CN111832749B

CN111832749B - Garbage bag identification method and related device

Info

Publication number: CN111832749B
Application number: CN201910290133.XA
Authority: CN
Inventors: 黄涛
Original assignee: Shenzhen Jiajia Classification Technology Co ltd
Current assignee: Shenzhen Jiajia Classification Technology Co ltd
Priority date: 2019-04-11
Filing date: 2019-04-11
Publication date: 2024-03-22
Anticipated expiration: 2039-04-11
Also published as: CN111832749A

Abstract

The embodiment of the application discloses a garbage bag identification method and a related device, which are applied to a cloud server in a garbage source classification and decrement comprehensive service platform, wherein the garbage source classification and decrement comprehensive service platform comprises the cloud server and a classification garbage can, and the method comprises the following steps: receiving a first image data set, ambient light and a first distance data set uploaded by a classified garbage can; analyzing, identifying and processing the first image data set and the first distance data set to obtain a processing result; and generating a delivery record of the target user according to the processing result, generating an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for trading in a virtual mall provided by the garbage source classification and decrement comprehensive service platform and is used for supervising the authority application. The method and the device are beneficial to improving the accuracy of generating the environmental protection gold aiming at the target user, increasing the enthusiasm of resident garbage classification and improving the environmental protection energy saving consciousness of residents.

Description

Garbage bag identification method and related device

Technical Field

The application relates to a garbage disposal technology, in particular to a garbage bag identification method and a related device.

Background

The garbage classification is an improvement of the traditional garbage collection and disposal mode, and is a scientific management method for effectively disposing garbage. Garbage classification refers to the general term of a series of activities of classifying, storing, throwing and carrying garbage according to a certain rule or standard, so as to convert the garbage into public resources. At present, the garbage classification awareness of residents in China is still deficient, and the society lacks garbage throwing classification atmosphere, and the renewable resource recovery mode is promoted to innovate according to related documents and in order to conform to the development trend of Internet+; to promote a new mode of "internet + recovery"; exploring a new mechanism for the coordinated development of two networks; the system for recycling the renewable resources is perfect, implements the household garbage classification which takes the dry and wet classification as the key point, guides residents to put kitchen garbage after filtering out water in the classification, and aims to solve the problem that the cultured residents have good garbage classification consciousness.

Disclosure of Invention

The embodiment of the application provides a garbage bag identification method and a related device, which are favorable for improving the accuracy of generating environmental protection gold aiming at target users, increasing the enthusiasm of resident garbage classification and improving the environmental protection and energy saving consciousness of residents.

In a first aspect, an embodiment of the present application provides a garbage bag identification method, which is applied to a cloud server in a garbage source classification and decrement integrated service platform, where the garbage source classification and decrement integrated service platform includes a cloud server and a classification garbage can, and the method includes:

receiving a first image data set, ambient light and a first distance data set uploaded by the classified garbage can;

analyzing, identifying and processing the first image data set and the first distance data set to obtain a processing result;

and generating a delivery record of the target user according to the processing result, and generating an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for trading in a virtual mall provided by the garbage source classification and decrement comprehensive service platform and is used for supervising the authority application.

In a second aspect, embodiments of the present application provide a garbage source classification and deweighting integrated service platform, which includes a cloud server and a classification garbage can, the classification garbage can includes a distance detection device and an image acquisition device, wherein,

The distance detection device is arranged at the middle position of the outer side of the classified garbage can, the image acquisition device is arranged at the position above the middle of the classified garbage can, and the distance detection device is connected with the image acquisition device;

the distance detection device is used for detecting the distance of the user and the stay time of the user;

the image acquisition device is used for acquiring image data and uploading the image data to the cloud server when the user distance is smaller than a preset distance and the stay time is longer than a preset time;

the cloud server is used for carrying out image analysis and identification processing on the image data to obtain a processing result; and generating a delivery record of the target user according to the processing result and scoring to generate the environmental protection gold.

In a third aspect, an embodiment of the present application provides a garbage bag identification apparatus, which is applied to a cloud server in a garbage source classification and decrement integrated service platform, where the garbage source classification and decrement integrated service platform includes a cloud server and a classification garbage can, and includes a processing unit and a communication unit,

the processing unit is used for receiving the first image data set, the ambient light and the first distance data set uploaded by the classified garbage can through the communication unit; analyzing, identifying and processing the first image data set and the first distance data set to obtain a processing result; and generating a delivery record of the target user according to the processing result, and generating an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for trading in a virtual mall provided by the garbage source classification decrement comprehensive service platform and is used for supervising the authority application.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program causes a computer to perform some or all of the steps as described in any of the methods of the first aspect of the embodiments of the present application.

In a fifth aspect, embodiments of the present application provide a computer program product, wherein the computer program product comprises a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in any of the methods of the first aspect of embodiments of the present application. The computer program product may be a software installation package.

It can be seen that in the embodiment of the present application, the cloud server receives the first image data set, the ambient light and the first distance data set uploaded by the classification garbage can; then, analyzing, identifying and processing the first image data set and the first distance data set to obtain a processing result; and finally, generating a delivery record of the target user according to the processing result, and generating an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for trading in a virtual mall provided by the garbage source classification decrement comprehensive service platform and is used for supervising the authority application. Therefore, the cloud server processes the first image data set, the ambient light and the first distance data set uploaded by the classified garbage can to obtain a processing result, a delivery record of the target user is generated according to the processing result, the environmental protection deposit is generated, the garbage throwing person and the garbage throwing garbage are combined, the garbage classification is monitored, the accuracy of generating the environmental protection deposit for the target user is improved, the enthusiasm of resident garbage classification is increased, the environmental protection and energy saving consciousness of residents is improved, the environmental pollution is reduced, and the community garbage classification can be continuously developed.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic flow chart of a garbage bag identification method provided in an embodiment of the present application;

FIG. 2 is a schematic flow chart of another method for identifying garbage bags according to an embodiment of the present application;

FIG. 3 is a schematic flow chart of another garbage bag identification method according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of a garbage source classification decrement comprehensive service platform provided in an embodiment of the present application;

fig. 5 is a functional unit composition block diagram of a garbage bag identification device provided in an embodiment of the present application.

Detailed Description

In order to make the present application solution better understood by those skilled in the art, the following description will clearly and completely describe the technical solution in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.

The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The cloud server, also referred to as a server, according to the embodiments of the present application is a device that provides computing services. Including various types of servers with communication and data processing, the construction of which includes processors, hard disks, memory, system buses, etc., is similar to a general-purpose computer architecture, but is highly demanding in terms of processing power, stability, reliability, security, scalability, manageability, etc., due to the need to provide highly reliable services.

The embodiments of the present application are described in detail below.

Referring to fig. 1, fig. 1 is a schematic flow chart of a garbage bag identification method applied to a cloud server in a garbage source classification and decrement integrated service platform, wherein the garbage source classification and decrement integrated service platform comprises the cloud server and a classification garbage can; as shown in the figure, the garbage bag identification method comprises the following steps:

s101, a cloud server receives a first image data set, ambient light and a first distance data set uploaded by the classified garbage can;

the first image data set comprises image data containing a user image and a garbage bag image at the same time, and the first distance set comprises a distance corresponding to each image data in the first image data set.

S102, the cloud server analyzes, identifies and processes the first image data set and the first distance data set to obtain a processing result;

the cloud server processes the image data set, determines the identity information of the target user and the garbage bag information delivered by the target user, and obtains a processing result according to the distance from the target user to the classified garbage can when delivering the garbage bag.

And S103, the cloud server generates a delivery record of the target user according to the processing result, and generates an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for conducting transactions in a virtual mall provided by the garbage source classification decrement comprehensive service platform and is used for supervising authority application.

And generating a successful delivery record and an error delivery record according to the obtained processing result, generating different environmental protection gold amounts according to different successful delivery records, and deducting the environmental protection gold according to the error delivery record.

In one possible example, the analyzing, identifying and processing the first image data set and the first distance data set to obtain a processing result includes: acquiring a first characteristic value of a pre-stored sample image; acquiring a second characteristic value of each image in the first image data set; comparing the second characteristic value with the first characteristic value, screening a second image data set meeting a preset condition, wherein the preset condition is that the characteristic values are the same or the characteristic values are in a matching range, and the second image data set comprises image data simultaneously comprising a user image and a garbage bag image; and carrying out analysis and identification processing according to the second image data set to obtain a processing result.

The method comprises the steps of obtaining a first characteristic value of a pre-stored sample image, wherein the sample image can be an image which is shot in advance and simultaneously contains a user image and a garbage bag image, and the first characteristic value comprises a human body characteristic value and a garbage bag characteristic value. And acquiring and receiving the characteristic value of the user human body image and the characteristic value of the garbage bag in the first image data, comparing the characteristic value of the user human body image and the characteristic value of the garbage bag in the first image data with the first characteristic value of the sample image, and screening out a high-quality second image data set containing the user image and the garbage bag image simultaneously based on image data of which the image quality is not satisfied with the preset condition. For image data which does not meet the preset condition based on image quality exclusion, the quality of all target images can be evaluated from the aspects of illumination, blurring and the like based on the image quality for the first image data set, and the image data which does not meet the preset condition such as illumination, definition and the like can be excluded.

In this example, the cloud server can preset the first characteristic value of the sample image and the second characteristic value of the collected first image data set, match the first characteristic value with the second characteristic value, screen out the second image data set meeting the preset condition, and improve the image processing efficiency and accuracy.

In one possible example, the analyzing, identifying and processing the first image data set and the first distance data set to obtain a processing result includes: when the target user is identified as front delivery, acquiring a user image set of an area where the current equipment is located; comparing the target user image with the user image set to determine the identity information of the target user; or when the target user is identified as front delivery, obtaining a face characteristic value of the target user through a face image of the target user and a preset face model; comparing the face characteristic value with a preset face characteristic value set to determine the identity information of the target user; or when the target user is detected to be side delivery, acquiring a face image and a body appearance characteristic of the target user; determining identity information of the target user according to the face image and the body appearance characteristics; determining a first distance from the target user to deliver the garbage according to the first distance data set; determining color information of garbage bags in the second image data set, and judging the types of the garbage bags according to the color information, wherein the types of the garbage bags comprise dry garbage bags and wet garbage bags; obtaining appearance states of the garbage bags according to the second image data set, wherein the appearance states comprise dirt states and damage states; determining the garbage bag information according to the color information and the appearance state; and determining a processing result according to the identity information of the target user, the first distance and the garbage bag information.

When the cloud server detects that the first data set contains face images of the front face of a user, the face images are acquired, all face image sets of the user in a preset area where a classification garbage can for uploading the first image data is located are acquired, the face images are compared with all face image sets of the user, identity information of a target user corresponding to the face images is determined, and the identity information comprises names, resident unit numbers and the like. When the cloud server detects that the first data set contains the face image on the front face of the user, the identity information of the target user can be obtained by extracting the characteristic value of the face image of the user in the first data set and then importing the characteristic value of the face image of the user into a preset face model. When the cloud server does not detect the face image on the front side of the user, namely when the user delivers garbage, the cloud server obtains the face image of the side face of the user and the characteristic value of the face image of the side face, and the body state characteristics of the user in the first image set are obtained, wherein the body state characteristics comprise: the reminding feature, the head shape feature, the leg shape feature, the gesture motion feature, the head motion feature and the limb motion feature are compared with the body state features in the pre-stored body state feature set to determine the identity information of the target user. After the physical characteristics of the user in the first image set are acquired, a camera monitoring image in a preset area where the classified garbage can uploading the first image data is located can be applied to acquire, and the identity information of the target user is determined by monitoring and tracking the target user according to the physical characteristics of the user and the camera monitoring image.

And correlating each piece of first image data with a first distance from a user to the classified garbage can when the user shoots the first image data.

And determining color information of the garbage bags according to the garbage bag images in the second image data set, and judging the types of the garbage bags according to the color information, wherein the types of the garbage bags comprise dry garbage bags and wet garbage bags. For example, different colors of garbage bags are classified in advance, red garbage bags are dry garbage bags, blue garbage bags are wet garbage bags, and when garbage bags delivered by users in the second image data set are blue, the garbage bags are wet garbage bags correspondingly. And then judging the appearance state of the garbage bag, such as a dirty state and a broken state.

And determining a processing result according to the identity information of the target user, the first distance and the garbage bag information, for example, the user A delivers a blue wet garbage bag without stains, damages and the like at a position 0.3 m away from the garbage can.

In this example, the cloud server may determine identity information of the target user by performing face recognition or morphological feature comparison and identification on the front side or the side of the user, determine a distance from the target user to the trash can when delivering the trash through the first distance data set, determine trash bag information through the trash bag image, and further obtain a processing result for the second image set.

In one possible example, the determining the color information of the trash bag in the second image data set includes: acquiring the color of the ambient light; acquiring first reflected light of a garbage bag in preset ambient light, wherein the preset ambient light is a plurality of mixed weighted lights of three primary colors of red, green and blue; determining the color of the garbage bag according to the color of the ambient light and the first reflected light.

The color of the ambient light is uploaded by the classified garbage can, and the classified garbage can collect the color of the ambient light through the image collecting device or collect the color of the ambient light through setting an ambient light sensor. The preset ambient light is a plurality of mixed weighted lights of three primary colors of red, green and blue, and the preset ambient light is the same as the current ambient light.

In specific implementation, after the color of the environmental light is obtained, the environmental light can be firstly judged to determine whether the current environmental light has an influence on the judgment of the color of the garbage bag, if so, the color of the garbage bag in the obtained environmental light is compared with the color of the first reflected light of the garbage bag in the preset environmental light to determine the first reflected light with the most similar or same color, and the color of the garbage bag is determined. For example, the garbage bag a is purple in the current ambient light (assuming that only red and blue garbage bags are present), and the color of the garbage bag a is determined to be blue according to the difference in color of the first reflected light of the two garbage bags in the preset ambient light.

In this example, the cloud server can determine the intrinsic color of the garbage bag based on the color of the garbage bag in the ambient light and the ambient light, so that the influence of the ambient light on determining the color of the garbage bag is eliminated, and the accuracy of judging the color of the garbage bag and obtaining the processing result is improved.

In one possible example, the generating a delivery record of the target user according to the processing result, and generating an environmental protection gold according to the delivery record, includes: acquiring identification information of the classified garbage can; judging whether the garbage delivery behavior of the target user is accurate or not according to the garbage bag type and the identification information; if yes, generating a delivery record of the target user according to the appearance state of the garbage bag and the first distance, and generating an environmental protection gold according to the delivery record; if not, sending an alarm instruction to the classified garbage can, wherein the alarm instruction is used for sending alarm information to the classified garbage can to prompt the target user to incorrectly deliver garbage; if the target user is detected not to be processed within the preset time, generating an error delivery record of the target user, and scoring the delivery record.

The method comprises the steps of obtaining identification information of a classified garbage can, wherein the identification information comprises the type of the current classified garbage can, and the type comprises a dry garbage can and a wet garbage can.

In a specific implementation, when the classified garbage can uploads data such as the first image data, the serial numbers of the classified garbage can be uploaded at the same time, and the serial numbers are related to the categories of the classified garbage can. When the class of the garbage bag is matched with the class of the classified garbage bin, the garbage bag is correctly delivered, for example, the red garbage bag is a dry garbage bag, the dry garbage bin is put into, namely, the target user correctly delivers the garbage, otherwise, if the blue garbage bag is a wet garbage bag, the dry garbage bin is put into, namely, the target user incorrectly delivers the garbage. If the target user correctly delivers the garbage, determining the distance and the appearance state of the garbage bag when the target user delivers the garbage bag, and generating the environmental protection gold according to different grades. For example, if the target user a delivers the garbage bag in the first preset range, the final environmental protection gold is calculated according to the first preset proportion (e.g. 100%) of the preset environmental protection gold, if the target user a delivers the garbage bag in the second preset range, the final environmental protection gold is calculated according to the second preset proportion (e.g. 90%) of the preset environmental protection gold, etc.; and calculating the environmental protection gold according to different proportions according to the appearance state of the garbage bag, for example, calculating the final environmental protection gold according to a third preset proportion (for example, 30%) of the damage degree of the garbage bag and a fourth preset proportion (for example, 90%) of the environmental protection gold. If the target user fails to deliver the garbage, an alarm instruction is sent to the classified garbage can, so that the classified garbage can sends out prompt information to prompt the target user to deliver the garbage in error, the target user can conveniently deliver the garbage bag again, if the target user fails to deliver the garbage bag again correctly within the preset time, an error delivery record of the target user is generated, and preset punishment measures are taken for the target user aiming at the error delivery record.

In this example, the cloud server can determine the delivery behavior of the target according to the garbage bin type, the garbage bag type and the appearance state of the garbage bag, and generate the corresponding delivery record and the environmental protection gold, so that the accuracy of generating the environmental protection gold and the delivery record is ensured.

In one possible example, the cloud server identifies target user images in all the first image data sets uploaded by the classified garbage can, obtains the number of target user people delivering garbage, detects other classified garbage cans in a preset range of the area where the current classified garbage can is located when the number of target user people is greater than the preset number of people, and pushes suggestions for delivering garbage to the other classified garbage cans to the user of the area where the current classified garbage can is located.

In specific implementation, all the first image data sets refer to all image data collected by the classified garbage can after being cleaned, the number of people delivering garbage is determined by identifying target user images in the first image data sets, when the number of people delivering garbage exceeds a preset number, a cloud server obtains the position of the current classified garbage can, then queries other classified garbage cans in the preset range of the current position, detects whether the number of people delivering garbage in the other classified garbage cans exceeds the preset number of people through the image data uploaded by the other classified garbage cans, and if the number of people delivering garbage in the other classified garbage cans does not exceed the preset number of people, pushes suggestions for delivering garbage in the other garbage cans to users in the preset range of the position of the current classified garbage can.

In this example, the cloud server may recommend other classified garbage cans to the user when the number of delivery people of the current garbage can reaches a preset number, so as to reduce the load of the current classified garbage can and balance the garbage can load in the preset area.

In one possible example, when the cloud server recognizes that the garbage amount of the current garbage can reaches a preset value through the classified garbage can, the cloud server detects other classified garbage cans within a preset range of the area where the current classified garbage can is located, and pushes suggestions for delivering garbage to the other classified garbage cans to a user of the area where the current classified garbage can is located.

In particular implementations, the identification of the current trash amount by the sorting trash can may include, but is not limited to, capturing an image by a camera device mounted on the sorting trash can. For example, the cloud server determines that the garbage amount of the current garbage can reaches a preset value through the image uploaded by the classified garbage can a, the cloud server acquires the position of the classified garbage can a, queries other classified garbage cans in the preset range of the current position, determines the garbage amount through the image data uploaded by the other classified garbage cans, and pushes a suggestion for delivering garbage to the other garbage cans to a user in the preset range of the position of the current classified garbage can if the garbage amount of the other classified garbage cans does not reach the preset value.

In this example, it can be seen that when the current garbage can amount reaches the preset value, the cloud server recommends other classified garbage cans to the user, so as to reduce the load of the current classified garbage can and balance the garbage can load in the preset area.

In one possible example, before receiving the first image data set, the ambient light, and the first distance data set uploaded by the classification garbage, the method further comprises: detecting the user distance and the user stay time by a distance detection device of the classified garbage can; when the distance of the user is detected to be smaller than a preset distance and the stay time is longer than a preset time by the distance detection device, acquiring a first image data set and ambient light by the image acquisition device, and acquiring a corresponding first distance data set by the distance detection device; uploading the first image data set, ambient light, and the first distance data set through the classification garbage can.

The distance detection device can be an ultrasonic distance detection device, an infrared distance detection device and the like, and is arranged at the middle upper position of the classified garbage can. The image data and the ambient light are acquired by an image acquisition device such as a camera, etc., the ambient light can also be detected by an ambient light sensor, and the image acquisition device and/or the ambient light sensor can be arranged at the middle-upper position of the classified garbage can or on the barrel cover of the classified garbage can with the cover. Distance detection means and image acquisition means and/or ambient light sensors may be provided on multiple sides of a sorting bin to facilitate detection of user delivery of waste from different directions to the sorting bin.

In the specific implementation, when the distance between the user and the classified garbage can is smaller than a preset distance and the residence time in the preset distance is longer than a preset duration, the image of the user and surrounding ambient light are collected.

In this example, the first image data set, the ambient light and the first distance data set received by the cloud server are detected in real time through the classified garbage can, so that accuracy and effectiveness of analysis and processing of delivery behaviors of the user are ensured.

In one possible example, when the distance of the user is detected by the distance detection device to be smaller than a preset distance and the stay time period is longer than a preset time period, acquiring, by the image acquisition device, a first image data set and ambient light, and acquiring, by the distance detection device, a corresponding first distance data set includes: pre-shooting through the image acquisition device to obtain a first image; pre-judging whether the first image has effective delivery behaviors of a user or not; if yes, sending a shooting instruction to the classification garbage can, shooting for a plurality of times through the image acquisition device, and acquiring a first image data set; if not, deleting the first image, and not sending a shooting instruction.

The cloud server determines whether the image has the action of delivering garbage by a user, namely whether the image has the appearance of the user and the garbage bag, and sends shooting instructions to the image acquisition device of the classified garbage can, the image acquisition device starts to acquire image books for many times to form a first image data set, if the image does not appear, the pre-shot image is deleted and the subsequent shooting is not performed, and the image acquisition device is excluded from acquiring the image due to animals or other conditions.

In this example, the cloud server sets the pre-shot secondary shooting collected image data set by the classification garbage can and uploads the collected image data set to obtain the first image data set, so that accuracy of collected data is improved, invalid image data is prevented from being analyzed and processed, resources are saved, and accuracy and efficiency of image analysis and processing are improved.

In one possible example, the sorting waste bin further comprises an alarm device, the method further comprising: and sending an alarm instruction to the classified garbage can, wherein the alarm instruction is used for sending alarm information through an alarm device after the classified garbage can receives the alarm instruction, and the alarm information comprises voice information and is used for prompting the current delivery behavior error of the target user.

When the cloud server determines that the user has wrong delivery, an alarm instruction is sent to the dustbin, and after the dustbin receives the alarm instruction, alarm information is sent, wherein the alarm information comprises voice prompt information for prompting that the user delivers the wrong delivery at present and needs to deliver the wrong delivery again.

In this example, the cloud server controls the classified garbage can to send out prompt information by sending an alarm instruction, so as to prompt the user of wrong delivery behavior, and thus the probability of correctly delivering garbage by the user is improved.

Consistent with the embodiment shown in fig. 1, referring to fig. 2, fig. 2 is a schematic flow chart of a garbage bag identification method provided in an embodiment of the present application, which is applied to a cloud server in a garbage source classification and decrement integrated service platform, where the garbage source classification and decrement integrated service platform includes a cloud server and a classification garbage can, as shown in the figure, the garbage bag identification method includes:

s201, the cloud server performs pre-shooting through the image acquisition device to obtain a first image;

s202, the cloud server prejudges whether the first image has effective delivery behaviors of a user or not;

s203, if yes, the cloud server shoots for a plurality of times through the image acquisition device, acquires a first image data set and ambient light, and acquires a corresponding first distance data set through the distance detection device;

S204, the cloud server receives a first image data set, ambient light and a first distance data set uploaded by the classified garbage can;

s205, the cloud server analyzes, identifies and processes the first image data set and the first distance data set to obtain a processing result;

s206, the cloud server generates a delivery record of the target user according to the processing result, and generates an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for conducting transactions in a virtual mall provided by the garbage source classification decrement comprehensive service platform and is used for supervising authority application.

In addition, the cloud server obtains the first image data set by setting the pre-shooting secondary shooting collected image data set through the classified garbage bin and uploading the collected image data set, so that the accuracy of collected data is improved, invalid image data is prevented from being analyzed and processed, resources are saved, and the accuracy and efficiency of image analysis and processing are improved.

In accordance with the embodiment shown in fig. 1, please refer to fig. 3, fig. 3 is a schematic flow chart of a method provided in an embodiment of the present application, which is applied to an electronic device, where the electronic device includes a radar sensor, and as shown in the drawing, the method includes:

s301, a cloud server receives a first image data set, ambient light and a first distance data set uploaded by the classified garbage can;

s302, when the cloud server identifies that the target user is front delivery, acquiring a user image set of an area where the current equipment is located;

s303, the cloud server compares the target user image with the user image set to determine the identity information of the target user;

s304, the cloud server determines a first distance for delivering garbage by the target user according to the first distance data set;

S305, the cloud server determines color information of garbage bags in the second image data set, and judges the types of the garbage bags according to the color information, wherein the types of the garbage bags comprise dry garbage bags and wet garbage bags;

s306, the cloud server acquires appearance states of the garbage bags according to the second image data set, wherein the appearance states comprise a dirt state and a damage state;

s307, the cloud server determines the garbage bag information according to the color information and the appearance state;

s308, the cloud server determines a processing result according to the identity information of the target user, the first distance and the garbage bag information;

s309, the cloud server generates a delivery record of the target user according to the processing result, and generates an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for conducting transactions in a virtual mall provided by the garbage source classification decrement comprehensive service platform and is used for supervising authority application.

In addition, the cloud server can determine the identity information of the target user through face recognition or morphological feature comparison and identification of the front face of the user, determine the distance from the target user to the garbage can when delivering garbage through the first distance data set, determine the garbage bag information through the garbage bag image, and further obtain the processing result aiming at the second image set.

In accordance with the embodiments shown in fig. 1, 2 and 3, referring to fig. 4, fig. 4 is a schematic diagram of a comprehensive service platform for garbage source classification and decrement according to an embodiment of the present application, as shown in the foregoing, the comprehensive service platform for garbage source classification and decrement includes a cloud server 410 and a classified garbage can 420, and the classified garbage can 420 includes a distance detecting device 421 and an image collecting device 422, where,

the distance detection device is arranged at the middle position of the outer side of the classified garbage can, the image acquisition device is arranged at the position above the middle of the classified garbage can, and the distance detection device is connected with the image acquisition device; the distance detection device is used for detecting the distance of the user and the stay time of the user; the image acquisition device is used for acquiring image data and uploading the image data to the cloud server when the user distance is smaller than a preset distance and the stay time is longer than a preset time; the cloud server is used for carrying out image analysis and identification processing on the image data through the cloud server to obtain a processing result; and generating a delivery record of the target user according to the processing result and scoring to generate the environmental protection gold.

In a possible example, the classification garbage can 420 further includes a prompting device 423, where the prompting device is configured to receive the prompting information sent by the cloud server and alarm with the prompting device, and the prompting information includes voice information, and is configured to prompt the target user that the delivery behavior is wrong currently.

The foregoing description of the embodiments of the present application has been presented primarily in terms of a method-side implementation. It will be appreciated that the electronic device, in order to achieve the above-described functions, includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied as hardware or a combination of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The embodiment of the application may divide the functional units of the electronic device according to the above method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated in one processing unit. The integrated units may be implemented in hardware or in software functional units. It should be noted that, in the embodiment of the present application, the division of the units is schematic, which is merely a logic function division, and other division manners may be implemented in actual practice.

Fig. 5 is a functional block diagram of a garbage bag identification apparatus 500 according to an embodiment of the present application. The garbage bag identification device 500 is applied to a cloud server in a garbage source classification and decrement integrated service platform, wherein the garbage source classification and decrement integrated service platform comprises the cloud server and a classification garbage can, and comprises a processing unit 501 and a communication unit 502,

the processing unit 501 is configured to receive, through the communication unit 502, the first image data set, the ambient light, and the first distance data set uploaded by the classification garbage; analyzing, identifying and processing the first image data set and the first distance data set to obtain a processing result; and generating a delivery record of the target user according to the processing result, and generating an environmental protection fee according to the delivery record, wherein the environmental protection fee is used for trading in a virtual mall provided by the garbage source classification decrement comprehensive service platform and is used for supervising the authority application.

The garbage bag identifying apparatus 500 may further include a storage unit 503 for storing program codes and data of the electronic device. The processing unit 501 may be a processor, the communication unit 502 may be a touch display screen or a transceiver, and the storage unit 503 may be a memory.

In one possible example, in terms of the analysis and identification processing performed on the first image data set and the first distance data set to obtain a processing result, the processing unit 501 is specifically configured to: acquiring a first characteristic value of a pre-stored sample image; acquiring a second characteristic value of each image in the first image data set; comparing the second characteristic value with the first characteristic value, screening a second image data set meeting a preset condition, wherein the preset condition is that the characteristic values are the same or the characteristic values are in a matching range, and the second image data set comprises image data simultaneously comprising a user image and a garbage bag image; and carrying out analysis and identification processing according to the second image data set to obtain a processing result.

In one possible example, in terms of the analysis and identification processing performed on the first image data set and the first distance data set to obtain a processing result, the processing unit 501 is specifically configured to: when the target user is identified as front delivery, acquiring a user image set of an area where the current equipment is located; comparing the target user image with the user image set to determine the identity information of the target user; or when the target user is identified as front delivery, obtaining a face characteristic value of the target user through a face image of the target user and a preset face model; comparing the face characteristic value with a preset face characteristic value set to determine the identity information of the target user; or when the target user is detected to be side delivery, acquiring a face image and a body appearance characteristic of the target user; determining identity information of the target user according to the face image and the body appearance characteristics; determining a first distance from the target user to deliver the garbage according to the first distance data set; determining color information of garbage bags in the second image data set, and judging the types of the garbage bags according to the color information, wherein the types of the garbage bags comprise dry garbage bags and wet garbage bags; obtaining appearance states of the garbage bags according to the second image data set, wherein the appearance states comprise dirt states and damage states; determining the garbage bag information according to the color information and the appearance state; and determining a processing result according to the identity information of the target user, the first distance and the garbage bag information.

In one possible example, in said determining the color information of the garbage bags in said second image data set, said processing unit 501 is specifically configured to: acquiring the color of the ambient light; acquiring first reflected light of a garbage bag in preset ambient light, wherein the preset ambient light is a plurality of mixed weighted lights of three primary colors of red, green and blue; determining the color of the garbage bag according to the color of the ambient light and the first reflected light.

In one possible example, in the aspect of generating a delivery record of the target user according to the processing result and generating an environmental protection fee according to the delivery record, the processing unit 501 is specifically configured to: acquiring identification information of the classified garbage can; judging whether the garbage delivery behavior of the target user is accurate or not according to the garbage bag type and the identification information; if yes, generating a delivery record of the target user according to the appearance state of the garbage bag and the first distance, and generating an environmental protection gold according to the delivery record; if not, sending an alarm instruction to the classified garbage can, wherein the alarm instruction is used for sending alarm information to the classified garbage can to prompt the target user to incorrectly deliver garbage; if the target user is detected not to be processed within the preset time, generating an error delivery record of the target user, and scoring the delivery record.

In one possible example, the processing unit 501, before receiving the first image data set, the ambient light, and the first distance data set uploaded by the classification garbage, is further configured to: detecting the user distance and the user stay time by a distance detection device of the classified garbage can; when the distance of the user is detected to be smaller than a preset distance and the stay time is longer than a preset time by the distance detection device, acquiring a first image data set and ambient light by the image acquisition device, and acquiring a corresponding first distance data set by the distance detection device; uploading the first image data set, ambient light, and the first distance data set through the classification garbage can.

In one possible example, when the user distance is detected by the distance detection device to be smaller than a preset distance and the stay time period is longer than a preset time period, the processing unit 501 is specifically configured to, in terms of acquiring, by the image acquisition device, a first image data set and ambient light, and acquiring, by the distance detection device, a corresponding first distance data set: pre-shooting through the image acquisition device to obtain a first image; pre-judging whether the first image has effective delivery behaviors of a user or not; if yes, sending a shooting instruction to the classified garbage can, shooting for a plurality of times through the image acquisition device, acquiring a first image data set and ambient light, and acquiring a corresponding first distance data set through the distance detection device; if not, deleting the first image, and not sending a shooting instruction.

In one possible example, the sorting waste bin further comprises an alarm device, and the processing unit 501 is further configured to: and sending an alarm instruction to the classified garbage can, wherein the alarm instruction is used for sending alarm information through an alarm device after the classified garbage can receives the alarm instruction, and the alarm information comprises voice information and is used for prompting the current delivery behavior error of the target user.

The embodiment of the application also provides a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, where the computer program causes a computer to execute part or all of the steps of any one of the methods described in the embodiments of the method, where the computer includes an electronic device.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any one of the methods described in the method embodiments above. The computer program product may be a software installation package, said computer comprising an electronic device.

It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, such as the above-described division of units, merely a division of logic functions, and there may be additional manners of dividing in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, or may be in electrical or other forms.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units described above, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the above-mentioned method of the various embodiments of the present application. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be implemented by a program that instructs associated hardware, and the program may be stored in a computer readable memory, which may include: flash disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.

The foregoing has outlined rather broadly the more detailed description of embodiments of the present application, wherein specific examples are provided herein to illustrate the principles and embodiments of the present application, the above examples being provided solely to assist in the understanding of the methods of the present application and the core ideas thereof; meanwhile, as those skilled in the art will have modifications in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.

Claims

1. The method is characterized by being applied to a cloud server in a garbage source classification and decrement integrated service platform, wherein the garbage source classification and decrement integrated service platform comprises the cloud server and a classification garbage can, and the method comprises the following steps:

preprocessing the first image data set to obtain a second image data set, wherein the second image data set comprises image data of a target user and image data of a garbage bag;

determining a first distance from the target user to deliver the garbage according to the first distance data set;

acquiring the color of the ambient light;

acquiring first reflected light of a garbage bag in preset ambient light, wherein the preset ambient light is a plurality of mixed weighted lights of three primary colors of red, green and blue;

determining the color of the garbage bag according to the color of the ambient light and the first reflected light;

judging the types of the garbage bags according to the colors of the garbage bags, wherein the types of the garbage bags comprise dry garbage bags and wet garbage bags;

obtaining appearance states of the garbage bags according to the image data of the garbage bags, wherein the appearance states comprise dirt states and damage states;

determining garbage bag information according to the garbage bag category and the appearance state;

determining a processing result according to the identity information of the target user, the first distance and the garbage bag information, wherein the determining process of the identity information of the target user comprises the following steps:

When the target user is identified as front delivery, acquiring a user image set of an area where the current equipment is located;

comparing the image data of the target user with the user image set to determine the identity information of the target user; or alternatively, the first and second heat exchangers may be,

when the target user is identified as front delivery, a face characteristic value of the target user is obtained through a face image of the target user and a preset face model;

comparing the face characteristic value with a preset face characteristic value set to determine the identity information of the target user; or alternatively, the first and second heat exchangers may be,

when the target user is detected to be side delivery, acquiring a face image and a body appearance characteristic of the target user;

determining identity information of the target user according to the face image and the body appearance characteristics;

2. The method of claim 1, wherein preprocessing the first set of image data to obtain a second set of image data comprises:

Acquiring a first characteristic value of a pre-stored sample image;

acquiring a second characteristic value of each image in the first image data set;

and comparing the second characteristic value with the first characteristic value, and screening out a second image data set meeting a preset condition, wherein the preset condition is that the characteristic values are the same or the characteristic values are in a matching range.

3. The method according to claim 1 or 2, wherein generating a delivery record of the target user according to the processing result, generating an environmental protection fee according to the delivery record, comprises:

acquiring identification information of the classified garbage can;

judging whether the garbage delivery behavior of the target user is accurate or not according to the garbage bag type and the identification information;

if yes, generating a delivery record of the target user according to the appearance state of the garbage bag and the first distance, and generating an environmental protection gold according to the delivery record;

if not, sending an alarm instruction to the classified garbage can, wherein the alarm instruction is used for sending alarm information to the classified garbage can to prompt the target user to incorrectly deliver garbage;

if the fact that the target user does not deliver the garbage bags correctly again within the preset time is detected, generating an error delivery record of the target user, and scoring the error delivery record.

4. The method of claim 1, wherein the sorting bin comprises a distance detection device and an image acquisition device, and further comprising, prior to receiving the first image data set, the ambient light, and the first distance data set uploaded by the sorting bin:

detecting the distance of the user and the stay time of the user through the distance detection device;

when the distance detection device detects that the user distance is smaller than a preset distance and the stay time is longer than a preset time, acquiring a first image data set and ambient light through the image acquisition device, and acquiring a corresponding first distance data set through the distance detection device;

uploading the first image data set, ambient light, and the first distance data set through the classification garbage can.

5. The method of claim 4, wherein the acquiring, by the image acquisition device, a first set of image data and ambient light and the corresponding first set of distance data by the distance detection device when the user distance is detected by the distance detection device to be less than a preset distance and the dwell time is longer than a preset duration, comprises:

Pre-shooting through the image acquisition device to obtain a first image;

pre-judging whether the first image has effective delivery behaviors of a user or not;

if yes, sending a shooting instruction to the classified garbage can, shooting for a plurality of times through the image acquisition device, acquiring a first image data set and ambient light, and acquiring a corresponding first distance data set through the distance detection device;

if not, deleting the first image, and not sending a shooting instruction.

6. The method of claim 4, wherein the sorting waste bin further comprises a reminder device, the method further comprising:

and sending an alarm instruction to the classified garbage can, wherein the alarm instruction is used for sending alarm information through a prompting device after the classified garbage can receives the alarm instruction, and the alarm information comprises voice information and is used for prompting the current delivery behavior error of the target user.

7. A garbage source classification decrement comprehensive service platform is characterized by comprising a cloud server and a classification garbage can, wherein the classification garbage can comprises a distance detection device and an image acquisition device,

the cloud server is configured to perform the steps of the method according to any of claims 1-6.

8. The garbage source classification decrement comprehensive service platform according to claim 7, wherein the classification garbage can further comprises a prompting device, the prompting device is used for receiving an alarm instruction sent by the cloud server and sending alarm information through the prompting device, and the alarm information comprises voice information and is used for prompting the current delivery behavior errors of the target user.