CN109146030B - Low-carbon consumption identification method and device and electronic equipment - Google Patents
Low-carbon consumption identification method and device and electronic equipment Download PDFInfo
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Abstract
The application discloses a low-carbon consumption identification method, a low-carbon consumption identification device and electronic equipment, wherein the method comprises the following steps: responding to a low-carbon consumer goods identification request of the user, and acquiring image information of the consumer goods scanned by the user; inputting the image information into a low-carbon consumer goods matching model, and determining the type of the consumer goods; acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user; obtaining payment information of the user, wherein the payment information comprises payment time and a payment object; determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
Description
Technical Field
The application relates to the technical field of computers, in particular to a low-carbon consumption identification method and device and electronic equipment.
Background
Due to the continuous accumulation of the greenhouse effect, the energy absorbed and emitted by the ground gas system is unbalanced, and the energy is continuously accumulated in the ground gas system, so that the temperature is increased, and the global warming is caused. In order to relieve global warming, low-carbon consumption behaviors are advocated to the utmost in all countries in the world.
However, many consumption behaviors which are contrary to low-carbon consumption behaviors still exist in daily life of some users, for example, the users use disposable tableware when dining in restaurants and use plastic shopping bags which are difficult to degrade when shopping in supermarkets. With the increasing enhancement of environmental awareness of more and more users, many users consciously select low-carbon consumption behaviors during consumption, such as selecting environment-friendly tableware during dining and selecting degradable environment-friendly shopping bags during shopping in supermarkets.
Therefore, how to effectively identify the low-carbon consumption behavior of the user and further encourage more and more users to participate in the low-carbon consumption behavior still needs to be solved urgently.
Disclosure of Invention
The embodiment of the application provides a low-carbon consumption identification method and device and electronic equipment, and aims to solve the problem that the low-carbon consumption behavior of a user cannot be effectively identified in the prior art.
In order to solve the above technical problem, the embodiment of the present application is implemented as follows:
in a first aspect, a low carbon consumption identification method is provided, including:
responding to a low-carbon consumer goods identification request of the user, and acquiring image information of the consumer goods scanned by the user;
inputting the image information into a low-carbon consumer goods matching model, and determining the type of the consumer goods;
acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
obtaining payment information of the user, wherein the payment information comprises payment time and a payment object;
determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
In a second aspect, an identification apparatus for low carbon consumption is provided, including:
the first acquisition unit is used for responding to a low-carbon consumer goods identification request of the user and acquiring image information of consumer goods scanned by the user;
the first determining unit is used for inputting the image information into a low-carbon consumer goods matching model and determining the type of the consumer goods;
the second acquisition unit is used for acquiring the type of the consumer goods, the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
a third acquisition unit configured to acquire payment information of the user, the payment information including payment time and a payment object;
and the second determination unit is used for determining whether the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant based on the type of the consumer goods, the time for scanning the consumer goods, the information of the consumer merchant determined by the user and the payment information.
In a third aspect, an electronic device is provided, which includes:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to:
responding to a low-carbon consumer goods identification request of the user, and acquiring image information of the consumer goods scanned by the user;
inputting the image information into a low-carbon consumer goods matching model, and determining the type of the consumer goods;
acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
obtaining payment information of the user, wherein the payment information comprises payment time and a payment object;
determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
In a fourth aspect, a computer-readable storage medium is presented, the computer-readable storage medium storing one or more programs that, when executed by an electronic device that includes a plurality of application programs, cause the electronic device to:
responding to a low-carbon consumer goods identification request of the user, and acquiring image information of the consumer goods scanned by the user;
inputting the image information into a low-carbon consumer goods matching model, and determining the type of the consumer goods;
acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
obtaining payment information of the user, wherein the payment information comprises payment time and a payment object;
determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
The embodiment of the application can at least achieve the following technical effects by adopting the technical scheme:
the method can firstly respond to a low-carbon consumer goods identification request of a user, acquire image information of a consumer goods scanned by the user, input the image information into a low-carbon consumer goods matching model, determine the type of the consumer goods, acquire the time for scanning the consumer goods and the information of a consumer merchant determined by the user, and then acquire payment information of the user, wherein the payment information comprises payment time and payment objects, and finally, whether the consumer goods is the low-carbon consumer goods consumed by the user at the consumer merchant can be effectively determined based on the type of the consumer goods, the time for scanning the consumer goods, the information of the consumer merchant determined by the user and the payment information, so that when the consumer goods is determined to be the low-carbon consumer goods consumed by the user at the consumer merchant, the user or the consumer merchant of the user can be rewarded, and more users and merchants are encouraged to participate in low-carbon consumption, the problem that the low-carbon consumption behaviors of the user cannot be effectively identified in the prior art is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart of an implementation of a method for identifying low-carbon consumption behaviors, provided in an embodiment of the present specification;
fig. 2 is a schematic view of an implementation flow of a low-carbon consumption behavior recognition method applied in an actual scene according to an embodiment of the present disclosure;
fig. 3 is a schematic flow chart of an implementation process of the method for identifying low-carbon consumption behaviors, provided in an embodiment of the present specification, applied in another practical scenario;
fig. 4 is a schematic structural diagram of an apparatus for recognizing low carbon consumption behaviors, according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of another electronic device provided in an embodiment of the present specification.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
In order to solve the problem that the low-carbon consumption behavior of a user cannot be effectively identified in the prior art, embodiments of the present specification provide a method for identifying low-carbon consumption behavior. The execution subject of the recognition method for low-carbon consumption behaviors provided by the embodiment of the present disclosure may be, but is not limited to, a mobile phone, a tablet computer, a personal computer, and the like, which can be configured to execute at least one of the user terminals of the method provided by the embodiment of the present disclosure, or the execution subject of the method may also be a client itself capable of implementing the method provided by the embodiment of the present disclosure.
For convenience of description, the following description will be made of an embodiment of the method taking as an example that an execution subject of the method is a terminal device capable of executing the method. It is understood that the implementation of the method by the terminal device is only an exemplary illustration, and should not be construed as a limitation of the method.
Specifically, an implementation flow diagram of a method for identifying low-carbon consumption behaviors, provided by one or more embodiments of the present specification, is shown in fig. 1, and includes:
optionally, since the image recognition technology can scan the articles and recognize the articles, the characters and other contents in the pictures in real time based on the picture machine learning technology, one or more embodiments of the present specification may first obtain the image information of the low-carbon consumer articles scanned by the user in response to the identification request of the low-carbon consumer articles by the user based on this function of the image recognition technology.
In practical application, a user can enter a recognition entrance of low-carbon consumption behaviors to scan image information of environmental protection articles used in the consumption behaviors of the user, specifically, a set of environmental protection articles used by the user, such as a set of Chinese environmental protection tableware, often comprises environmental protection chopsticks, an environmental protection spoon, an environmental protection bowl, an environmental protection plate and an environmental protection cup, on one hand, in order to improve the accuracy of image recognition, only one environmental protection article in the set of environmental protection articles can be scanned each time until the set of environmental protection articles is scanned; on the other hand, the user can avoid the complex user experience brought to the user by scanning for many times, and the whole set of environment-friendly articles can be scanned at one time.
It should be noted that the number of the environmental protection articles refers to the number of the environmental protection articles included in a set of environmental protection articles, and for example, the set of Chinese environmental protection tableware includes 5 pieces of environmental protection tableware, and the types of the environmental protection tableware are respectively environmental protection chopsticks, environmental protection spoons, environmental protection bowls, environmental protection plates and environmental protection cups.
the low-carbon consumption article matching model is obtained by training based on the characteristic information of the low-carbon consumption articles in the historical time period and the type information of the corresponding low-carbon consumption articles. The low-carbon consumption article matching model can be obtained based on image training of environment-friendly articles uploaded by a plurality of users in a historical time period in an initial stage. After the training of the low-carbon consumption object matching model is completed, the number of environment-friendly objects and the number of corresponding environment-friendly objects contained in the image of the environment-friendly objects newly uploaded by the user can be identified based on the image of the environment-friendly objects newly uploaded by the user, namely, the type and the number of the environment-friendly objects contained in the image of the environment-friendly objects uploaded by the user can be identified by the low-carbon consumption object matching model, for example, the environment-friendly objects contained in the image of the environment-friendly objects uploaded by the user can be identified to be environment-friendly bowls, environment-friendly chopsticks and environment-friendly cups.
And when the sample data for training the low-carbon consumer goods matching model is larger and larger, images of environment-friendly goods in different merchants uploaded by different users are collected in a historical time period. Because the types and the number of the environment-friendly articles in each merchant have some differences, for example, the environment-friendly articles in the Chinese restaurant include environment-friendly tableware such as environment-friendly bowls, environment-friendly chopsticks, environment-friendly cups and environment-friendly dishes, the environment-friendly articles in the western restaurant include environment-friendly dishes, environment-friendly knives, environment-friendly forks, and corresponding merchant identifications are often found on the environment-friendly articles in each merchant, one or more embodiments of the present specification can extract the characteristics such as the number and the types of the environment-friendly articles corresponding to each merchant based on this point, that is, the low-carbon consumption behavior matching sub-model corresponding to each merchant can be trained based on the image of the environment-friendly articles uploaded by the user of each merchant.
That is to say, the low-carbon consumer item matching model may be trained based on the feature information of the low-carbon consumer item in the historical time period and the information of the corresponding consumer merchant. In practical application, the low-carbon consumption article matching model can be obtained by training based on a large number of low-carbon consumption features in a historical time period and information of corresponding consumption merchants in advance, taking a merchant a and a set of environment-friendly tableware B provided by the merchant a as an example, when training the merchant a and extracting low-carbon consumption feature information matched with the merchant a, a large number of pictures marked according to different tableware categories in the environment-friendly tableware B are collected, the pictures are identified and trained through machine learning, rules of the tableware in the pictures are identified, functions of identifying the tableware in the pictures are further realized, feature information of different tableware categories in the pictures is extracted, and the feature information is bound with corresponding merchant information, namely the information of the merchant a.
Optionally, each merchant corresponds to one low-carbon consumption behavior matching sub-model, so that the corresponding low-carbon consumption behavior matching sub-model may be determined based on the information of the consumption merchant determined by the user, and then the image information of the consumer item scanned by the user may be used as the input of the low-carbon consumption behavior matching sub-model to obtain the type of the consumer item. The corresponding low-carbon consumption behavior matching sub-model can be determined based on the information of the consumption commercial tenant, and the image information of the consumption article scanned by the user is not directly used as the input of the low-carbon consumption article matching model containing a large amount of characteristic information, so that the comparison range can be narrowed for determining whether the consumption article is the low-carbon consumption article consumed by the user at the consumption commercial tenant.
optionally, to more accurately provide the user with nearby merchant information for the user to make a selection, one or more embodiments of the present specification may provide the user with selectable consumer merchant information Based on the Location Based Service (LBS) address of the user. Then, the information of the consumer merchant determined by the user is obtained, specifically, the LBS address information of the user is obtained in response to the identification request of the low-carbon consumer goods of the user; then, acquiring a list of merchant information within a preset range of latitude and longitude coordinate data address information from a user; and finally, responding to the merchant selection operation of the user, and acquiring the information of the consumer merchant determined by the user.
in order to accurately determine whether the consumer goods are low-carbon consumer goods consumed by the user in the selected consumer merchant, the payment information of the user can be acquired, wherein the payment information comprises payment time and payment objects. And the payment time in the payment information is used for determining whether the time when the consumer goods are scanned by the user and the payment time are in the same preset time period. The preset time period may be, for example, half an hour, two hours, or ten and several minutes, and the like, that is, the interval between the payment time of the user in the consumer merchant and the time when the user scans the consumer goods is not too long.
The payment object in the payment information may be used to determine whether the consumer merchant determined by the user is the same merchant as the payment object. In the process of actually determining whether the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant, if the time for scanning the consumer goods and the payment time in the payment information are not in the same preset time period and/or the information of the consumer merchant is not consistent with the payment object in the payment information, it can be determined that the consumer goods are not the low-carbon consumer goods consumed by the user at the consumer merchant.
And 150, determining whether the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant based on the type of the consumer goods, the time for scanning the consumer goods, the information of the consumer merchant determined by the user and the payment information.
Optionally, determining whether the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant based on the type of the consumer goods, the time for scanning the consumer goods, the information of the consumer merchant determined by the user and the payment information, and specifically, if the type of the consumer goods is a low-carbon consumer goods, determining whether the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant based on the time for scanning the consumer goods, the information of the consumer merchant and the payment information; and if the type of the consumer item is a non-low-carbon consumer item, determining that the consumer item is not a low-carbon consumer item consumed by the user at the consumer merchant.
Optionally, determining whether the consumer goods are low-carbon consumer goods consumed by the user at the consumer goods merchant based on the time for scanning the consumer goods, the information of the consumer goods merchant determined by the user and the payment information, and specifically determining that the consumer goods are low-carbon consumer goods consumed by the user at the consumer goods merchant if the time for scanning the consumer goods and the payment time in the payment information are within the same preset time period and the information of the consumer goods merchant is consistent with the payment object in the payment information; and if the time for scanning the consumer goods and the payment time in the payment information are not in the same preset time period, and/or the information of the consumer merchant is inconsistent with the payment object in the payment information, determining that the consumer goods are not the low-carbon consumer goods consumed by the user at the consumer merchant.
Optionally, after determining that the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant, in order to identify whether the consumer item of the user in the consumer merchant is a low-carbon consumer item or not in a request of identifying whether counterfeiting exists or not, and the type of the consumer item of each merchant in a predetermined time is not changed greatly, the type of the consumer item of the consumer merchant in the predetermined time may also be obtained first; then, determining a low-carbon consumption article set owned by a consumption merchant based on the type of the consumption article of the consumption merchant in a preset time; and finally, determining whether the low-carbon consumer goods consumed by the user at the consumption merchant are true or not based on the low-carbon consumer goods set owned by the consumption merchant and the type of the consumer goods.
Optionally, determining whether the low-carbon consumer goods consumed by the user at the consumption merchant are true based on the low-carbon consumer goods set owned by the consumption merchant and the type of the consumer goods, and specifically determining that the low-carbon consumer goods consumed by the user at the consumption merchant are true if the type of the consumer goods belongs to the low-carbon consumer goods set owned by the consumption merchant; and if the type of the consumer goods does not belong to the low-carbon consumer goods set owned by the consumer merchant, the low-carbon consumer goods consumed by the user at the consumer merchant can be determined to be counterfeit.
Optionally, in order to stimulate the low-carbon consumption behavior of the user to encourage more users to participate in the low-carbon consumption behavior, after determining that the consumer goods are low-carbon consumer goods consumed by the consumer merchant selected by the user, in one or more embodiments of the present specification, first, the carbon emission reduction data of the user may be determined based on the feature information of the low-carbon consumer goods consumed by the user at the consumer merchant; the user is then rewarded based on the user's carbon emissions reduction data and the user's consumable items.
Optionally, in order to encourage the consumption merchants to provide more convenience for the low-carbon consumption behaviors of the users, and further enable more merchants to participate in the team popularizing the low-carbon consumption behaviors, after determining that the consumption articles are the low-carbon consumption articles consumed by the consumption merchants selected by the users, one or more embodiments of the present specification may first determine the carbon emission reduction data of the corresponding consumption merchants based on the characteristic information of the low-carbon consumption articles consumed by the users at the consumption merchants; the consumer merchant is then rewarded based on the carbon emissions reduction data of the consumer merchant and the consumer goods of the user.
It should be noted that, the above calculation method for determining the carbon emission reduction data of the user or the corresponding carbon emission reduction data of the consumer merchant based on the low-carbon consumption characteristic information of the user is the prior art, and specifically, reference may be made to a calculation method for carbon emission reduction data provided by an authority such as the beijing environmental exchange, and details of one or more embodiments of the present specification will not be repeated here.
Optionally, in order to further optimize the low-carbon consumer item matching model, after determining that the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant, one or more embodiments of the present specification may further optimize the low-carbon consumer item matching model based on the image information of the consumer item and the type of the consumer item.
The method for identifying low carbon consumption provided by the present specification is described in detail below with schematic implementation flows in two specific application scenarios in fig. 2 and fig. 3.
As shown in fig. 2, an implementation flow diagram of the low-carbon consumption identification method provided for an embodiment of this specification applied to an actual scene is shown, where the scene shown in fig. 2 is a scene of performing consumption in a merchant under a subscriber line, taking a catering merchant as an example, and assuming that an identification entrance of low-carbon consumption is a "green spy" functional product, the functional product may be an individual application installed in a terminal device, or may be a function in a payment application. As shown in fig. 2, the method comprises the following main steps:
step 21, responding to the operation that the user starts the 'green detective' function, and acquiring the current LBS address information of the user;
it should be noted that the payment and the scanning of the user are not in sequence, that is, the environmental protection tableware can be scanned before the payment, and the environmental protection tableware can also be scanned after the payment operation.
based on the image information of the environment-friendly tableware scanned by the user and obtained in step 23, based on the low-carbon consumer item matching model and the low-carbon consumer item set owned by the consumer merchant, identifying whether the environment-friendly tableware scanned by the user is environment-friendly tableware of the corresponding consumer merchant, whether the information of the consumer merchant paid by the user is consistent with the information of the catering merchant selected by the user, and determining whether the payment time of the user is within the same time period as the selection time of the catering merchant selected by the user (for example, the difference between the two times is not more than two hours);
if the environment-friendly tableware scanned by the user is identified to be the environment-friendly tableware of the corresponding consumption merchant, the information of the consumption merchant paid by the user is consistent with the information of the catering merchant selected by the user, and whether the payment time of the user is within the same time period as the selection time of the catering merchant selected by the user, the consumption behavior of the user can be identified to be low-carbon consumption behavior.
for example, the user may be issued with coupons of some corresponding consuming merchants, or with reward money, and for a consuming merchant, the reward policy such as ranking priority of the consuming merchant in the commodity list may be improved, so as to encourage more users or merchants to participate in the low-carbon consumption behavior.
As shown in fig. 3, an implementation flow diagram of the recognition method of low-carbon consumption behavior provided for an embodiment of this specification applied to another actual scenario is shown, the scenario shown in fig. 3 is a scenario in which consumption and payment are completed in a merchant under a subscriber line, and a catering merchant is also taken as an example, and it is assumed that a recognition entrance of the low-carbon consumption behavior is a "green spy" functional product, and the functional product may be an individual application installed in a terminal device or a function in a payment application. As shown in fig. 3, the method comprises the following main steps:
based on the image information of the environment-friendly tableware scanned by the user and acquired in the step 32, based on the low-carbon consumer item matching model and the low-carbon consumer item set owned by the consumer merchant, identifying whether the environment-friendly tableware scanned by the user is the environment-friendly tableware of the corresponding consumer merchant, and determining whether the payment time of the user is within the same time period (for example, the difference between the two time periods is not more than two hours) as the selection time of the catering merchant selected by the user;
if the environment-friendly tableware scanned by the user is identified to be the environment-friendly tableware of the corresponding consumption merchant, and whether the payment time of the user is in the same time period with the selection time of the catering merchant selected by the user, the consumption behavior of the user can be identified to be low-carbon consumption behavior.
for example, the user may be issued with coupons of some corresponding consuming merchants, or with reward money, and for a consuming merchant, the reward policy such as ranking priority of the consuming merchant in the commodity list may be improved, so as to encourage more users or merchants to participate in the low-carbon consumption behavior.
And step 36, if the consumption behavior of the user in the selected consumption merchant is recognized as the low-carbon consumption behavior, optimizing the low-carbon consumption article matching model based on the low-carbon consumption characteristic information of the user and the information of the corresponding consumption merchant.
The method can firstly respond to a low-carbon consumer goods identification request of a user, acquire image information of a consumer goods scanned by the user, input the image information into a low-carbon consumer goods matching model, determine the type of the consumer goods, acquire the time for scanning the consumer goods and the information of a consumer merchant determined by the user, and then acquire payment information of the user, wherein the payment information comprises payment time and payment objects, and finally, whether the consumer goods is the low-carbon consumer goods consumed by the user at the consumer merchant can be effectively determined based on the type of the consumer goods, the time for scanning the consumer goods, the information of the consumer merchant determined by the user and the payment information, so that when the consumer goods is determined to be the low-carbon consumer goods consumed by the user at the consumer merchant, the user or the consumer merchant of the user can be rewarded, and more users and merchants are encouraged to participate in low-carbon consumption, the problem that the low-carbon consumption behaviors of the user cannot be effectively identified in the prior art is solved.
Fig. 4 is a schematic structural diagram of a low carbon consumption recognition device 400 provided in the present specification. Referring to fig. 4, in a software implementation, the low carbon consumption recognition apparatus 400 may include a first obtaining unit 401, a first determining unit 402, a second obtaining unit 403, a third obtaining unit 404, and a second determining unit 405, wherein:
a first obtaining unit 401, configured to obtain image information of a consumer item scanned by the user in response to a low-carbon consumer item identification request of the user;
a first determining unit 402, which inputs the image information into a low-carbon consumer goods matching model and determines the type of the consumer goods;
a second obtaining unit 403, obtaining the type of the consumer item, the time for scanning the consumer item, and the information of the consumer merchant determined by the user;
a third obtaining unit 404, configured to obtain payment information of the user, where the payment information includes payment time and a payment object;
a second determining unit 405, which determines whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
Alternatively, in one embodiment, the second determination unit 405,
if the type of the consumer goods is a low-carbon consumer goods, determining whether the consumer goods is the low-carbon consumer goods consumed by the user at the consumer merchant based on the time for scanning the consumer goods, the information of the consumer merchant and the payment information;
if the type of the consumer goods is a non-low-carbon consumer goods, determining that the consumer goods is not a low-carbon consumer goods consumed by the user at the consumer merchant.
Alternatively, in one embodiment, the second determination unit 405,
if the time for scanning the consumer goods and the payment time in the payment information are in the same preset time period, and the information of the consumer merchant is consistent with the payment object in the payment information, determining that the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant;
and if the time for scanning the consumer goods and the payment time in the payment information are not in the same preset time period, and/or the information of the consumer merchant is inconsistent with the payment object in the payment information, determining that the consumer goods are not the low-carbon consumer goods consumed by the user at the consumer merchant.
Alternatively, in one embodiment, the second obtaining unit 403,
responding to the low-carbon consumer goods identification request of the user, and acquiring longitude and latitude coordinate data address information of the user;
acquiring a list of merchant information within a preset range of latitude and longitude coordinate data address information from the user;
and responding to the merchant selection operation of the user, and acquiring the information of the merchant selected by the user when the user sends the identification request of the low-carbon consumption behavior.
Optionally, the apparatus further comprises:
a fourth obtaining unit 406, which obtains the type of the consumer goods of the consumer merchant within a predetermined time;
a third determining unit 407, configured to determine a set of low-carbon consumer items owned by the consumer merchant based on the type of consumer items of the consumer merchant within a predetermined time;
the fourth determining unit 408 determines whether the low-carbon consumer item consumed by the user at the consuming merchant is authentic based on the set of low-carbon consumer items owned by the consuming merchant and the type of the consumer item.
Alternatively, in one embodiment, the fourth determination unit 408,
if the type of the consumer goods belongs to the low-carbon consumer goods set owned by the consumer merchant, determining that the low-carbon consumer goods consumed by the user at the consumer merchant are true;
and if the type of the consumer goods does not belong to the low-carbon consumer goods set owned by the consumer merchant, determining that the low-carbon consumer goods consumed by the user at the consumer merchant are counterfeit.
Optionally, in an embodiment, the apparatus further includes:
a fifth determining unit 409, configured to determine carbon emission reduction data of the user based on feature information of the low-carbon consumer goods consumed by the user at the consumer merchant;
a first rewarding unit 410 rewarding the user based on the carbon emissions reduction data of the user and the consumable good.
Optionally, in an embodiment, the apparatus further includes:
a sixth determining unit 411, configured to determine carbon emission reduction data of a corresponding consumption merchant based on feature information of a low-carbon consumption article consumed by the user at the consumption merchant;
and a second rewarding unit 412 that rewards the consumer merchant based on the carbon emission reduction data of the consumer merchant and the characteristic information of the consumer goods.
Optionally, in an embodiment, the apparatus further includes:
the optimizing unit 413 optimizes the low-carbon consumer item matching model based on the image information of the consumer item and the type of the consumer item.
The low carbon consumption identification apparatus 400 can implement the method of the embodiment of the method shown in fig. 1 to 3, and specifically refer to the low carbon consumption identification method shown in the embodiment shown in fig. 1 to 3, which is not described again.
Fig. 5 is a schematic structural diagram of an electronic device provided in an embodiment of the present specification. Referring to fig. 5, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 5, but this does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program, and the low-carbon consumption recognition device is formed on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
responding to a low-carbon consumer goods identification request of the user, and acquiring image information of the consumer goods scanned by the user;
inputting the image information into a low-carbon consumer goods matching model, and determining the type of the consumer goods;
acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
obtaining payment information of the user, wherein the payment information comprises payment time and a payment object;
determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
The low carbon consumption recognition method disclosed in the embodiments of fig. 1 to 3 of the present specification may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in one or more embodiments of the present specification may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with one or more embodiments of the present disclosure may be embodied directly in hardware, in a software module executed by a hardware decoding processor, or in a combination of the hardware and software modules executed by a hardware decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further perform the low-carbon consumption recognition method shown in fig. 1 to 3, which is not described herein again.
Of course, besides the software implementation, the electronic device in this specification does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or logic devices.
In short, the above description is only a preferred embodiment of the present disclosure, and is not intended to limit the scope of the present disclosure. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of the present disclosure should be included in the scope of protection of one or more embodiments of the present disclosure.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Claims (12)
1. A low carbon consumption identification method comprises the following steps:
responding to a low-carbon consumer goods identification request of a user, and acquiring image information of consumer goods scanned by the user, wherein the consumer goods are goods consumed by the user at a consumer merchant;
inputting the image information into a low-carbon consumption article matching model, and determining the type of the consumption article, wherein the low-carbon consumption article matching model is obtained by training based on the characteristic information of the low-carbon consumption article in the historical time period and the type information of the corresponding low-carbon consumption article;
acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
the method comprises the steps of obtaining payment information of a user, wherein the payment information comprises payment time and a payment object, the payment time is used for determining whether the time of scanning consumer goods by the user and the payment time are in the same preset time period, and the payment object is used for determining whether a consumer merchant determined by the user is matched with the payment object;
determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
2. The method of claim 1, determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time at which the consumer item was scanned, the information of the consumer merchant determined by the user, and the payment information, comprising:
if the type of the consumer goods is a low-carbon consumer goods, determining whether the consumer goods is the low-carbon consumer goods consumed by the user at the consumer merchant based on the time for scanning the consumer goods, the information of the consumer merchant and the payment information;
if the type of the consumer goods is a non-low-carbon consumer goods, determining that the consumer goods is not a low-carbon consumer goods consumed by the user at the consumer merchant.
3. The method of claim 2, determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the time at which the consumer item was scanned, the information of the consumer merchant determined by the user, and the payment information, comprising:
if the time for scanning the consumer goods and the payment time in the payment information are in the same preset time period, and the information of the consumer merchant is consistent with the payment object in the payment information, determining that the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant;
and if the time for scanning the consumer goods and the payment time in the payment information are not in the same preset time period, and/or the information of the consumer merchant is inconsistent with the payment object in the payment information, determining that the consumer goods are not the low-carbon consumer goods consumed by the user at the consumer merchant.
4. A method as claimed in any one of claims 1 to 3, wherein obtaining information about the consumer merchant determined by the user comprises:
responding to the low-carbon consumer goods identification request of the user, and acquiring longitude and latitude coordinate data address information of the user;
acquiring a list of merchant information within a preset range of latitude and longitude coordinate data address information from the user;
and responding to the merchant selection operation of the user, and acquiring the information of the consumer merchant determined by the user.
5. The method of claim 3, after determining that the consumer item is a low-carbon consumer item that the user consumes at the consuming merchant, the method further comprising:
acquiring the type of the consumer goods of the consumer merchant in a preset time;
determining a low-carbon consumption article set owned by the consumption merchant based on the type of the consumption article of the consumption merchant in a preset time;
and determining whether the low-carbon consumer goods consumed by the user at the consumer merchant are true or not based on the low-carbon consumer goods set owned by the consumer merchant and the type of the consumer goods.
6. The method of claim 5, determining whether the low-carbon consumer item consumed by the user at the consuming merchant is authentic based on the set of low-carbon consumer items owned by the consuming merchant and the type of the consumer item, comprising:
if the type of the consumer goods belongs to the low-carbon consumer goods set owned by the consumer merchant, determining that the low-carbon consumer goods consumed by the user at the consumer merchant are true;
and if the type of the consumer goods does not belong to the low-carbon consumer goods set owned by the consumer merchant, determining that the low-carbon consumer goods consumed by the user at the consumer merchant are counterfeit.
7. The method of claim 3, after determining that the consumer item is a low-carbon consumer item that the user consumes at the consuming merchant, the method further comprising:
determining carbon emission reduction data of the user based on the characteristic information of the low-carbon consumption goods consumed by the user at the consumption merchant;
rewarding the user based on the user's carbon emissions reduction data and the consumer good.
8. The method of claim 3, after determining that the consumer item is a low-carbon consumer item that the user consumes at the consuming merchant, the method further comprising:
determining carbon emission reduction data of the corresponding consumption merchant based on the characteristic information of the low-carbon consumption goods consumed by the user at the consumption merchant;
rewarding the merchant based on the carbon emissions reduction data of the consumer merchant and the consumer item.
9. The method of claim 3, after determining that the consumer item is a low-carbon consumer item that the user consumes at the consuming merchant, the method further comprising:
optimizing the low-carbon consumer item matching model based on the image information of the consumer item and the type of the consumer item.
10. An identification apparatus for low carbon consumption, comprising:
the first acquisition unit is used for responding to a low-carbon consumer goods identification request of a user, and acquiring image information of consumer goods scanned by the user, wherein the consumer goods are goods consumed by the user at a consumer merchant;
the first determining unit is used for inputting the image information into a low-carbon consumption article matching model and determining the type of the consumption article, wherein the low-carbon consumption article matching model is obtained by training based on the characteristic information of the low-carbon consumption article in the historical time period and the type information of the corresponding low-carbon consumption article;
the second acquisition unit is used for acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
the third acquisition unit is used for acquiring payment information of the user, wherein the payment information comprises payment time and a payment object, the payment time is used for determining whether the time for scanning the consumer goods by the user and the payment time are in the same preset time period, and the payment object is used for determining whether a consumer merchant determined by the user is matched with the payment object;
and the second determination unit is used for determining whether the consumer goods are low-carbon consumer goods consumed by the user at the consumer merchant based on the type of the consumer goods, the time for scanning the consumer goods, the information of the consumer merchant determined by the user and the payment information.
11. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to:
responding to a low-carbon consumer goods identification request of a user, and acquiring image information of consumer goods scanned by the user, wherein the consumer goods are goods consumed by the user at a consumer merchant;
inputting the image information into a low-carbon consumption article matching model, and determining the type of the consumption article, wherein the low-carbon consumption article matching model is obtained by training based on the characteristic information of the low-carbon consumption article in the historical time period and the type information of the corresponding low-carbon consumption article;
acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
the method comprises the steps of obtaining payment information of a user, wherein the payment information comprises payment time and a payment object, the payment time is used for determining whether the time of scanning consumer goods by the user and the payment time are in the same preset time period, and the payment object is used for determining whether a consumer merchant determined by the user is matched with the payment object;
determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
12. A computer-readable storage medium storing one or more programs that, when executed by an electronic device including a plurality of application programs, cause the electronic device to:
responding to a low-carbon consumer goods identification request of a user, and acquiring image information of consumer goods scanned by the user, wherein the consumer goods are goods consumed by the user at a consumer merchant;
inputting the image information into a low-carbon consumption article matching model, and determining the type of the consumption article, wherein the low-carbon consumption article matching model is obtained by training based on the characteristic information of the low-carbon consumption article in the historical time period and the type information of the corresponding low-carbon consumption article;
acquiring the time for scanning the consumer goods and the information of the consumer merchant determined by the user;
the method comprises the steps of obtaining payment information of a user, wherein the payment information comprises payment time and a payment object, the payment time is used for determining whether the time of scanning consumer goods by the user and the payment time are in the same preset time period, and the payment object is used for determining whether a consumer merchant determined by the user is matched with the payment object;
determining whether the consumer item is a low-carbon consumer item consumed by the user at the consumer merchant based on the type of the consumer item, the time for scanning the consumer item, the information of the consumer merchant determined by the user, and the payment information.
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| CN202110377040.8A CN113516212B (en) | 2018-08-17 | 2018-08-17 | Low-carbon consumption identification method and device and electronic equipment |
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| CN202433967U (en) * | 2011-12-15 | 2012-09-12 | 北京互帮国际技术有限公司 | Device and system for paperless exchange memo |
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| US20090157510A1 (en) * | 2007-11-07 | 2009-06-18 | Ken Pridmore | Method of Tracking and Redeeming Consumer Carbon Emission Credits |
| KR100967229B1 (en) * | 2008-01-25 | 2010-07-05 | (주) 에코프론티어 | Point-Rewarding System with Carbon-Credit |
| JP5084806B2 (en) * | 2009-10-05 | 2012-11-28 | 中国電力株式会社 | Environmental load suppression system, environmental load suppression support device, and environmental load suppression method |
| BR112013003687A2 (en) * | 2010-08-18 | 2016-08-16 | James S Rhodes | carbon storage of biomass in the solid phase |
| KR20120137583A (en) * | 2011-05-12 | 2012-12-24 | (주)피케이티 | Point management system for carbon reduction |
| US20150127391A1 (en) * | 2013-11-06 | 2015-05-07 | Vita Travel Agent Corporation | Comprehensive carbon footprint determination and offset for multi-point, multi-modal, mixed activity travel |
| CN108229337B (en) * | 2017-12-14 | 2021-03-30 | 创新先进技术有限公司 | Data processing method, device and equipment |
| CN107993106B (en) * | 2017-12-14 | 2020-04-10 | 阿里巴巴集团控股有限公司 | Electronic invoice generation method and device |
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