CN113697319A - Intelligent kitchen garbage dumping device - Google Patents
Intelligent kitchen garbage dumping device Download PDFInfo
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- CN113697319A CN113697319A CN202110968831.8A CN202110968831A CN113697319A CN 113697319 A CN113697319 A CN 113697319A CN 202110968831 A CN202110968831 A CN 202110968831A CN 113697319 A CN113697319 A CN 113697319A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/0033—Refuse receptacles; Accessories therefor specially adapted for segregated refuse collecting, e.g. receptacles with several compartments; Combination of receptacles
- B65F1/0053—Combination of several receptacles
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47B—TABLES; DESKS; OFFICE FURNITURE; CABINETS; DRAWERS; GENERAL DETAILS OF FURNITURE
- A47B31/00—Service or tea tables, trolleys, or wagons
- A47B31/001—Service or tea tables, trolleys, or wagons with devices for laying, clearing, cleaning, or the like, a table
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/14—Other constructional features; Accessories
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F2210/00—Equipment of refuse receptacles
- B65F2210/184—Weighing means
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W30/00—Technologies for solid waste management
- Y02W30/10—Waste collection, transportation, transfer or storage, e.g. segregated refuse collecting, electric or hybrid propulsion
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- Life Sciences & Earth Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Processing Of Solid Wastes (AREA)
Abstract
The invention discloses an intelligent kitchen waste dumping device which comprises a table body, wherein a garbage can is arranged below the table body, a weighing device is arranged at the bottom of the garbage can and is used for weighing kitchen waste dumped by a current diner, a camera device, a user identity information acquisition device, a processor and a display screen are arranged on an intelligent operation table, the camera device is used for acquiring a dinner plate image and a kitchen waste image, the user identity information acquisition device is used for acquiring information of the diner dumped with the kitchen waste, the processor is used for inquiring ordering information of the diner according to the acquired diner information, whether the diner belongs to a compact disc behavior or not is analyzed according to the ordering information, the dinner plate image, the kitchen waste image and the weight of the kitchen waste, and the display screen is used for displaying the acquired data and the analyzed result. The device can not only classify kitchen garbage, can also analyze out according to the kitchen garbage data analysis that the person of having a dinner whether is the CD action with the kitchen garbage data of empting, promotes the environmental protection consciousness of person of having a dinner, reduces carbon and discharges.
Description
Technical Field
The invention relates to the technical field of kitchen waste recovery, in particular to an intelligent kitchen waste dumping device.
Background
The kitchen waste is solid waste generated in production, transportation, distribution and consumption links of food, and has the main physical and chemical characteristics of high moisture content, high organic matter content, high oil and salt content, various trace elements, easiness in storage, easiness in odor and the like. Due to high water content, the kitchen waste cannot meet the requirement of heat productivity (not lower than 5000kJ/kg) of waste incineration, and is not suitable for direct landfill, and the incineration and the landfill cause a great deal of waste of organic matters; meanwhile, the garbage pig, hogwash oil and the like derived from kitchen garbage are harmful to human health, and the kitchen garbage is directly discharged into a sewer and can cause methane gas explosion and other problems. With the increase of urban scale and population, kitchen waste is increasing, so that the treatment and disposal of kitchen waste are attracting more and more attention. As the main components of the kitchen waste, such as starch, cellulose, protein, lipid, inorganic salt and the like, can be recycled, the source separation and resource treatment of the kitchen waste can not only avoid the mutual pollution among all the components of the waste, but also greatly reduce the pressure of the tail end treatment of the municipal waste.
At present, the existing kitchen waste dumping device only sorts and throws the waste, but does not analyze the habits of diners, whether the behavior is compact disc behavior and the like.
Disclosure of Invention
Aiming at the defects in the prior art, the embodiment of the invention provides an intelligent kitchen waste dumping device which can not only carry out classified putting management on kitchen waste, but also analyze whether a diner is in a compact disc behavior or not according to ordering information of the diner and dumped kitchen waste data.
The embodiment of the invention provides an intelligent kitchen waste dumping device, which comprises a table body, wherein a waste dumping opening and a dinner plate placing area are arranged on the table top of the table body, a garbage can is arranged at the lower part of the table body, a weighing device is arranged at the bottom of the garbage can, the weighing device automatically resets before weighing each time, kitchen waste dumped by a current diner is weighed to obtain the weight of the kitchen waste, an intelligent operation table is further arranged on the table body, a camera device, a user identity information acquisition device, a processor and a display screen are arranged on the intelligent operation table, the camera device is arranged above the dinner plate placing area and used for acquiring a dinner plate image and a kitchen waste image, the user identity information acquisition device is used for acquiring information of the diner dumping the kitchen waste, the processor is used for inquiring ordering information of the diner according to the acquired diner information, whether the diner belongs to the behavior of the optical disk is analyzed according to the ordering information, the dinner plate image, the kitchen garbage image and the weight of the kitchen garbage, and the display screen is used for displaying the collected data and the analysis result.
Optionally, an ultrasonic detection device is further arranged on the table body or the intelligent operation table, and the ultrasonic detection device is used for detecting the distance between the diner and the table body and judging whether the diner leans forwards on the table body to dump kitchen garbage and whether dumping is finished.
Optionally, the user identity information acquisition device includes a radio frequency card reading module, a two-dimensional code recognition module and/or a face detection module.
Optionally, the processor includes an intelligent weighing analysis unit, and the intelligent weighing analysis unit is configured to query ordering information of the diner according to the user identity information, query a preset kitchen garbage threshold of the diner according to the ordering information, and determine whether the diner is performing the optical disc operation this time according to the ordering information, the weight of the kitchen garbage and the kitchen garbage threshold, so as to obtain a first determination result.
Optionally, the processor further includes an intelligent image recognition unit, and the intelligent image recognition unit is configured to partition a dinner plate image dumped by the diner, compare the extracted kitchen waste image with a meal image during ordering, and determine whether the diner is an optical disc behavior this time according to a ratio of the partition occupied by the kitchen waste and a color and size change of the kitchen waste, so as to obtain a second determination result.
Optionally, the processor further includes an artificial intelligence recognition unit, and the artificial intelligence recognition unit recognizes the dinner plate image dumped by the diner and the kitchen garbage image in the dinner plate by using a convolutional neural network, and judges whether the diner is in the optical disc behavior at this time, so as to obtain a third judgment result.
Optionally, the artificial intelligence recognition unit further includes a model training subunit, where the model training subunit compares the third determination result with the first determination result and the second determination result, and if the third determination result is different from the first determination result or the second determination result, it is determined that the image is a recognition error or an image to be confirmed, and the recognition error or the image to be confirmed is input into the error problem to further train the neural network.
Optionally, the intelligent operation platform is obliquely arranged on the table top, and an included angle formed between the intelligent operation platform and the table top is 100-130 °.
Optionally, the trash can includes a dry trash can and a wet trash can.
The invention has the beneficial effects that:
the intelligent kitchen waste dumping device provided by the embodiment of the invention not only can classify and manage kitchen waste, but also can analyze whether a diner is in a CD behavior according to ordering information of the diner and dumping kitchen waste data, so that the environmental awareness of the diner is improved, and carbon emission is reduced.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a schematic structural diagram illustrating an intelligent kitchen garbage dumping device according to an embodiment of the present invention;
fig. 2 shows a schematic block diagram of an intelligent kitchen garbage dumping device provided by the embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. 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 invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
Referring to fig. 1 and 2, an intelligent kitchen waste dumping device provided by a first embodiment of the invention comprises a table body 1, a waste dumping opening 2 and a dinner plate placing area are arranged on a table top of the table body, a garbage can 3 is arranged at the lower part of the table body, a weighing device 4 is arranged at the bottom of the garbage can 3, the weighing device 4 is automatically reset before weighing each time, kitchen waste dumped by a current diner is weighed to obtain the weight of the kitchen waste, an intelligent operation table 5 is further arranged on the table body, a camera device 6, a user identity information acquisition device 7, a processor 8 and a display screen 9 are arranged on the intelligent operation table 5, the camera device 6 is arranged above the dinner plate placing area and used for acquiring an image of the dinner plate and an image of the kitchen waste, the user identity information acquisition device 7 is used for acquiring information of the diner dumping the kitchen waste, the processor 8 is used for inquiring ordering information of the diner according to the acquired information of the diner, whether the diner belongs to the behavior of the optical disk is analyzed according to the ordering information, the dinner plate image, the kitchen garbage image and the weight of the kitchen garbage, and the display screen 9 is used for displaying the acquired data and the analysis result. In the present embodiment, the image pickup apparatus employs a high-speed scanner.
The user identity information acquisition device 7 comprises a radio frequency card reading module, a two-dimensional code recognition module and/or a face detection module. In this embodiment, the user identity information acquisition device 7 adopts a face detection module as an example for explanation. When a diner pours kitchen waste, the face detection module collects a face image of the diner, the camera device collects a kitchen waste image and a dinner plate image of the diner when the kitchen waste is poured, the weighing device resets and resets before weighing and then weighs the kitchen waste, so that the weight of the weighed kitchen waste is the weight of the kitchen waste, the kitchen waste is accurately measured, and the weighing device can accurately reach the range of 1 g-100 kg. The processor acquires ordering information of the diner and basic information of the user according to the face image information, analyzes whether the diner belongs to the behavior of the optical disc according to the ordering information, the dinner plate image, the kitchen garbage image and the kitchen garbage weight, and displays the acquired data and the analysis result through the display screen.
The table body or the intelligent operation table is also provided with an ultrasonic detection device 10, and the ultrasonic detection device 10 is used for detecting the distance between a diner and the table body and judging whether the diner leans forwards on the table body to dump kitchen garbage and whether dumping is finished. The ultrasonic detection device 10 judges whether a person dumps kitchen waste or not according to the time difference between the ultrasonic emission signal and the ultrasonic reception signal, the ultrasonic detection device 10 can detect the human body within a short distance of 0.1-1.4 m, when a shelter/obstacle is found within the distance, the dumping of the kitchen waste is judged not to be finished, and when the time of no obstacle within the short distance of 0.1-1.4 m of the ultrasonic detection device exceeds 3 seconds or more, the dumping action is judged to be finished. Set up ultrasonic detection device and empty kitchen garbage and detect the diner, whether can accurate detection diner empties kitchen garbage and empties and finish.
The processor 8 comprises an intelligent weighing and analyzing unit 81, wherein the intelligent weighing and analyzing unit 81 is used for inquiring ordering information of a diner according to the user identity information, inquiring a kitchen garbage threshold value of a diner according to the ordering information, and judging whether the diner is an optical disc behavior at this time according to the ordering information, the weight of the kitchen garbage and the kitchen garbage threshold value to obtain a first judgment result. And the kitchen waste threshold value of the food is set according to the Internet nutritional diet database and by combining with the kitchen waste characteristic values of different areas. For example: the dishes of the diner A at the time of ordering comprise corn and sparerib soup, green pepper and shredded meat, fried shredded potatoes and rice, when the diner A pours kitchen garbage, the face detection module detects a face image, the ordering information of the diner is obtained according to face identification information, the intelligent weighing and analyzing unit 81 judges that the remaining corn kernels and sparerib bones and the like are kitchen garbage according to the dishes, the kitchen garbage threshold of the corn and sparerib soup set according to the Internet nutritional diet database is 50-60 g, the sum of the kitchen garbage thresholds of 3 kinds of diners is 10 g, and if the weight of the obtained kitchen garbage is 70 g, the intelligent weighing and analyzing unit judges that the diner A is in a compact disc behavior at this time; if the weight of the kitchen garbage obtained in the weighing process is 85 g, the intelligent weighing and analyzing unit judges that the diner A is not a compact disc behavior at this time.
The processor 8 further comprises an intelligent image recognition unit 82, wherein the intelligent image recognition unit 82 is configured to partition a dinner plate image dumped by the diner, compare the extracted kitchen waste image with a meal image during ordering, and judge whether the diner is in a compact disc behavior this time according to the proportion of the partition occupied by the kitchen waste and the color and size change of the kitchen waste to obtain a second judgment result.
The method for identifying the kitchen garbage in the dinner plate by the intelligent image identification unit 82 comprises the following steps: firstly, preprocessing an acquired dinner plate image poured by a diner by adopting guide filtering, initially segmenting by adopting SLIC superpixel clustering, constructing a graph model by taking superpixels as a basis, further aggregating the superpixels by utilizing a local variation thought to form different regions, finally extracting the regions belonging to kitchen garbage by utilizing a region analysis method, uniformly classifying the regions not belonging to the kitchen garbage into a background to obtain a final segmentation result, and thus obtaining the kitchen garbage. The guided filtering has good edge protection and noise removal properties, and when using the dumped dinner tray image as a guide image, can obscure all food ingredients within each tray while ensuring that the edge information for each tray is still present. The guide filtering is beneficial to the subsequent processing correction of the image, and the super pixels which are more suitable for the whole edge of the meal can be formed. Because the meal feature changes greatly, the segmentation result generates a lot of noise points based on the low-order features extracted from the pixel points, and the segmentation integrity is poor. The super-pixels are a set of adjacent pixel points with similar characteristics, are high-order characteristic representations of images, and replace the pixel points by adopting the super-pixels, so that the high-order characteristics of the food can be captured more abundantly, the segmented edges are smoother, and the segmented results are more complete. And further aggregating the superpixels by using the idea of local variation to form different regions, and performing region analysis on the formed different regions to divide the foreground region and the background region. The region analysis method specifically comprises the following steps: the method comprises the steps of area shape analysis, inclusion relation detection, area splitting, area merging, rectangle degree analysis and isolated area judgment, and can effectively extract various kitchen waste images from dumped kitchen waste images, and judge whether the kitchen waste images are optical discs according to the proportion of partitions occupied by the kitchen waste and the change of the color and the size of the kitchen waste.
The processor 8 further includes an artificial intelligence recognition unit 83, and the artificial intelligence recognition unit 83 recognizes the dinner plate image dumped by the diner and the kitchen garbage image in the dinner plate by using the convolutional neural network, and determines whether the diner is the optical disc behavior at this time, so as to obtain a third determination result.
The artificial intelligence recognition unit 83 further includes a model training subunit, the model training subunit compares the third determination result with the first determination result and the second determination result, if the third determination result is different from the first determination result or the second determination result, the artificial intelligence recognition unit determines that the image is a recognition error or an image to be confirmed, and inputs the recognition error or the image to be confirmed into the error problem to further train the neural network. The result of the neural network identification is compared with the result of the other 2 types of identification, and the neural network is further trained in the identification error or the image to be confirmed is input into the error problem, so that the prediction accuracy of the neural network can be improved.
The artificial intelligence recognition unit 83 reads the video stream based on the google open source deep learning toolkit tensflo Object Detection API and multithreading; multi-process, loading an object recognition model to perform partial structure fine adjustment to achieve the function of recognizing food and kitchen garbage, wherein a training platform adopts Baidu AI Studio; on the basis, a kitchen garbage recognition model based on deep learning is developed, a mobile end application system and a back end application system are developed, and deployment is carried out in a mode of combining software and hardware.
Firstly, the dish and bowl utensil for containing dishes is basically circular, so that the detection of the dish and bowl position is realized by Hough circle transformation after the dinner plate image is denoised, and the dish and bowl separation is realized. The Hough transform is a feature extraction technology in image processing, and a set conforming to the specific shape is obtained as a Hough transform result by calculating a local maximum of accumulated results in a parameter space. Secondly, the kitchen waste identification divides the kitchen waste into six types of grains, meat, fish, shrimp, egg, milk, fruits, vegetables, and the like, wherein each classification enlarges a data set of each classified dish through collecting thousands of pictures in an experimental restaurant and image augmentation processing, and reduces the influence of light and other environmental factors on the identification effect in the actual environment. Training by a neural network (sensorflow Object Detection API); the optical disk behavior prediction and judgment mainly comprises four steps: the first step is as follows: configuring a prediction environment; the second step is that: preprocessing a predicted image, cutting and scaling the predicted image, adjusting the size to [3,224,224], converting a text through a pre-training word vector model, and processing the text into an index set result; the third step: loading a prediction model and putting a prediction text into the model for prediction; the fourth step: outputting the prediction result of the behavior of the optical disc to obtain a third judgment result, and determining the category of the result; and if the third judgment result is different from the first judgment result or the second judgment result, judging that the image is wrong or is to be confirmed, and inputting the image into a wrong question to further train the neural network.
The processor adopts intelligent weighing, intelligent image recognition and artificial intelligence technology to identify whether the diner is a compact disc or not, the identification result is more accurate and reliable, the action of the compact disc is effectively converted into measurable and recordable action from the original consciousness propaganda layer, the power-assisted compact disc action is fallen in the real place, the environmental protection consciousness of the diner is improved, and the carbon emission is reduced.
In order to enable the face detection module to more accurately detect the face image of a diner dumping kitchen garbage, the intelligent operation platform is obliquely arranged on the table top of the table body, and the included angle formed by the intelligent operation platform and the table top of the table body ranges from 100 degrees to 130 degrees. The face detection module is arranged on the intelligent operation platform, the intelligent operation platform is obliquely arranged on the table body table board, other coming and going face images generated when kitchen garbage is dumped can be reduced, and the accuracy of face detection is improved.
In the present embodiment, the trash can 3 includes a dry trash can and a wet trash can. Thus, the kitchen waste can be classified.
The intelligent kitchen waste dumping device provided by the embodiment of the invention not only can classify and manage kitchen waste, but also can analyze whether a diner is in a CD behavior according to ordering information of the diner and dumping kitchen waste data, so that the environmental awareness of the diner is improved, and carbon emission is reduced.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (9)
1. The utility model provides an intelligence kitchen garbage emptys device, includes the table body, is equipped with rubbish dumping mouth and dinner plate on table body mesa and places the district, is equipped with the garbage bin in table body lower part, its characterized in that is equipped with weighing device in the bottom of garbage bin, weighing device carries out automatic re-setting before weighing at every turn after, weighs the kitchen garbage that present diner emptys and obtains the weight of kitchen garbage, still is equipped with intelligent operation panel on the table body, is equipped with camera device, user identity information acquisition device, treater and display screen on intelligent operation panel, camera device sets up in dinner plate places the district's top for gather dinner plate image and kitchen garbage image, user identity information acquisition device is used for gathering the information of the diner of empting kitchen garbage, the treater is used for inquiring diner's information of diner according to gathering, according to the information of ordering, The dinner plate image, the kitchen garbage image and the weight of the kitchen garbage analyze whether the diner belongs to the behavior of the optical disk, and the display screen is used for displaying the acquired data and the analysis result.
2. The device as claimed in claim 1, wherein an ultrasonic detection device is further provided on the table body or the intelligent operation table, and the ultrasonic detection device is used for detecting the distance between the diner and the table body and judging whether the diner leans forward on the table body to dump the kitchen garbage and whether the dumping is finished.
3. The apparatus of claim 1, wherein the user identity information acquisition means comprises a radio frequency card reading module, a two-dimensional code recognition module and/or a face detection module.
4. The apparatus of claim 3, wherein the processor comprises an intelligent weighing analysis unit, and the intelligent weighing analysis unit is configured to query ordering information of the diner according to the user identity information, query a preset kitchen garbage threshold value of the diner according to the ordering information, and judge whether the diner is in the optical disc behavior at this time according to the ordering information, the weight of the kitchen garbage and the kitchen garbage threshold value to obtain a first judgment result.
5. The apparatus of claim 4, wherein the processor further comprises an intelligent image recognition unit, and the intelligent image recognition unit is configured to partition the dinner plate image dumped by the diner, compare the extracted kitchen garbage image with the meal image at the time of ordering, and determine whether the diner is the optical disc behavior at this time according to the proportion of the partition occupied by the kitchen garbage and the color and size change of the kitchen garbage to obtain a second determination result.
6. The apparatus of claim 5, wherein the processor further comprises an artificial intelligence recognition unit, and the artificial intelligence recognition unit recognizes the dinner plate image dumped by the diner and the kitchen garbage image in the dinner plate by using a convolutional neural network, and judges whether the diner is in a compact disc behavior at this time, so as to obtain a third judgment result.
7. The apparatus of claim 6, wherein the artificial intelligence recognition unit further comprises a model training subunit, the model training subunit compares the third determination result with the first determination result and the second determination result, respectively, determines that the image is a recognition error or an image to be confirmed if the third determination result is different from the first determination result or the second determination result, and inputs the recognition error or the image to be confirmed into a wrong question to further train the neural network.
8. The device as claimed in claim 1, wherein the intelligent operation platform is obliquely arranged on the table top of the table body, and the included angle formed between the intelligent operation platform and the table top of the table body is 100-130 °.
9. The apparatus of claim 1, wherein the trash can comprises a dry trash can and a wet trash can.
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| CN117610901A (en) * | 2024-01-24 | 2024-02-27 | 成都环境工程建设有限公司 | Scheduling method and system for garbage transport vehicle of garbage power plant |
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| CN213504142U (en) * | 2020-07-31 | 2021-06-22 | 东莞理工学院 | Intelligent kitchen waste garbage can |
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| CN117610901A (en) * | 2024-01-24 | 2024-02-27 | 成都环境工程建设有限公司 | Scheduling method and system for garbage transport vehicle of garbage power plant |
| CN117610901B (en) * | 2024-01-24 | 2024-04-05 | 成都环境工程建设有限公司 | Scheduling method and system for garbage transport vehicle of garbage power plant |
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