Garbage can control method, device and electronic equipment applied to intelligent garbage can

Abstract

This disclosure presents embodiments of a trash can control method, apparatus, and electronic device applied to a smart trash can. One specific implementation of the method includes: recognizing human actions in a target image; controlling the opening of the trash disposal hatch of the smart trash can; in response to a first infrared sensor detecting the end of a trash disposal action, performing the following processing steps: controlling a spray device inside the smart trash can to spray disinfectant; in response to determining that the current trash weight is less than a preset trash weight threshold and the current trash volume is greater than or equal to a preset trash volume threshold, compressing the trash inside the smart trash can using a trash compression device installed inside the smart trash can; and in response to determining that the current trash weight is greater than or equal to the preset trash weight threshold, moving the smart trash can to a trash recycling area within the target area. This implementation achieves timely trash disposal and reduces the occurrence of environmental sanitation problems in the park.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the field of computer technology, and more specifically to a trash can control method, apparatus, and electronic device applied to a smart trash can. Background Technology

[0002] As cities continue to expand, the amount of waste generated by people in their daily lives and work is also increasing. This is especially true in large industrial parks (such as amusement parks and office parks), where high foot traffic leads to even greater demands for waste management. Currently, the common method for waste disposal is to set up trash cans and manually empty them regularly.

[0003] However, the inventors discovered that the following technical problems often arise when using the above method:

[0004] Manually cleaning trash cans, especially in large parks with high temperatures, can easily lead to untimely trash can emptying, which in turn allows germs to multiply and cause environmental sanitation problems in the park.

[0005] Furthermore, the following technical problems exist when users dispose of garbage into the trash cans:

[0006] Because garbage often produces odors during the accumulation process, common garbage cans often have compartments to mask the smell. This means that users often need to open the compartments by physical contact to dispose of the garbage, which may lead to the spread of diseases.

[0007] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0009] Some embodiments of this disclosure provide trash can control methods, devices, and electronic devices for use in smart trash cans to solve one or more of the technical problems mentioned in the background section above.

[0010] In a first aspect, some embodiments of this disclosure provide a trash can control method applied to a smart trash can. The method includes: performing human action recognition on a target image to generate human action information, wherein the target image is an image captured by a camera installed on the smart trash can, the image acquisition direction of the camera is consistent with the orientation of the trash can's disposal opening, and the smart trash can controls the camera to acquire the image via a first infrared sensor; in response to the human action information representing a trash disposal action, controlling the opening of the trash disposal opening door of the smart trash can, wherein the smart trash can is in a sealed state when the trash disposal opening door is closed; and in response to the first infrared sensor recognizing the end of the trash disposal action, executing... The following processing steps are performed: The garbage disposal hatch is closed; in response to confirming that the garbage disposal hatch is closed, the spray device inside the smart garbage bin is controlled to spray disinfectant; in response to confirming that the disinfectant spraying has ended, the current garbage volume indicator and current garbage weight inside the smart garbage bin are determined using a second infrared sensor and a pressure sensor; in response to confirming that the current garbage weight is less than a preset garbage weight threshold and the current garbage volume indicator is greater than or equal to the preset garbage volume threshold, the garbage inside the smart garbage bin is compressed using a garbage compression device installed inside the smart garbage bin; in response to confirming that the current garbage weight is greater than or equal to the preset garbage weight threshold, the smart garbage bin is moved to the garbage recycling area included in the target area.

[0011] Secondly, some embodiments of this disclosure provide a trash can control device for a smart trash can, the device comprising: a human motion recognition unit configured to perform human motion recognition on a target image to generate human motion information, wherein the target image is an image captured by a camera mounted on the smart trash can, the image acquisition direction of the camera being consistent with the orientation of the trash can's trash disposal opening, and the smart trash can controlling the camera to acquire images via a first infrared sensor; a control unit configured to control the opening of the trash disposal opening door of the smart trash can in response to the human motion information representing a trash disposal action, wherein the smart trash can is in a sealed state when the trash disposal opening door is closed; and an execution unit configured to respond to the first infrared sensor. Upon detecting the completion of the waste disposal action, the following processing steps are executed: the waste disposal hatch is closed; in response to confirming that the waste disposal hatch is closed, the spray device inside the smart trash can is controlled to spray disinfectant; in response to confirming that the disinfectant spraying has ended, the current waste volume indicator and current waste weight inside the smart trash can are determined using a second infrared sensor and a pressure sensor; in response to confirming that the current waste weight is less than a preset waste weight threshold and the current waste volume indicator is greater than or equal to the preset waste volume threshold, the waste inside the smart trash can is compressed using a waste compression device installed inside the smart trash can; in response to confirming that the current waste weight is greater than or equal to the preset waste weight threshold, the smart trash can is moved to the waste recycling area included in the target area.

[0012] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0013] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

[0014] The above-described embodiments of this disclosure have the following beneficial effects: The trash can control method applied to smart trash cans according to some embodiments of this disclosure inhibits the growth of germs and reduces the probability of environmental sanitation problems in the park. Specifically, the reason for the growth of germs and the resulting environmental sanitation problems in the park is that manual trash can cleaning, especially in large parks with high temperatures, easily leads to untimely trash can cleaning, which in turn leads to the growth of germs and causes environmental sanitation problems. Based on this, the trash can control method applied to smart trash cans according to some embodiments of this disclosure firstly performs human action recognition on the target image to generate human action information. The target image is an image captured by a camera installed on the smart trash can, and the image acquisition direction of the camera is consistent with the orientation of the trash can's disposal opening. The smart trash can controls the camera to acquire images through a first infrared sensor. Secondly, in response to the human action information representing the trash disposal action, the trash can's disposal opening door is controlled to open. The smart trash can is in a sealed state when the trash can's disposal opening door is closed. This achieves contactless trash disposal. Next, in response to the first infrared sensor detecting the end of the waste disposal action, the following processing steps are executed: First, the waste disposal hatch is closed. Second, in response to confirming that the waste disposal hatch is closed, the spray device inside the smart trash can is controlled to spray disinfectant. This disinfects and sterilizes the inside of the trash can to inhibit the growth of germs. Third, in response to confirming that the disinfectant spraying has ended, the current volume and weight of the waste inside the smart trash can are determined using the second infrared sensor and pressure sensor. Fourth, in response to confirming that the current waste weight is less than a preset waste weight threshold and the current waste volume is greater than or equal to the preset waste volume threshold, the waste is compressed using the waste compression device installed inside the smart trash can. In practice, when there is a situation where the waste volume is large but the waste weight is small, the trash can may not be able to store the waste efficiently. Therefore, when the current weight of the garbage is less than a preset garbage weight threshold, and the current garbage volume indicator is greater than or equal to the preset garbage volume threshold, this disclosure uses a garbage compression device to compress the garbage in the smart garbage bin, thereby improving the garbage storage capacity of the garbage bin. Fifth step: In response to determining that the current garbage weight is greater than or equal to the preset garbage weight threshold, the smart garbage bin is moved to the garbage recycling area included in the target area. In practice, due to the size of the garbage bin, the upper limit of the garbage storage capacity is limited. Therefore, when the current garbage weight is greater than or equal to the preset garbage weight threshold, this disclosure will automatically move the smart garbage bin to the garbage recycling area, thereby achieving timely garbage disposal and reducing the occurrence of environmental sanitation problems in the park. Attached Figure Description

[0015] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0016] Figure 1 This is a flowchart of some embodiments of a trash can control method applied to a smart trash can according to the present disclosure;

[0017] Figure 2 These are schematic diagrams illustrating the structure of some embodiments of a trash can control device applied to a smart trash can according to the present disclosure;

[0018] Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0019] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0020] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0021] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0022] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0023] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0024] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0025] refer to Figure 1 The diagram illustrates a flow 100 of some embodiments of a trash can control method applied to a smart trash can according to the present disclosure. The trash can control method applied to a smart trash can includes the following steps:

[0026] Step 101: Perform human action recognition on the target image to generate human action information. In some embodiments, the execution subject (e.g., a computing device) of the trash can control method applied to a smart trash can can perform human action recognition on the target image to generate human action information. The target image is an image captured by a camera mounted on the smart trash can. The image acquisition direction of the camera is consistent with the orientation of the trash can's disposal opening. In practice, the camera is used to capture images of the area facing the trash can's disposal opening. The smart trash can controls the camera to capture images via a first infrared sensor. In practice, the first infrared sensor is located outside the smart trash can. The first infrared sensor is aligned with the image acquisition direction of the camera. Specifically, when the first infrared sensor detects the presence of a person in the area facing the trash can's disposal opening, it controls the camera to turn on for image acquisition. Controlling the camera's activation and image acquisition via the first infrared sensor avoids unnecessary computational resource waste caused by real-time camera acquisition. Human action information characterizes the actions of the person contained in the target image. For example, human action information may include any one of the following: trash disposal actions and non-trash disposal actions.

[0027] As an example, the aforementioned executing entity can use the YOLO (You Only Look Once) model and a binary classifier to perform human action recognition on the target image to generate human action information. Specifically, the binary classifier is used to generate human action information representing garbage disposal actions, and to generate human action information representing non-garbage disposal actions.

[0028] It should be noted that the aforementioned computing devices can be either hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or terminal device. When the computing device is software, it can be installed within the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here. It should be understood that the number of computing devices can be arbitrary, depending on the implementation requirements.

[0029] In some optional implementations of certain embodiments, the execution entity performs personnel action recognition on the target image to generate personnel action information, which may include the following steps:

[0030] The first step is to perform multi-scale cropping on the target image to generate a cropped image sequence.

[0031] In this sequence of cropped images, the cropped images are arranged in descending order of image scale. In practice, the aforementioned execution entity can perform multi-scale cropping of the target image using K cropping boxes of different image scales, each with a fixed step size. Here, K ≥ 2.

[0032] As an example, the cropped image sequence may include: cropped image A, cropped image B, and cropped image C. The image size of cropped image A is greater than the image size of cropped image B, which in turn is greater than the image size of cropped image C.

[0033] The second step involves performing the following image processing steps based on the cropped image sequence:

[0034] The first sub-step is to determine the cropped image at the beginning of the cropped image sequence as the target cropped image.

[0035] The first position of the sequence can be the position of the cropped image with the largest image size in the cropped image sequence.

[0036] As an example, the cropped image sequence may include cropped image A, cropped image B, and cropped image C. Therefore, the aforementioned execution entity may use cropped image A as the target cropped image.

[0037] The second sub-step involves extracting image features from the cropped target image using the image feature extraction layer included in the pre-trained hand judgment model, in order to generate the cropped target image features.

[0038] The image feature extraction layer mentioned above includes three sequentially connected convolutional layers.

[0039] The third sub-step involves inputting the cropped image features of the target into the hand classifier included in the aforementioned hand judgment model to generate classification results.

[0040] The hand classifier is a binary classifier. The hand classifier classifies the image into two categories: hand and non-hand. The hand category indicates that the cropped image contains a hand image. The non-hand category indicates that the cropped image does not contain a hand image.

[0041] The fourth sub-step, in response to determining that the classification result is a hand category, generates the aforementioned person motion information based on the cropped image of the target and the pre-trained person motion information, and ends the aforementioned image processing steps.

[0042] The personnel motion information generation model is used to identify the actions of people within an image. For example, the personnel motion information generation model could be a Fast R-CNN (Faster Region-based Convolutional Neural Network) model.

[0043] Optionally, the personnel action information generation model may include: a hand location area recognition model, a waste location area recognition model, a hand action classification layer, and a waste type classification layer. The hand location area recognition model and the waste location area recognition model are configured in parallel and share model parameters. The personnel action information generation model and the hand judgment model share an image feature extraction layer. The waste type classification layer is a binary classifier. The classification categories of the waste type classification layer include: waste category and non-waste category. Both the hand location area recognition model and the waste location area recognition model use VGG16 as the backbone network. Both the hand location area recognition model and the waste location area recognition model contain M convolutional blocks. 3 ≤ M ≤ 5. Each convolutional block includes: 3 sequentially connected convolutional layers and 1 max-pooling layer. The hand action classification layer is connected after the hand location area recognition model. The waste type classification layer is connected after the waste location area recognition model. The aforementioned human motion information generation model shares the same image feature extraction layer as the aforementioned hand identification model. That is, the inputs to both the hand location recognition model and the trash location recognition model are the outputs of the image feature extraction layer. Specifically, the target cropped image features generated by the image feature extraction layer can be cached in a cache pool to serve as the inputs for subsequent hand location recognition and trash location recognition models, thereby reducing redundant data computation.

[0044] Optionally, the aforementioned execution entity generates the aforementioned personnel action information based on the target cropped image and pre-trained personnel action information using a model, which may include the following steps:

[0045] Step 1: Input the target cropped image features corresponding to the above target cropped image into the above hand area recognition model and the above garbage area recognition model in parallel to generate the hand area and the garbage area.

[0046] Step 2: Input the local image features corresponding to the area where the hand is located in the image features after the target is cropped into the hand action classification layer to generate a hand action category.

[0047] Step 3: Input the local image features corresponding to the area where the garbage is located in the image features after the target is cropped into the garbage type classification layer to generate garbage categories.

[0048] Step 4: In response to determining that the above hand action category is the grasping category and the above garbage category is the garbage category, determine the area intersection and union ratio between the garbage area and the above hand area.

[0049] Wherein, the area comparison intersection-union ratio = (intersection area of ​​the area where the garbage is located and the aforementioned hand area) / (union area of ​​the area where the garbage is located and the aforementioned hand area).

[0050] Step 5: In response to the above-mentioned area intersection ratio being greater than the preset area intersection ratio, and the area center of the above-mentioned garbage area being located being located within the above-mentioned hand area, generate the above-mentioned personnel action information representing the garbage disposal action.

[0051] Third, in response to the determination that the classification result is not a hand category, the cropped image sequence after removing the target is used as the cropped image sequence, and the above image processing steps are performed again.

[0052] The above-described optional implementations and contents in some embodiments, as an inventive point of this disclosure, solve the technical problem mentioned in the background art: "Because garbage often produces odors during accumulation, common garbage cans often have doors for odor masking, which often requires users to open the doors by physical contact to dispose of garbage, potentially leading to the spread of diseases." Based on this, firstly, this disclosure automatically controls the opening of the garbage disposal compartment door through human motion recognition. During the recognition process, considering that conventional recognition methods relying solely on infrared sensors may result in misidentification, leading to the accidental opening of the garbage disposal compartment door. For example, when a person passes in front of the smart garbage can, it may trigger the infrared sensor, causing the garbage disposal compartment door to open accidentally. Furthermore, a purely visual method that analyzes camera images in real time would consume excessive computing resources, resulting in wasted computing resources. Therefore, this disclosure uses a first infrared sensor as the start / stop condition for camera image acquisition and human motion recognition. This reduces the risk of false recognition relying solely on infrared sensors and the waste of computational resources caused by relying solely on vision and real-time analysis of camera footage. Secondly, in practice, people often use their hands to dispose of garbage, resulting in a small proportion of the hand in the target image. In other words, the effective features in the target image are only around the hand. Conventional methods of directly detecting the entire target image involve large amounts of data processing and high computational resource requirements. Therefore, this disclosure uses multi-scale cropping to obtain multiple images of different sizes. By reversing the image size, a hand classifier determines whether the cropped image contains the hand. The resulting cropped image is smaller than the target image, thus reducing the amount of data processing. Furthermore, to further reduce the probability of false recognition during garbage disposal, this disclosure addresses hand action recognition and garbage identification by setting up a hand area recognition model, a garbage area recognition model, a hand action classification layer, and a garbage type classification layer to achieve the identification of garbage categories and hand action categories. This method greatly reduces the probability of misidentification, achieves contactless waste disposal, and reduces the risk of disease transmission.

[0053] Step 102: In response to the garbage disposal action represented by the personnel's motion information, control the opening of the garbage disposal compartment door of the smart garbage bin.

[0054] In some embodiments, in response to personnel motion information representing waste disposal actions, the aforementioned executing entity can control the opening of the waste disposal compartment door included in the smart trash can. The smart trash can is in a sealed state when the waste disposal compartment door is closed. In practice, a sealing ring is provided at the contact point between the waste disposal compartment door and the smart trash can to ensure that the smart trash can is in a sealed state when the waste disposal compartment door is closed. Specifically, the aforementioned executing entity can drive a hydraulic rod connected to the waste disposal compartment door to push the waste disposal compartment door open.

[0055] Step 103: In response to the first infrared sensor detecting the end of the waste disposal action, the following processing steps are executed:

[0056] Step 1031: Close the garbage disposal hatch.

[0057] In some embodiments, the aforementioned actuator can close the garbage disposal hatch door. In practice, when the first infrared sensor does not detect the presence of personnel in the area facing the garbage disposal hatch, the aforementioned actuator can drive the hydraulic rod connected to the garbage disposal hatch door to control the garbage disposal hatch door to close.

[0058] Step 1032: In response to determining that the garbage disposal hatch is closed, control the spray device inside the smart garbage bin to spray disinfectant.

[0059] In some embodiments, in response to determining that the garbage disposal hatch is closed, a spray device inside the smart garbage bin is controlled to spray disinfectant. The spray device is located inside the smart garbage bin and is directed towards the garbage inside. In practice, the spray device may include: a spray nozzle, a gas tank, and a disinfectant storage tank. The spray nozzle is connected to the disinfectant storage tank. The gas tank and the disinfectant storage tank are connected. The gas tank stores high-pressure gas. The disinfectant storage tank stores disinfectant. Due to gravity, when the spray nozzle is open, the disinfectant in the disinfectant storage tank is sprayed onto the garbage inside the smart garbage bin. To ensure more even spraying, high-pressure gas can be released through the gas tank during the spraying process to promote uniform disinfectant spraying.

[0060] Step 1033: In response to determining that the disinfectant spraying has ended, the current volume and weight of the trash in the smart trash can are determined by the second infrared sensor and the pressure sensor.

[0061] In some embodiments, in response to determining that the disinfectant spraying has ended, the aforementioned executing entity can determine the current volume and weight of the waste inside the smart trash can using a second infrared sensor and a pressure sensor. The second infrared sensor is directed towards the waste in the smart trash can. The pressure sensor is used to determine changes in the weight of the waste inside the smart trash can.

[0062] As an example, firstly, when the signal value of the infrared echo signal corresponding to the second infrared sensor exceeds a preset signal value, it indicates that the volume of trash in the smart trash can is greater than the preset trash volume. The aforementioned execution entity can determine the identifier indicating that the trash volume is greater than the preset trash volume as the current trash volume identifier. Secondly, when the signal value of the infrared echo signal corresponding to the second infrared sensor is less than the preset signal value, it indicates that the volume of trash in the smart trash can is less than or equal to the preset trash volume. The aforementioned execution entity can determine the identifier indicating that the trash volume is less than or equal to the preset trash volume as the current trash volume identifier. Next, the aforementioned execution entity can determine the current trash weight based on the pressure readings of the pressure sensor before and after trash disposal.

[0063] Optionally, the smart trash can includes a detachable trash can bin. The detachable trash can bin is disposed inside the smart trash can. A spray device faces the opening of the detachable trash can bin. The second infrared sensor is disposed inside the smart trash can bin. The second infrared sensor faces the opening of the detachable trash can bin. Specifically, the second infrared sensor is angled towards the opening of the detachable trash can bin. The second infrared sensor includes an infrared transmitter, an infrared receiver, and a Fresnel lens. The infrared transmitter emits infrared signals. The infrared receiver receives infrared echo signals. The Fresnel lens refracts the infrared signals emitted by the infrared transmitter onto the plane containing the opening of the detachable trash can bin.

[0064] In some optional implementations of certain embodiments, the execution entity determines the current volume and weight of the trash in the smart trash can using a second infrared sensor and a pressure sensor, which may include the following steps:

[0065] The first step is to control the infrared transmitter to emit infrared signals.

[0066] The second step is to receive the infrared echo signal corresponding to the infrared signal through the infrared receiver.

[0067] The third step is to determine, based on the infrared echo signal, whether there are any obstructions on the plane where the opening of the detachable trash can is located.

[0068] In practice, the aforementioned implementing entities can determine whether there are any obstructions on the plane where the opening of the detachable trash can is located based on the signal energy value corresponding to the infrared echo signal.

[0069] Fourth step: In response to the presence of an obstruction, the first waste volume identifier is determined to be the current waste volume identifier mentioned above.

[0070] The first garbage indicator indicates that the volume of garbage in the smart garbage bin is greater than the preset garbage volume.

[0071] Fifth step: In response to the absence of obstructions, the second waste volume identifier is determined to be the aforementioned current waste volume identifier.

[0072] The second waste label indicates that the volume of waste in the smart waste bin is less than or equal to the preset waste volume.

[0073] The sixth step is to determine the current pressure value and the no-load pressure value using the aforementioned pressure sensor.

[0074] The aforementioned empty pressure value represents the pressure value of the detachable waste bin when it is empty. In practice, the actuator can map the voltage signal from the pressure sensor when the detachable waste bin is empty to the empty pressure value. Alternatively, the actuator can map the voltage signal from the pressure sensor at the moment the first infrared sensor detects the end of the waste disposal action to the current pressure value.

[0075] Step 7: Determine the current weight of the waste based on the current pressure value and the no-load pressure value.

[0076] In practice, the aforementioned implementing entity can determine the current weight of the waste using the formula F=Mg, based on the current pressure value and the empty pressure value. Here, F represents pressure, M represents weight, and g represents gravitational acceleration.

[0077] Step 1034: In response to determining that the current garbage weight is less than the preset garbage weight threshold and the current garbage volume indicator is greater than or equal to the preset garbage volume threshold, the garbage in the smart garbage bin is compressed by the garbage compression device installed in the smart garbage bin.

[0078] In some embodiments, in response to determining that the current waste weight is less than a preset waste weight threshold and the current waste volume is greater than or equal to a preset waste volume threshold, the aforementioned executing entity can compress the waste inside the smart trash can using a waste compression device installed inside the smart trash can. The waste compression device is perpendicular to the opening of the detachable trash can and is used to compress the waste in the detachable trash can. In practice, the waste compression device may include a telescopic arm and a compression surface. The telescopic arm is connected to the compression surface. The aforementioned executing entity can drive the telescopic arm to extend and retract, thereby driving the compression surface to compress the waste in the detachable trash can.

[0079] Optionally, before moving the smart trash can to the waste recycling area included in the target area, the method further includes:

[0080] The waste is packaged using the waste sealing device inside the aforementioned smart waste bin. In practice, the waste sealing device is flush with the opening of the detachable waste bin, and the waste bag used to hold the waste in the detachable waste bin is sealed by heat fusion.

[0081] Step 1035: In response to determining that the current waste weight is greater than or equal to a preset waste weight threshold, the smart trash can is moved to the waste recycling area included in the target area.

[0082] In some embodiments, in response to determining that the current weight of the waste is greater than or equal to a preset waste weight threshold, the aforementioned implementing entity may move the smart trash can to a waste recycling area included in the target area. The waste recycling area is a recycling area used for centralized storage of waste. For example, the waste recycling area may be a waste transfer station. In practice, the aforementioned implementing entity may notify a waste collection truck to retrieve the smart trash can to the waste recycling area included in the target area.

[0083] In some optional implementations of certain embodiments, the process of moving the smart trash can to the waste recycling area included in the target area may include the following steps:

[0084] The first step is to determine if the target trash can delivery vehicle exists.

[0085] The target trash can transport vehicle is a self-propelled trash can transport vehicle that is in an idle state. In practice, for example, when the placement location of the smart trash can is fixed, the self-propelled trash can transport vehicle can be an AGV (Automated Guided Vehicle), that is, a fixed transportation route is set up, and the smart trash can is transported to a fixed point by the AGV. Alternatively, when the placement location of the smart trash can is not fixed, and if it is necessary to change the location of the smart trash can according to the flow of people, the self-propelled trash can transport vehicle can be an automated transport vehicle equipped with LiDAR, that is, using LiDAR for real-time road analysis and planning to transport the non-fixed-point smart trash can to the connected recycling area. Specifically, the aforementioned implementing entity can determine whether a target trash can transport vehicle exists by checking the idle status of the self-propelled trash can transport vehicle.

[0086] The second step is to respond to the existence of trash cans and plan recycling routes.

[0087] The trash can recycling route refers to the route taken by the transport vehicle from the location of the target trash can to the location of the smart trash can. In practice, the implementing entity can use an electronic map as a regional constraint and an ant colony algorithm to plan the trash can recycling route.

[0088] The third step involves using the target trash can transport vehicle to carry the target detachable trash can along the trash can recycling route to the location of the smart trash can.

[0089] The aforementioned target detachable trash cans are detachable trash cans in an empty state. In practice, since the purpose of the target trash can transport vehicle is to move the detachable trash cans, which are full of trash, from the smart trash can to the trash recycling area, the smart trash can will no longer contain detachable trash cans during the return trip. To ensure the normal use of the smart trash can and to save the time and transportation resources consumed by the target trash can transport vehicle to reload the target detachable trash cans, the target trash can transport vehicle can carry the target detachable trash cans when heading to the location of the aforementioned smart trash cans.

[0090] The fourth step involves using the aforementioned target trash can transport vehicle to replace the aforementioned target detachable trash can with the detachable trash can included in the aforementioned smart trash can.

[0091] In practice, smart trash cans may also include a detachable trash can replacement compartment. The detachable trash can replacement compartment is located below the trash delivery compartment. A sealing ring is provided at the interface between the detachable trash can replacement compartment and the smart trash can, ensuring the smart trash can is sealed when the detachable trash can replacement compartment is closed. The detachable trash can replacement compartment is driven by a hydraulic rod. When the detachable trash can replacement compartment is opened, the detachable trash can inside the smart trash can can be replaced. Specifically, after the detachable trash can replacement compartment is opened, the target trash can transport vehicle can remove the detachable trash can from the smart trash can and place the target detachable trash can inside the smart trash can. Upon completion of placement, the detachable trash can replacement compartment is closed by controlling the telescopic rod.

[0092] The above-described embodiments of this disclosure have the following beneficial effects: The trash can control method applied to smart trash cans according to some embodiments of this disclosure inhibits the growth of germs and reduces the probability of environmental sanitation problems in the park. Specifically, the reason for the growth of germs and the resulting environmental sanitation problems in the park is that manual trash can cleaning, especially in large parks with high temperatures, easily leads to untimely trash can cleaning, which in turn leads to the growth of germs and causes environmental sanitation problems. Based on this, the trash can control method applied to smart trash cans according to some embodiments of this disclosure firstly performs human action recognition on the target image to generate human action information. The target image is an image captured by a camera installed on the smart trash can, and the image acquisition direction of the camera is consistent with the orientation of the trash can's disposal opening. The smart trash can controls the camera to acquire images through a first infrared sensor. Secondly, in response to the human action information representing the trash disposal action, the trash can's disposal opening door is controlled to open. The smart trash can is in a sealed state when the trash can's disposal opening door is closed. This achieves contactless trash disposal. Next, in response to the first infrared sensor detecting the end of the waste disposal action, the following processing steps are executed: First, the waste disposal hatch is closed. Second, in response to confirming that the waste disposal hatch is closed, the spray device inside the smart trash can is controlled to spray disinfectant. This disinfects and sterilizes the inside of the trash can to inhibit the growth of germs. Third, in response to confirming that the disinfectant spraying has ended, the current volume and weight of the waste inside the smart trash can are determined using the second infrared sensor and pressure sensor. Fourth, in response to confirming that the current waste weight is less than a preset waste weight threshold and the current waste volume is greater than or equal to the preset waste volume threshold, the waste is compressed using the waste compression device installed inside the smart trash can. In practice, when there is a situation where the waste volume is large but the waste weight is small, the trash can may not be able to store the waste efficiently. Therefore, when the current weight of the garbage is less than a preset garbage weight threshold, and the current garbage volume indicator is greater than or equal to the preset garbage volume threshold, this disclosure uses a garbage compression device to compress the garbage in the smart garbage bin, thereby improving the garbage storage capacity of the garbage bin. Fifth step: In response to determining that the current garbage weight is greater than or equal to the preset garbage weight threshold, the smart garbage bin is moved to the garbage recycling area included in the target area. In practice, due to the size of the garbage bin, the upper limit of the garbage storage capacity is limited. Therefore, when the current garbage weight is greater than or equal to the preset garbage weight threshold, this disclosure will automatically move the smart garbage bin to the garbage recycling area, thereby achieving timely garbage disposal and reducing the occurrence of environmental sanitation problems in the park.

[0093] Further reference Figure 2 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a trash can control device applied to a smart trash can, these device embodiments being similar to... Figure 1 Corresponding to the method embodiments shown, the trash can control device applied to smart trash cans can be specifically applied to various electronic devices.

[0094] like Figure 2 As shown, a trash can control device 200 for a smart trash can in some embodiments includes: a human motion recognition unit 201, a control unit 202, and an execution unit 203. The human motion recognition unit 201 is configured to perform human motion recognition on a target image to generate human motion information. The target image is an image captured by a camera mounted on the smart trash can, the image acquisition direction of the camera being aligned with the orientation of the trash can's disposal opening. The smart trash can controls the camera to acquire images via a first infrared sensor. The control unit 202 is configured to control the opening of the trash disposal opening door of the smart trash can in response to the human motion information representing a trash disposal action. The smart trash can is in a sealed state when the trash disposal opening door is closed. The execution unit 203 is configured to execute a function in response to the first infrared sensor recognizing the end of the trash disposal action. The following processing steps are performed: The garbage disposal hatch is closed; in response to confirming that the garbage disposal hatch is closed, the spray device inside the smart garbage bin is controlled to spray disinfectant; in response to confirming that the disinfectant spraying has ended, the current garbage volume indicator and current garbage weight inside the smart garbage bin are determined using a second infrared sensor and a pressure sensor; in response to confirming that the current garbage weight is less than a preset garbage weight threshold and the current garbage volume indicator is greater than or equal to the preset garbage volume threshold, the garbage inside the smart garbage bin is compressed using a garbage compression device installed inside the smart garbage bin; in response to confirming that the current garbage weight is greater than or equal to the preset garbage weight threshold, the smart garbage bin is moved to the garbage recycling area included in the target area.

[0095] It is understood that the units described in the trash can control device 200 applied to smart trash cans are similar to those in the reference device. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the trash can control device 200 and the units contained therein applied to the smart trash can, and will not be repeated here.

[0096] The following is for reference. Figure 3 It shows a schematic diagram of the structure of an electronic device (e.g., a computing device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0097] like Figure 3 As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory 302 or a program loaded from a storage device 308 into a random access memory 303. The random access memory 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, the read-only memory 302, and the random access memory 303 are interconnected via a bus 304. An input / output interface 305 is also connected to the bus 304.

[0098] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.

[0099] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 309, or installed from a storage device 308, or installed from a read-only memory 302. When the computer program is executed by the processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.

[0100] It should be noted that, in some embodiments of this disclosure, the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0101] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed networks.

[0102] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: perform human action recognition on a target image to generate human action information, wherein the target image is an image captured by a camera mounted on the smart trash can, the image acquisition direction of the camera being aligned with the orientation of the trash can's disposal opening, and the smart trash can controlling the camera to acquire the image via a first infrared sensor; in response to the human action information representing a trash disposal action, controlling the opening of the trash disposal opening door of the smart trash can, wherein the smart trash can is in a sealed state when the trash disposal opening door is closed; and in response to the first infrared sensor recognizing the end of the trash disposal action... The following processing steps are performed: the garbage disposal hatch is closed; in response to determining that the garbage disposal hatch is closed, the spray device inside the smart garbage bin is controlled to spray disinfectant; in response to determining that the disinfectant spraying has ended, the current garbage volume indicator and current garbage weight inside the smart garbage bin are determined by the second infrared sensor and the pressure sensor; in response to determining that the current garbage weight is less than a preset garbage weight threshold and the current garbage volume indicator is greater than or equal to the preset garbage volume threshold, the garbage inside the smart garbage bin is compressed by the garbage compression device installed inside the smart garbage bin; in response to determining that the current garbage weight is greater than or equal to the preset garbage weight threshold, the smart garbage bin is moved to the garbage recycling area included in the target area.

[0103] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0104] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0105] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including a human motion recognition unit, a control unit, and an execution unit. The names of these units do not necessarily limit the specific unit itself; for example, a control unit may also be described as "a unit that, in response to the aforementioned human motion information representing a garbage disposal action, controls the opening of the garbage disposal hatch of the smart garbage bin, wherein the smart garbage bin is in a sealed state when the garbage disposal hatch is closed."

[0106] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0107] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A trash can control method applied to a smart trash can, comprising: Human action recognition is performed on the target image to generate human action information. The target image is an image captured by a camera installed on a smart trash can. The image acquisition direction of the camera is consistent with the direction of the trash can's trash disposal opening. The smart trash can controls the camera to acquire images through a first infrared sensor. The human action information includes any one of the following: trash disposal actions and non-trash disposal actions. In response to the personnel action information representing the garbage disposal action, the garbage disposal hatch of the smart garbage bin is controlled to open, wherein the smart garbage bin is in a sealed state when the garbage disposal hatch is closed; In response to the first infrared sensor detecting the end of the waste disposal action, the following processing steps are executed: Close the garbage disposal hatch door; In response to determining that the garbage disposal hatch is closed, the spray device inside the smart garbage bin is controlled to spray disinfectant. In response to the determination that the disinfectant spraying has ended, the current volume and weight of the trash in the smart trash can are determined by the second infrared sensor and the pressure sensor. In response to determining that the current weight of the garbage is less than a preset garbage weight threshold and the current garbage volume indicator is greater than or equal to a preset garbage volume threshold, the garbage in the smart garbage bin is compressed by the garbage compression device installed in the smart garbage bin. In response to determining that the current weight of the waste is greater than or equal to the preset waste weight threshold, the smart trash can is moved to the waste recycling area included in the target area; The step of performing human action recognition on the target image to generate human action information includes: The target image is cropped at multiple scales to generate a cropped image sequence, wherein the cropped images in the cropped image sequence are arranged in descending order of image scale; Based on the cropped image sequence, perform the following image processing steps: The cropped image at the beginning of the cropped image sequence is identified as the target cropped image. The image feature extraction layer of the pre-trained hand judgment model is used to extract image features from the cropped image of the target to generate the cropped image features. The image feature extraction layer includes three serially connected convolutional layers. The features of the cropped image are input into the hand classifier included in the hand judgment model to generate a classification result. The hand classifier is a binary classifier, and the classification categories of the hand classifier include: hand category and non-hand category. The hand category indicates that the cropped image contains a hand image, and the non-hand category indicates that the cropped image does not contain a hand image. In response to determining that the classification result is a hand category, a model is generated based on the cropped image of the target and pre-trained human motion information to generate the human motion information, and the image processing step is terminated. In response to determining that the classification result is not a hand category, the cropped image sequence after removing the target cropped image is used as the cropped image sequence, and the image processing steps are executed again.

2. The method of claim 1, wherein, The smart trash can includes: a detachable trash can housing inside the smart trash can; a second infrared sensor housing inside the smart trash can, facing the opening of the detachable trash can; and the second infrared sensor including: an infrared transmitter and an infrared receiver; and The process of determining the current volume and weight of the trash in the smart trash can using a second infrared sensor and a pressure sensor includes: Control the infrared transmitter to emit infrared signals; The infrared receiver receives the infrared echo signal corresponding to the infrared signal. Based on the infrared echo signal, determine whether there is an obstruction on the plane where the opening of the detachable trash can is located; In response to the presence of an obstruction, the first waste volume identifier is determined as the current waste volume identifier, wherein the first waste volume identifier indicates that the waste volume in the smart trash can is greater than a preset waste volume; In response to the absence of obstructions, the second waste volume identifier is determined as the current waste volume identifier, wherein the second waste volume identifier indicates that the waste volume in the smart trash can is less than or equal to a preset waste volume; The pressure sensor is used to determine the current pressure value and the empty pressure value, wherein the empty pressure value represents the pressure value when the separable trash can is in an empty state; The current weight of the waste is determined based on the current pressure value and the empty pressure value.

3. The method according to claim 2, wherein, The personnel action information generation model includes: a hand location area recognition model, a waste location area recognition model, a hand action classification layer, and a waste type classification layer. The hand location area recognition model and the waste location area recognition model are set in parallel and share model parameters. The personnel action information generation model and the hand judgment model share an image feature extraction layer. The waste type classification layer is a binary classifier, and the classification categories of the waste type classification layer include: waste type and non-waste type. The generation model, based on the cropped image of the target and pre-trained human motion information, generates the human motion information, including: The target cropped image features corresponding to the target cropped image are input in parallel into the hand area recognition model and the garbage area recognition model to generate the hand area and the garbage area; The local image features corresponding to the area where the hand is located in the cropped image of the target are input into the hand action classification layer to generate a hand action category. The local image features corresponding to the area where the garbage is located in the cropped image of the target are input into the garbage type classification layer to generate garbage classification categories; In response to determining that the hand action category is a grasping category and the waste classification category is a waste category, the intersection and union ratio of the areas where the waste is located and the areas where the hand is located is determined; In response to the region intersection-to-union ratio being greater than a preset region intersection-to-union ratio, and the region center of the area where the garbage is located being located being within the area where the hand is located, the personnel action information representing the garbage disposal action is generated.

4. The method according to claim 3, wherein, Before moving the smart trash can to the waste recycling area included in the target area, the method further includes: The garbage is packaged in the detachable garbage bin using the garbage sealing device inside the smart garbage bin.

5. The method according to claim 4, wherein, Moving the smart trash can to the target area, including the waste recycling area, includes: Determine whether a target trash can transport vehicle exists, wherein the target trash can transport vehicle is a self-propelled trash can transport vehicle that is in an idle state; In response to the existence of the trash can, a trash can recycling route is planned, wherein the trash can recycling route refers to the route taken by the transport vehicle from the location of the target trash can transport vehicle to the location of the smart trash can. The target detachable trash can is carried by the target trash can transport vehicle and moved along the trash can recycling route to the location of the smart trash can, wherein the target detachable trash can is a detachable trash can in an empty state; The target detachable trash can is replaced with the detachable trash can included in the smart trash can by the target trash can transport vehicle. In response to the completion of the replacement, the target trash can transport vehicle is controlled to move the detachable trash can, including the smart trash can, to the trash recycling area.

6. A trash can control device for use in a smart trash can, comprising: A human motion recognition unit is configured to perform human motion recognition on a target image to generate human motion information. The target image is an image captured by a camera installed on a smart trash can. The image acquisition direction of the camera is consistent with the orientation of the trash can's trash can opening. The smart trash can controls the camera to acquire images via a first infrared sensor. The human motion information includes any one of the following: trash disposal actions and non-trash disposal actions. The control unit is configured to control the opening of the garbage disposal compartment door of the smart trash can in response to the personnel action information representing the garbage disposal action, wherein the smart trash can is in a sealed state when the garbage disposal compartment door is closed; The execution unit is configured to, in response to the first infrared sensor detecting the end of the waste disposal action, perform the following processing steps: close the waste disposal hatch; in response to determining that the waste disposal hatch is closed, control the spray device inside the smart trash can to spray disinfectant; in response to determining that the disinfectant spraying has ended, determine the current waste volume indicator and current waste weight inside the smart trash can using a second infrared sensor and a pressure sensor; in response to determining that the current waste weight is less than a preset waste weight threshold and the current waste volume indicator is greater than or equal to the preset waste volume threshold, compress the waste inside the smart trash can using a waste compression device installed inside the smart trash can; in response to determining that the current waste weight is greater than or equal to the preset waste weight threshold, move the smart trash can to the waste recycling area included in the target area; The personnel action recognition unit is further configured to: The target image is cropped at multiple scales to generate a cropped image sequence, wherein the cropped images in the cropped image sequence are arranged in descending order of image scale; Based on the cropped image sequence, perform the following image processing steps: The cropped image at the beginning of the cropped image sequence is identified as the target cropped image. The image feature extraction layer of the pre-trained hand judgment model is used to extract image features from the cropped image of the target to generate the cropped image features. The image feature extraction layer includes three serially connected convolutional layers. The features of the cropped image are input into the hand classifier included in the hand judgment model to generate a classification result. The hand classifier is a binary classifier, and the classification categories of the hand classifier include: hand category and non-hand category. The hand category indicates that the cropped image contains a hand image, and the non-hand category indicates that the cropped image does not contain a hand image. In response to determining that the classification result is a hand category, a model is generated based on the cropped image of the target and pre-trained human motion information to generate the human motion information, and the image processing step is terminated. In response to determining that the classification result is not a hand category, the cropped image sequence after removing the target cropped image is used as the cropped image sequence, and the image processing steps are executed again.

7. An electronic device, comprising: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 5.

8. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 5.

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