Intelligent recycling method for renewable resources and related equipment

Abstract

The invention relates to an intelligent recycling method for renewable resources, which comprises the following steps that a resource recycling cabinet is scanned through an applet in electronic equipment, and a camera shoots the renewable resources to obtain a renewable resource image; performing type identification on renewable resources in the renewable resource image to obtain renewable resource types; obtaining initial weight data of a weight sensor, obtaining contact weight data when the renewable resources are in complete contact with the weight sensor, and obtaining renewable resource weight data based on the contact weight data and the initial weight data; and calling a renewable resource price list in a database, obtaining recovery value data based on the renewable resource type, the renewable resource weight data and the renewable resource price list, and returning the recovery value data to a collection area in the applet, thereby solving the technical problem of how to efficiently classify and recover renewable resources.

Description

Technical Field

[0001] The present invention relates to the technical field of renewable resources, and in particular to an intelligent recycling method for renewable resources and related equipment. Background Art

[0002] With the acceleration of urbanization and the development of social economy, the amount of urban garbage has increased dramatically. How to efficiently classify and recycle renewable resources has become one of the urgent problems to be solved. Traditional resource recycling methods mostly rely on manual classification and measurement, which is not only inefficient, but also prone to errors and increases labor costs. In addition, the public's lack of awareness of garbage classification and the lack of effective incentive mechanisms have led to a low resource recycling rate.

[0003] In order to solve the above problems, some renewable resource classification and recycling systems have emerged in recent years. These systems usually use Internet of Things technology and artificial intelligence technology to improve the automation level of resource recycling. However, the existing intelligent recycling system still has some shortcomings, such as insufficient recognition accuracy and complicated operation process, which limit the wide application of the system. Summary of the invention

[0004] The main purpose of the present invention is to provide an intelligent recycling method and related equipment for renewable resources, which solves the technical problem of how to efficiently classify and recycle renewable resources.

[0005] To achieve the above object, the present invention provides an intelligent recycling method for renewable resources, which is applied to a resource recycling cabinet, wherein the resource recycling cabinet is provided with a camera and a weight sensor is provided at the bottom of the resource recycling cabinet, and the method comprises the following steps: Scanning the resource recycling cabinet through a small program in the electronic device to put the resource recycling cabinet in an open state, and placing the renewable resources in the resource recycling cabinet after the cabinet is in the open state; During the process of placing the resource recycling cabinet, the camera photographs the renewable resources to obtain a renewable resource image; Identifying the types of renewable resources in the renewable resource image to obtain the types of renewable resources; Acquire initial weight data of a weight sensor, obtain contact weight data when the renewable resource is in full contact with the weight sensor, and obtain renewable resource weight data based on the contact weight data and the initial weight data; The renewable resource price table in the database is called, and the recycling value data is obtained based on the renewable resource type, the renewable resource weight data and the renewable resource price table, and the recycling value data is returned to the payment area in the mini program.

[0006] Furthermore, scanning the resource recycling cabinet through a small program in the electronic device so that the resource recycling cabinet is in an open state includes: The mini-program in the electronic device is started to obtain a user interface; wherein the user interface is a user interface that displays a code scanning function; Scan the QR code of the resource recycling cabinet through the user interface to obtain a unique identifier of the resource recycling cabinet; By using a preset identity authentication algorithm, the resource recycling cabinet is authenticated and matched based on the unique identifier to obtain an authentication matching result of the resource recycling cabinet; wherein the authentication matching result includes an authentication matching success or an authentication matching failure; If the authentication matches successfully, a door opening instruction is sent to the resource recycling cabinet, so that the resource recycling cabinet is in an open state; If the authentication match fails, the user interface displays an error message and prohibits sending a door opening command.

[0007] Furthermore, the camera shoots the renewable resources to obtain a renewable resource image, including: Capturing an image of the renewable resource by using the camera to obtain a preliminary photographed image; De-noising the preliminary captured image to obtain a clear recycled resource image; The clear renewable resource image is subjected to distortion correction through the image enhancement algorithm to obtain the renewable resource image.

[0008] Furthermore, the types of renewable resources in the renewable resource image are identified to obtain the types of renewable resources, including: Performing color space conversion on the renewable resource image to obtain an enhanced grayscale image; Performing renewable resource identification on the enhanced grayscale image to obtain an identified renewable resource image, and annotating the identified renewable resource image to obtain an annotated renewable resource image; Segmenting the enhanced grayscale image based on the labeled renewable resource image to obtain a segmented image; wherein there are a plurality of segmented images, each of which has a corresponding renewable resource; Based on the convolutional neural network model, the segmented image is subjected to feature extraction to obtain a high-dimensional feature vector; Performing feature selection and dimensionality reduction on the high-dimensional feature vector to obtain a reduced-dimensional feature vector; Performing label classification on the dimension-reduced feature vector to obtain a classification label vector; The classification label vector is subjected to vector analysis to obtain the type of renewable resources.

[0009] Further, the initial weight data includes first initial data and second initial data, the initial weight data of the weight sensor is obtained, when the renewable resource is in full contact with the weight sensor, contact weight data is obtained, and the renewable resource weight data is obtained based on the contact weight data and the initial weight data, including: If no renewable resources are placed in the resource recovery cabinet, an empty-load measurement is performed on the resource recovery cabinet to obtain first initial data; wherein the first initial data is zero; If there are previously existing renewable resources in the resource recovery cabinet, then the load of the previously existing renewable resources is measured to obtain second initial data; wherein the second initial data is the weight of the previously existing renewable resources; When the renewable resource contacts the weight sensor, the contact state between the renewable resource and the weight sensor is detected to confirm whether the renewable resource and the sensor are in full contact; wherein the contact state includes full contact and incomplete contact; If the contact is complete, contact weight data is obtained, and the net weight of the recycled resources is calculated based on the contact weight data and the initial weight data to obtain recycled resource weight data; If the contact is not complete, the user interface and / or the weight sensor may display a warning message to remind the user of the electronic device to bring the renewable resource into complete contact with the weight sensor.

[0010] Furthermore, the recycling value data is obtained based on the type of renewable resources, the weight data of renewable resources and the price list of renewable resources, including: Matching the category labels in the renewable resource price table based on the renewable resource category to obtain a matching result; Obtaining a matching unit price corresponding to the type of renewable resource based on the matching result; Obtaining a preliminary recycling value based on the matching unit price and the recycled resource weight data; Obtain the market volatility factor corresponding to the renewable resources in the renewable resource price table; The preliminary recovery value is adjusted based on market volatility factors to obtain adjusted value data, and the adjusted value is used as the recovery value data.

[0011] Furthermore, the recycling value data is returned to the payment area in the mini program, including: Through a preset API interface and a preset error handling algorithm, the process of transmitting the recycled value data to the mini program is monitored to obtain a mini program security data flow; Performing data parsing and format conversion on the mini-program security data stream to obtain parsed and converted data; wherein the parsed and converted data is display data of formatted recycling value suitable for display in the mini-program payment area; The interface of the mini program is updated based on the analyzed conversion data to obtain the recycling value displayed in real time in the payment area of ​​the mini program.

[0012] The present invention also provides an intelligent recycling device for renewable resources, which is applied to a resource recycling cabinet. The resource recycling cabinet is provided with a camera and a weight sensor is provided at the bottom of the resource recycling cabinet, including: A scanning module, used to scan the resource recycling cabinet through a small program in the electronic device, so that the resource recycling cabinet is in an open state, and after the door is in the open state, the renewable resources are placed in the resource recycling cabinet; A shooting module, used for shooting the renewable resources by the camera to obtain a renewable resource image during the process of placing the resource recycling cabinet; An identification module, used for identifying the type of renewable resources in the renewable resource image to obtain the type of renewable resources; A contact module, used for obtaining initial weight data of a weight sensor, obtaining contact weight data when the renewable resource is in full contact with the weight sensor, and obtaining renewable resource weight data based on the contact weight data and the initial weight data; The calling module is used to call the renewable resource price list in the database, obtain the recycling value data based on the renewable resource type, the renewable resource weight data and the renewable resource price list, and return the recycling value data to the payment area in the mini program.

[0013] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0014] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0015] The intelligent recycling method of renewable resources provided by the present invention comprises the following steps: scanning the resource recycling cabinet through a small program in an electronic device so that the resource recycling cabinet is in an open state, and in the process of placing the resource recycling cabinet, the camera shoots the renewable resources to obtain a renewable resource image; identifying the type of renewable resources in the renewable resource image to obtain the type of renewable resources; acquiring the initial weight data of the weight sensor, and when the renewable resources are in full contact with the weight sensor, obtaining the contact weight data, and obtaining the renewable resource weight data based on the contact weight data and the initial weight data; calling the renewable resource price list in the database, and obtaining the recycling value data based on the renewable resource type, the renewable resource weight data and the renewable resource price list, and returning the recycling value data to the collection area in the small program. The above technical solution solves the technical problem of how to efficiently classify and recycle renewable resources, realizes the automation process, reduces the labor cost, and improves the speed and efficiency of resource recycling. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the steps of an intelligent recycling method for renewable resources in one embodiment of the present invention; Figure 2 It is a structural block diagram of an intelligent recycling device for renewable resources in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0017] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] like Figure 1 As shown, Figure 1 It is a schematic diagram of the steps of an intelligent recycling method for renewable resources in one embodiment of the present invention; In one embodiment of the present invention, a method for intelligently recycling renewable resources is provided, which is applied to a resource recycling cabinet, wherein the resource recycling cabinet is provided with a camera and a weight sensor is provided at the bottom of the resource recycling cabinet. The method comprises the following steps: Step S1, scanning the resource recycling cabinet through a small program in an electronic device to make the resource recycling cabinet in an open state, and after being in the open state, placing the recycled resources in the resource recycling cabinet.

[0020] Specifically, the resource recycling cabinet is scanned by a small program in an electronic device: this step refers to the user using a specific application (i.e., "small program") on his mobile phone or other mobile device to scan the QR code or barcode on the resource recycling cabinet. The scanning action triggers the unlocking mechanism of the resource recycling cabinet, changing it from a locked state to an openable state. So that the resource recycling cabinet is in an open state: after the user completes the scanning action, the resource recycling cabinet will automatically unlock and open the door so that the user can put the items to be recycled into it. This process is usually achieved by an electronic lock or mechanical device inside the resource recycling cabinet. After being in the open state, the renewable resources are placed in the resource recycling cabinet: when the resource recycling cabinet is in the open state, the user can put the prepared renewable resources into the cabinet. The "renewable resources" here refer to any recyclable items, such as waste paper, plastic bottles, metal cans, etc. In short, the user first uses the small program on the electronic device to scan the resource recycling cabinet to unlock and open the cabinet door; then, the user puts the items to be recycled into the opened resource recycling cabinet. This process not only simplifies the user's operating procedures, but also ensures the safety and convenience of resource recycling.

[0021] Step S2: During the process of placing the resource recycling cabinet, the camera photographs the renewable resources to obtain a renewable resource image.

[0022] Specifically, in the process of placing the resource recycling cabinet: this refers to the process in which the user places the renewable resources into the resource recycling cabinet.

[0023] The camera photographs the renewable resources: the camera installed on the resource recycling cabinet will automatically start to photograph the renewable resources put in by the user. The position of the camera is usually designed to capture the full view of the resources to ensure that the captured image is clear and visible.

[0024] Obtaining images of renewable resources: After the camera is finished shooting, one or more images containing renewable resources will be generated, and these images will be saved for subsequent type identification. In short, when the user puts renewable resources into the recycling cabinet, the camera installed on the recycling cabinet will take pictures of the items put in, thereby obtaining images of renewable resources. These images will be used for the next step of type identification.

[0025] Step S3, identifying the types of renewable resources in the renewable resource image to obtain the types of renewable resources.

[0026] Specifically, the types of renewable resources in the renewable resource images are identified: After obtaining the images of renewable resources, image processing technology and machine learning algorithms are used to analyze the renewable resources in these images. Obtaining the types of renewable resources: Through image analysis, the system can identify the specific types of renewable resources in the image, such as paper, plastic bottles, metal cans, etc., and give corresponding classification results. In short, after obtaining the image of renewable resources, the image is analyzed through image processing technology to identify the specific types of renewable resources in the image.

[0027] Step S4, obtaining initial weight data of the weight sensor, obtaining contact weight data when the renewable resource is in full contact with the weight sensor, and obtaining renewable resource weight data based on the contact weight data and the initial weight data.

[0028] Specifically, the initial weight data of the weight sensor is obtained: before the user starts to place the recycled resources, the system will first record the current reading of the weight sensor. This reading reflects the total weight of the items already in the resource recycling cabinet, which is called the "initial weight data". When the recycled resources are completely in contact with the weight sensor, the contact weight data is obtained: when the user completely puts the recycled resources into the resource recycling cabinet and contacts the weight sensor at the bottom, the weight sensor will record the reading at this time, which is called the "contact weight data". This step ensures that the weight of all recycled resources is accurately measured. The recycled resource weight data is obtained based on the contact weight data and the initial weight data: by calculating the difference between the contact weight data and the initial weight data, the total weight of the recycled resources placed in the resource recycling cabinet this time, that is, the "recycled resource weight data", can be obtained. In short, the system first records the initial reading of the weight sensor, and then records the new reading after the recycled resources are completely placed and contacted with the weight sensor. By comparing the difference between these two readings, the weight of the recycled resources can be calculated.

[0029] Step S5, calling the renewable resource price table in the database, obtaining recycling value data based on the renewable resource type, the renewable resource weight data and the renewable resource price table, and returning the recycling value data to the payment area in the mini program.

[0030] Specifically, call the price list of renewable resources in the database: the system will access the price list of renewable resources pre-stored in the database, which contains the price information of various renewable resources. Based on the type of renewable resources, the weight data of the renewable resources and the price list of renewable resources, obtain the recycling value data: according to the previously identified types of renewable resources and their corresponding weight data, combined with the price information in the price list of renewable resources, calculate the recycling value of each renewable resource. This process may involve a simple multiplication operation, that is, multiplying the weight of each resource by its corresponding price. Return the recycling value data to the payment area in the mini program: the calculated recycling value data will be sent back to the mini program in the electronic device used by the user, and displayed in a specially set payment area, so that the user can clearly see the value obtained by investing in renewable resources. In short, the system will look up the price list in the database according to the type and weight of the renewable resources, calculate the specific recycling value, and display this value in the payment area of ​​the mini program for the user to view.

[0031] In a specific embodiment, scanning the resource recycling cabinet through a small program in an electronic device so that the resource recycling cabinet is in an open state includes: The mini-program in the electronic device is started to obtain a user interface; wherein the user interface is a user interface that displays a code scanning function; Scan the QR code of the resource recycling cabinet through the user interface to obtain a unique identifier of the resource recycling cabinet; By using a preset identity authentication algorithm, the resource recycling cabinet is authenticated and matched based on the unique identifier to obtain an authentication matching result of the resource recycling cabinet; wherein the authentication matching result includes an authentication matching success or an authentication matching failure; If the authentication matches successfully, a door opening instruction is sent to the resource recycling cabinet, so that the resource recycling cabinet is in an open state; If the authentication match fails, the user interface displays an error message and prohibits sending a door opening command.

[0032] Specifically, the applet in the electronic device is started to obtain a user interface: the user first starts a specific applet on his electronic device (such as a smart phone), and the applet will display a user interface with a code scanning function. The QR code of the resource recycling cabinet is scanned through the user interface to obtain the unique identifier of the resource recycling cabinet: the user scans the QR code on the resource recycling cabinet through the code scanning function in the user interface provided by the applet. This QR code contains the unique identification information of the resource recycling cabinet. Through the preset identity authentication algorithm, the resource recycling cabinet is authenticated and matched based on the unique identifier to obtain the authentication matching result of the resource recycling cabinet: after the applet receives the unique identifier in the QR code, it will use the preset identity authentication algorithm to authenticate and match the resource recycling cabinet. This process is to confirm that the user is trying to open the correct resource recycling cabinet and ensure safety. If the authentication match is successful, an opening instruction is sent to the resource recycling cabinet to put the resource recycling cabinet in an open state: if the authentication match is successful, that is, the unique identifier of the resource recycling cabinet matches the information recorded by the system, then the applet will send an opening instruction to the resource recycling cabinet, and the resource recycling cabinet will unlock and enter the open state after receiving the instruction. If the authentication match fails, the user interface displays an error message and prohibits sending the door opening command: If the authentication match fails, that is, the unique identifier of the resource recycling cabinet does not match the information recorded in the system, the applet will display an error message on the user interface and will not send the door opening command to prevent unauthorized access. In short, the user starts the applet on the electronic device and uses the scanning function to scan the QR code on the resource recycling cabinet. The applet will authenticate the resource recycling cabinet based on the unique identifier in the QR code. If the authentication is successful, the resource recycling cabinet will be unlocked and opened; if the authentication fails, an error message will be displayed on the user interface of the applet, and the resource recycling cabinet will be prevented from being unlocked.

[0033] In a specific embodiment, the camera photographs the renewable resources to obtain a renewable resource image, including: Capturing an image of the renewable resource by using the camera to obtain a preliminary photographed image; De-noising the preliminary captured image to obtain a clear recycled resource image; The clear renewable resource image is subjected to distortion correction through the image enhancement algorithm to obtain the renewable resource image.

[0034] Specifically, the camera captures the image of the renewable resources to obtain a preliminary captured image: when the user puts the renewable resources into the resource recycling cabinet, the camera installed on the resource recycling cabinet will automatically start and capture the image of the renewable resources, thereby obtaining a preliminary captured image. The preliminary captured image is denoised to obtain a clear renewable resource image: the preliminary captured image is processed, especially the noise in the image is removed, such as noise or blurred parts, to improve the quality of the image, make it clearer, and facilitate subsequent image recognition. The clear renewable resource image is corrected for distortion by an image enhancement algorithm to obtain a renewable resource image: the image enhancement algorithm is used to further optimize the image quality, including but not limited to distortion correction and other processing, to ensure that the renewable resources in the image have clear contours and correct shapes, and to prepare for subsequent category recognition. In short, after the camera captures the preliminary image of the renewable resources, it will denoise the image to improve the clarity of the image; then the image enhancement algorithm is used to correct the distortion, and finally a renewable resource image suitable for category recognition is obtained.

[0035] In a specific embodiment, the type of renewable resources in the renewable resource image is identified to obtain the type of renewable resources, including: Performing color space conversion on the renewable resource image to obtain an enhanced grayscale image; Performing renewable resource identification on the enhanced grayscale image to obtain an identified renewable resource image, and annotating the identified renewable resource image to obtain an annotated renewable resource image; Segmenting the enhanced grayscale image based on the labeled renewable resource image to obtain a segmented image; wherein there are a plurality of segmented images, each of which has a corresponding renewable resource; Based on the convolutional neural network model, the segmented image is subjected to feature extraction to obtain a high-dimensional feature vector; Performing feature selection and dimensionality reduction on the high-dimensional feature vector to obtain a reduced-dimensional feature vector; Performing label classification on the dimension-reduced feature vector to obtain a classification label vector; The classification label vector is subjected to vector analysis to obtain the type of renewable resources.

[0036] Specifically, the color space conversion is performed on the renewable resource image to obtain an enhanced grayscale image: First, the captured renewable resource image is converted into a grayscale image by color space conversion to reduce the complexity of image processing and enhance the image contrast for subsequent processing. The enhanced grayscale image is subjected to renewable resource identification to obtain an identified renewable resource image, and the identified renewable resource image is annotated to obtain an annotated renewable resource image: image processing technology is used to identify renewable resources in the enhanced grayscale image, determine the location and shape of renewable resources, and annotate these resources to form an annotated renewable resource image. The enhanced grayscale image is segmented based on the annotated renewable resource image to obtain a segmented image: the enhanced grayscale image is segmented according to the location information in the annotated renewable resource image, and each individual renewable resource is separated from the background to form a series of segmented images. Feature extraction of the segmented image is performed based on the convolutional neural network model to obtain a high-dimensional feature vector: a convolutional neural network (CNN) model is used to extract features from each segmented image to extract a high-dimensional feature vector that can represent the characteristics of renewable resources. The high-dimensional feature vector is subjected to feature selection and dimensionality reduction to obtain a reduced-dimensional feature vector: Since the high-dimensional feature vector may contain redundant information, feature selection and dimensionality reduction are performed on it to improve recognition efficiency and accuracy. The reduced-dimensional feature vector is subjected to label classification to obtain a classification label vector: The reduced-dimensional feature vector is classified using a machine learning algorithm to obtain a classification label for each renewable resource, forming a classification label vector. The classification label vector is subjected to vector parsing to obtain the type of renewable resource: Finally, the classification label vector is parsed to determine the type of each renewable resource, thereby obtaining the type of renewable resource. In short, by performing a series of image processing and application of machine learning algorithms on the renewable resource image, including color space conversion, image segmentation, feature extraction, feature selection and dimensionality reduction, label classification and other steps, the type of renewable resource is finally obtained.

[0037] In a specific embodiment, the initial weight data includes first initial data and second initial data, the initial weight data of the weight sensor is obtained, and when the renewable resource is in full contact with the weight sensor, contact weight data is obtained, and the renewable resource weight data is obtained based on the contact weight data and the initial weight data, including: If no renewable resources are placed in the resource recovery cabinet, an empty-load measurement is performed on the resource recovery cabinet to obtain first initial data; wherein the first initial data is zero; If there are previously existing renewable resources in the resource recovery cabinet, then the load of the previously existing renewable resources is measured to obtain second initial data; wherein the second initial data is the weight of the previously existing renewable resources; When the renewable resource contacts the weight sensor, the contact state between the renewable resource and the weight sensor is detected to confirm whether the renewable resource and the sensor are in full contact; wherein the contact state includes full contact and incomplete contact; If the contact is complete, the contact weight data is obtained, and the net weight of the recycled resources is calculated based on the contact weight data and the initial weight data to obtain the recycled resources weight data; If the contact is not complete, the user interface and / or the weight sensor may display a warning message to remind the user of the electronic device to bring the renewable resource into complete contact with the weight sensor.

[0038] Specifically, if there is no renewable resource in the resource recycling cabinet, that is, it is in an empty state, then the weight sensor will record the weight reading at this time as the first initial data, which is usually zero. If there are already some previous renewable resources in the resource recycling cabinet, the weight sensor will record the total weight of these resources as the second initial data. When the user puts the renewable resources into the resource recycling cabinet, the system will detect the contact state between the renewable resources and the weight sensor to confirm whether they are in full contact. If it is detected that the renewable resources are in full contact with the weight sensor, the system will calculate the net weight of the renewable resources based on the contact weight data and the initial weight data (first initial data or second initial data). If it is detected that the renewable resources are not in full contact with the weight sensor, the system will issue a warning message on the user interface or through the weight sensor, prompting the user to adjust the position of the renewable resources to ensure that it is in full contact with the weight sensor. In short, the system will first record the initial weight data according to the state of the resource recycling cabinet (empty or loaded). When the user puts the renewable resources into the resource recycling cabinet, the system will detect the contact state between the renewable resources and the weight sensor, and calculate the net weight if they are in full contact; if they are not in full contact, a warning message will be issued to remind the user to make adjustments.

[0039] In a specific embodiment, the recycling value data is obtained based on the type of renewable resources, the weight data of the renewable resources and the price list of the renewable resources, including: Matching the category labels in the renewable resource price table based on the renewable resource category to obtain a matching result; Obtaining a matching unit price corresponding to the type of renewable resource based on the matching result; Obtaining a preliminary recycling value based on the matching unit price and the recycled resource weight data; Obtain the market volatility factor corresponding to the renewable resources in the renewable resource price table; The preliminary recovery value is adjusted based on market volatility factors to obtain adjusted value data, and the adjusted value is used as the recovery value data.

[0040] Specifically, the type label in the renewable resource price table is matched based on the renewable resource type to obtain a matching result: according to the previously identified renewable resource type, the type label in the renewable resource price table is queried to find an entry matching the type and obtain a matching result.

[0041] Based on the matching result, the matching unit price corresponding to the type of renewable resources is obtained: according to the matching result, the price matching the type of renewable resources, i.e., the matching unit price, is extracted from the renewable resource price table. Based on the matching unit price and the renewable resource weight data, a preliminary recycling value is obtained: the matching unit price and the previously calculated renewable resource weight data are used to calculate the preliminary recycling value of the renewable resources through simple mathematical operations (usually multiplication). Obtain the market volatility factor corresponding to the renewable resources in the renewable resource price table: the renewable resource price table also includes the market volatility factor, which is a coefficient reflecting the impact of market price fluctuations and is used to adjust the recycling value to reflect the actual market situation. Based on the market volatility factor, the preliminary recycling value is adjusted to obtain the adjusted value data, and the adjusted value is used as the recycling value data: the preliminary recycling value is combined with the market volatility factor, and the preliminary recycling value is adjusted through a certain calculation formula (such as multiplication) to obtain the final adjusted value data, and this adjusted value data is used as the actual recycling value data. In short, the system first queries the price table by the type of renewable resources to obtain the matching unit price, and then calculates the preliminary recycling value in combination with the weight data of the renewable resources. Next, the preliminary recovery value is adjusted according to market volatility factors to obtain the final recovery value data.

[0042] In a specific embodiment, returning the recycling value data to the payment area in the mini program includes: Through a preset API interface and a preset error handling algorithm, the process of transmitting the recycled value data to the mini program is monitored to obtain a mini program security data flow; Performing data parsing and format conversion on the mini-program security data stream to obtain parsed and converted data; wherein the parsed and converted data is display data of formatted recycling value suitable for display in the mini-program payment area; The interface of the mini program is updated based on the analyzed conversion data to obtain the recycling value displayed in real time in the payment area of ​​the mini program.

[0043] Specifically, the recovery value data is transmitted to the mini program through a preset API interface and a preset error handling algorithm to monitor the data transmission process, thereby obtaining a mini program security data stream: when the recovery value data is transmitted to the mini program through a preset API interface, the system will use a preset error handling algorithm to monitor the data transmission process to ensure the security and integrity of the data transmission, thereby obtaining a mini program security data stream. The mini program security data stream is parsed and formatted to obtain parsed conversion data; wherein the parsed conversion data is display data of the formatted recovery value suitable for display in the mini program payment area: the recovery value data in the mini program security data stream is parsed and formatted to ensure that the data meets the display requirements of the mini program payment area, and the parsed conversion data is obtained so that the user can clearly see the recovery value in the payment area. The mini program interface is updated based on the parsed conversion data to obtain the recovery value displayed in real time in the mini program payment area: the interface of the mini program is updated using the parsed conversion data to realize the real-time display of the recovery value in the payment area, so that the user can immediately see the value obtained by investing in recycled resources. In short, the system first transmits the recycling value data to the mini program securely through the preset API interface and handles errors during the transmission process. Then, the data is parsed and formatted so that it is suitable for display in the payment area of ​​the mini program. Finally, the mini program interface is updated to display the recycling value in real time.

[0044] The above describes the intelligent recycling method of renewable resources in the embodiment of the present invention. The following describes the intelligent recycling device of renewable resources in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, an intelligent recycling device for renewable resources includes: The scanning module 21 is used to scan the resource recycling cabinet through a small program in the electronic device to make the resource recycling cabinet open. After the cabinet is in the open state, the renewable resources are placed in the resource recycling cabinet; The shooting module 22 is used for shooting the renewable resources by the camera to obtain the renewable resource image during the process of placing the resource recycling cabinet; The identification module 23 is used to identify the type of renewable resources in the renewable resource image to obtain the type of renewable resources; A contact module 24, used to obtain initial weight data of the weight sensor, obtain contact weight data when the renewable resource is in full contact with the weight sensor, and obtain renewable resource weight data based on the contact weight data and the initial weight data; The calling module 25 is used to call the renewable resource price list in the database, obtain the recycling value data based on the renewable resource type, the renewable resource weight data and the renewable resource price list, and return the recycling value data to the payment area in the mini program.

[0045] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0046] Reference Figure 3 The present invention also provides a computer device in an embodiment, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0047] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0048] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0049] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0050] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0051] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An intelligent recycling method for renewable resources, characterized in that: Applied to a resource recovery cabinet, the resource recovery cabinet is provided with a camera and a weight sensor is provided at the bottom of the resource recovery cabinet, and the method comprises the following steps: Scanning the resource recycling cabinet through a small program in the electronic device to put the resource recycling cabinet in an open state, and placing the renewable resources in the resource recycling cabinet after the cabinet is in the open state; During the process of placing the resource recycling cabinet, the camera photographs the renewable resources to obtain a renewable resource image; Identifying the types of renewable resources in the renewable resource image to obtain the types of renewable resources; Acquire initial weight data of a weight sensor, obtain contact weight data when the renewable resource is in full contact with the weight sensor, and obtain renewable resource weight data based on the contact weight data and the initial weight data; The renewable resource price table in the database is called, and the recycling value data is obtained based on the renewable resource type, the renewable resource weight data and the renewable resource price table, and the recycling value data is returned to the payment area in the mini program.

2. The intelligent recycling method of renewable resources according to claim 1, characterized in that: Scanning the resource recycling cabinet through a small program in an electronic device to put the resource recycling cabinet in an open state includes: The mini-program in the electronic device is started to obtain a user interface; wherein the user interface is a user interface that displays a code scanning function; Scan the QR code of the resource recycling cabinet through the user interface to obtain a unique identifier of the resource recycling cabinet; By using a preset identity authentication algorithm, the resource recycling cabinet is authenticated and matched based on the unique identifier to obtain an authentication matching result of the resource recycling cabinet; wherein the authentication matching result includes an authentication matching success or an authentication matching failure; If the authentication matches successfully, a door opening instruction is sent to the resource recycling cabinet, so that the resource recycling cabinet is in an open state; If the authentication match fails, the user interface displays an error message and prohibits sending a door opening command.

3. The intelligent recycling method of renewable resources according to claim 1, characterized in that: The camera shoots the renewable resources to obtain a renewable resource image, including: Capturing an image of the renewable resource by using the camera to obtain a preliminary photographed image; De-noising the preliminary captured image to obtain a clear recycled resource image; The clear renewable resource image is distorted and corrected by an image enhancement algorithm to obtain a renewable resource image.

4. The intelligent recycling method of renewable resources according to claim 1, characterized in that: Identifying the types of renewable resources in the renewable resource image to obtain the types of renewable resources includes: Performing color space conversion on the renewable resource image to obtain an enhanced grayscale image; Performing renewable resource identification on the enhanced grayscale image to obtain an identified renewable resource image, and annotating the identified renewable resource image to obtain an annotated renewable resource image; Segmenting the enhanced grayscale image based on the labeled renewable resource image to obtain a segmented image; wherein there are a plurality of segmented images, each of which has a corresponding renewable resource; Based on the convolutional neural network model, the segmented image is subjected to feature extraction to obtain a high-dimensional feature vector; Performing feature selection and dimensionality reduction on the high-dimensional feature vector to obtain a reduced-dimensional feature vector; Performing label classification on the dimension-reduced feature vector to obtain a classification label vector; The classification label vector is subjected to vector analysis to obtain the type of renewable resources.

5. The intelligent recycling method of renewable resources according to claim 2, characterized in that: The initial weight data includes first initial data and second initial data, the initial weight data of the weight sensor is acquired, contact weight data is acquired when the renewable resource is in full contact with the weight sensor, and renewable resource weight data is acquired based on the contact weight data and the initial weight data, including: If no renewable resources are placed in the resource recovery cabinet, an empty-load measurement is performed on the resource recovery cabinet to obtain first initial data; wherein the first initial data is zero; If there are previously existing renewable resources in the resource recovery cabinet, then the load of the previously existing renewable resources is measured to obtain second initial data; wherein the second initial data is the weight of the previously existing renewable resources; When the renewable resource contacts the weight sensor, the contact state between the renewable resource and the weight sensor is detected to confirm whether the renewable resource and the sensor are in full contact; wherein the contact state includes full contact and incomplete contact; If the contact is complete, contact weight data is obtained, and the net weight of the recycled resources is calculated based on the contact weight data and the initial weight data to obtain recycled resource weight data; If the contact is not complete, the user interface and / or the weight sensor may display a warning message to remind the user of the electronic device to bring the renewable resource into complete contact with the weight sensor.

6. The intelligent recycling method of renewable resources according to claim 1, characterized in that: The recycling value data is obtained based on the type of renewable resources, the weight data of the renewable resources and the price list of renewable resources, including: Matching the category labels in the renewable resource price table based on the renewable resource category to obtain a matching result; Obtaining a matching unit price corresponding to the type of renewable resource based on the matching result; Obtaining a preliminary recycling value based on the matching unit price and the recycled resource weight data; Obtain the market volatility factor corresponding to the renewable resources in the renewable resource price table; The preliminary recovery value is adjusted based on market volatility factors to obtain adjusted value data, and the adjusted value is used as the recovery value data.

7. The intelligent recycling method of renewable resources according to claim 1, characterized in that: Return the recycling value data to the payment area in the mini program, including: Through a preset API interface and a preset error handling algorithm, the process of transmitting the recycled value data to the mini program is monitored to obtain a mini program security data flow; Performing data parsing and format conversion on the mini-program security data stream to obtain parsed and converted data; wherein the parsed and converted data is display data of formatted recycling value suitable for display in the mini-program payment area; The interface of the mini program is updated based on the analyzed conversion data to obtain the recycling value displayed in real time in the payment area of ​​the mini program.

8. An intelligent recycling device for renewable resources, characterized in that: Applied to a resource recycling cabinet, the resource recycling cabinet is provided with a camera and a weight sensor is provided at the bottom of the resource recycling cabinet, including: A scanning module, used to scan the resource recycling cabinet through a small program in the electronic device, so that the resource recycling cabinet is in an open state, and after the door is in the open state, the renewable resources are placed in the resource recycling cabinet; A shooting module, used for shooting the renewable resources by the camera to obtain a renewable resource image during the process of placing the resource recycling cabinet; An identification module, used for identifying the type of renewable resources in the renewable resource image to obtain the type of renewable resources; A contact module, used for obtaining initial weight data of a weight sensor, obtaining contact weight data when the renewable resource is in full contact with the weight sensor, and obtaining renewable resource weight data based on the contact weight data and the initial weight data; The calling module is used to call the renewable resource price list in the database, obtain the recycling value data based on the renewable resource type, the renewable resource weight data and the renewable resource price list, and return the recycling value data to the payment area in the mini program.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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