the garbage height has reached an overflowing position is installed in the i-th category garbage bin of the intelligent garbage recycling station, and the position sensor is connected to the main control module of the intelligent garbage recycling station; when the garbage height in the i-th category garbage bin reaches an overflowing position, the intelligent garbage recycling station sends the overflowing information of the i-th category garbage bin to the cloud server terminal, and the cloud server terminal sends the overflowing information of the i-th category garbage bin to the garbage collection and transportation terminal.

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