CN112061624A - Garbage classification recognition device and recognition method - Google Patents
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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
- B65F1/006—Rigid receptacles stored in an enclosure or forming part of it
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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
- B65F1/16—Lids or covers
- B65F1/1623—Lids or covers with means for assisting the opening or closing thereof, e.g. springs
- B65F1/1638—Electromechanically operated lids
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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
- B65F2001/008—Means for automatically selecting the receptacle in which refuse should be placed
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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
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
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- B—PERFORMING OPERATIONS; TRANSPORTING
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Abstract
The invention relates to a garbage classification recognition device and a recognition method, wherein the related garbage classification recognition device comprises a garbage can, a throwing area, a recognition area and a classification area, wherein the garbage can is provided with a garbage throwing port; the putting area is positioned above the identification area, and the identification area is positioned above the classification area; the throwing area comprises a motor and a throwing plate, and the motor is connected with the throwing plate through a traction mechanism; the identification area comprises a camera, a rotating shaft and an object placing plate; the camera is arranged on the object placing plate, and the rotating shaft is connected with the object placing plate; the classification area comprises a plurality of garbage cans and steering engines, and the garbage cans are arranged along the axes of the steering engines. The invention identifies whether a person approaches through the pyroelectric infrared sensor, then judges whether the trash can cover is opened, identifies trash through a neural network algorithm, transmits a trash identification signal to the single chip microcomputer, and controls the steering engine to rotate the corresponding trash can to the trash throwing channel through the single chip microcomputer.
Description
Technical Field
The invention relates to the technical field of garbage classification, in particular to a garbage classification recognition device and method.
Background
At present, garbage classification and recovery are developed comprehensively, but the following problems exist in garbage classification in China: firstly, a large number of people in China have large garbage output, relatively complicated garbage types and low-efficiency garbage treatment methods, and basically the garbage treatment methods are incineration and landfill methods; secondly, the citizens generally have lack of consciousness on garbage classification; these problems lead to the irreversible pollution of our environment by the waste, which directly or indirectly affects the health of people; the phenomenon of refuse surrounding city has appeared in some cities. Clearly, garbage classification has become an urgent problem to be solved in China.
At present, human eye identification is adopted for garbage classification, but as the garbage types and properties tend to be complicated, the garbage treatment method is low in efficiency, and the citizens generally have lack of consciousness on garbage classification. With the rapid development of economy in China, the urbanization process is gradually accelerated, and the living standard of people is increasingly improved. In order to meet the increasing living demands of people, diversified commodities and living goods are rapidly spread. Along with the increase of domestic garbage, great pressure is exerted on the environment, and the phenomenon of refuse surrounding city appears in some cities. Clearly, garbage classification has become an urgent problem to be solved in China.
In life, with the increasing of the types and the quantity of garbage, the garbage can becomes an indispensable necessity in our life. Not only at home, on the street, also have great demand for the garbage bin in the community. But for many people it can be proposed that many people are troubled by the disposal of garbage. Therefore, special people need to be assigned to classify the garbage, and it is difficult to accurately identify the types of the garbage to which various types of garbage belong. This greatly increases manpower and material resources with the policy of four-classification of garbage.
In view of the above technical problems, it is desirable to improve.
Disclosure of Invention
The invention aims to provide a garbage classification recognition device and a garbage classification recognition method aiming at the defects of the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
a garbage classification recognition device comprises a garbage can, a garbage throwing port is arranged on the garbage can, and the garbage sorting recognition device further comprises a throwing area, a recognition area and a classification area; the putting area is positioned above the identification area, and the identification area is positioned above the classification area; the throwing area comprises a motor and a throwing plate, and the motor is connected with the throwing plate through a traction mechanism; the identification area comprises a camera, a rotating shaft and an object placing plate; the camera is arranged on the object placing plate, and the rotating shaft is connected with the object placing plate; the classification area comprises a plurality of garbage cans and steering engines, and the garbage cans are arranged along the axes of the steering engines.
Further, the identification area further comprises a plurality of sensors.
Further, still include the processing unit, processing unit is connected with camera, motor, sensor, steering wheel communication respectively.
Further, the plurality of sensors include one or more of a capacitive sensor, a metal sensor, a temperature and humidity sensor, an ultrasonic ranging sensor, and a smoke detection sensor.
Further, still include infrared sensor, infrared sensor sets up in the garbage bin outside.
Further, the traction mechanism is a traction rope.
Correspondingly, a garbage classification identification method is also provided, and the method comprises the following steps:
s1, acquiring garbage information thrown through a garbage throwing port;
s2, classifying the garbage according to the acquired garbage information to obtain a processing result, and sending a control instruction corresponding to the processing result according to the processing result;
and S3, controlling the garbage can to rotate according to the control instruction, so that the garbage falls into the garbage can corresponding to the garbage.
Further, the spam in step S1 is obtained by a camera and/or a plurality of sensors.
Further, the step S2 of classifying the garbage includes classifying the garbage information acquired by the camera based on a neural network algorithm.
Further, the step S2 of classifying the garbage includes classifying the garbage information acquired by the sensor.
Compared with the prior art, the garbage can is identified through a neural network algorithm, whether a person approaches the garbage can or not is identified through the pyroelectric infrared sensor, then whether the garbage can cover is opened or not is judged, the height position of garbage in the garbage can is detected through the ultrasonic module, the full load degree of the garbage can is judged, then a garbage identification signal is transmitted to the single chip microcomputer, and the single chip microcomputer controls the steering engine to rotate the corresponding garbage can to the garbage throwing channel. The accuracy of the combined use of the neural network algorithm, the capacitance module, the metal sensor and the temperature and humidity sensor is improved greatly. A monitoring means is provided for the residents to throw bagged garbage, and the integral system is introduced by matching with the identity recognition of the users. The correct throwing adds points to residents, and the wrong throwing reminds the residents of inquiry, so that the garbage classification consciousness of the residents is promoted, and the national garbage classification advocates. Is beneficial to garbage recovery, thereby having good environmental protection significance.
Drawings
FIG. 1 is a block diagram of an apparatus for identifying garbage classification according to an embodiment;
FIG. 2 is a system diagram of a garbage classification recognition device according to an embodiment;
FIG. 3 is a system diagram of a garbage classification recognition device according to an embodiment;
FIG. 4 is a schematic structural diagram of a convolutional neural network according to an embodiment;
FIG. 5 is a flowchart of a garbage classification recognition method according to the second embodiment;
wherein, 100, the garbage can; 11. a motor; 12. a throwing plate; 13. a traction mechanism; 21. a camera; 22. a rotating shaft; 23. a storage plate; 31. a dustbin; 32. a steering engine; 4. an infrared sensor.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
The invention aims to provide a garbage classification recognition device and a garbage classification recognition method aiming at the defects of the prior art.
Example one
The present embodiment provides a device for identifying garbage classification, as shown in fig. 1-2, including a garbage can 100, the garbage can is provided with a garbage throwing port, and further includes a throwing area, an identification area, and a classification area; the putting area is positioned above the identification area, and the identification area is positioned above the classification area; the throwing area comprises a motor 11 and a throwing plate 12, and the motor 11 is connected with the throwing plate 12 through a traction mechanism 13; the identification area comprises a camera 21, a rotating shaft 22, an object placing plate 23 and a sensor; the camera 21 is arranged on the object placing plate, the rotating shaft 22 is connected with the object placing plate 23, and the sensor is arranged in the identification area; the classification area comprises a plurality of garbage cans 31 and steering engines 32, and the garbage cans 31 are arranged along the axes of the steering engines 32.
It should be noted that the present embodiment specifically describes the garbage types as kitchen garbage, recyclable garbage, harmful garbage, and other garbage.
The top of the trash can 100 is also provided with a trash can cover (not shown in fig. 1).
The trash can 100 further comprises an infrared sensor 4 arranged on the outer side of the trash can, wherein the infrared sensor is a pyroelectric infrared sensor; in the present embodiment, the specific position of the infrared sensor is not limited to the position shown in fig. 1, and the infrared sensor may be installed at a position where it is detected that a person approaches.
As shown in fig. 3, the trash can 100 further includes a processing unit, which is a single chip microcomputer STM32 and is respectively in communication connection with a camera, a motor, a sensor, a steering engine, and the like, for processing related data information. The position of the single chip microcomputer is not shown in fig. 1, and the installation position of the single chip microcomputer is only required to be capable of communicating with the related components, which is not limited in this embodiment.
The throwing area comprises a motor 11, a throwing plate 12 and a traction mechanism 13; the size of the throwing plate 12 is not more than the height from the throwing area to the identification area, the throwing plate 12 is parallel to the top of the garbage can in an initial state, and at the moment, a traction mechanism 13 connected with the motor 11 of the throwing plate 12 is in a tensioning state; when infrared sensor 4 detected that there is the personnel to be close to, infrared sensor 4 sends the information that detects to the singlechip, whether the singlechip judges that personnel are close to surpass preset time (as 2s), if yes, then singlechip driving motor 11 makes the automatic opening of rubbish bung, the singlechip still judges whether there is rubbish to place in on throwing board 12, if there is, then the singlechip will control motor work, make the drive mechanism 13 that links to each other with the motor be in the state of relaxing, and then make the one end of throwing board and drive mechanism 13 connection drop, the messenger places rubbish on throwing board 12 and drops on putting thing board 23.
In the present embodiment, the position where the drawing mechanism 13 is connected to the projection plate 12 is not limited, and it is preferably connected to both sides of the projection plate 12.
The identification area comprises a camera 21, a rotating shaft 22, an object placing plate 23 and a sensor; the camera 21 is arranged on the object placing plate 23, the rotating shaft 22 is fixedly connected with the object placing plate 23, two ends of the rotating shaft 22 are connected with two sides of the garbage can 100, and the sensor is arranged in the identification area.
In this embodiment, 2 cameras are preferably arranged on the object placing plate 23, and are used for acquiring image information of garbage and transmitting the acquired information to the single chip microcomputer;
the sensor comprises one or more of an ultrasonic ranging sensor and a smoke detection sensor. The ultrasonic ranging sensor is used for detecting the full load degree of the garbage can so as to remind a user whether the garbage needs to be taken out or not; the smoke detection sensor is used for detecting whether open fire exists in the garbage can or not, and safety is guaranteed.
Under the reinitialization state of the identification area, the object placing plate 23 is parallel to the top of the garbage can; when the garbage on the throwing plate 12 falls on the object placing plate 23, the camera acquires relevant image information of the garbage and transmits the acquired image information to the single chip microcomputer, the single chip microcomputer classifies the image information acquired by the camera 21 based on a neural network algorithm to obtain a processing result, and then the single chip microcomputer controls the rotating shaft 22 to rotate so that the object placing plate 23 rotates along with the rotation of the rotating shaft, and the garbage falls.
In this embodiment, the sensor further includes a capacitance sensor, a metal sensor, and a temperature and humidity sensor; the capacitance sensor is used for detecting the capacitance value of the garbage; the metal sensor is used for detecting whether the garbage contains metal; the temperature and humidity sensor is used for detecting the temperature and the humidity of the garbage. The purpose that this embodiment set up capacitive sensor, metal sensor, temperature and humidity sensor is that there are some unable discernment rubbish after carrying out analysis processes through neural network algorithm, like wet rubbish (the milk box that has milk), can utilize capacitive sensor, temperature and humidity sensor, the metal sensor who sets up in the discernment district this moment to carry out the accuracy and distinguish, and then improve the rate of accuracy of rubbish discernment.
The capacitance sensor, the metal sensor and the temperature and humidity sensor respectively detect capacitance, metal strength, temperature and humidity of the garbage, the detected information is transmitted to the single chip microcomputer, and the single chip microcomputer can distinguish kitchen garbage from recyclable garbage by comparing capacitance values and dry and wet degrees of the garbage on the basis of preliminary recognition based on a neural network algorithm; harmful garbage can be separated by detecting whether the garbage contains metal and the capacitance value; other garbage is left, so that the accuracy of garbage identification is improved.
In this embodiment, still include display module, the display screen is connected with the singlechip, singlechip electric connection capacitive sensor, metal sensor and temperature and humidity sensor, the data of each sensor output is gathered and handled to the singlechip, display module shows the judged result of singlechip output.
In this embodiment, the classification processing of the image information acquired by the camera 21 by the single chip microcomputer based on a neural network algorithm specifically includes:
the convolutional neural network is a feedforward type neural network, as shown in fig. 4, and comprises an input layer, a convolutional layer, a pooling layer, a full-link layer and a Softmax output layer, wherein neurons of all layers are only connected with the previous layer.
The convolutional neural network has 47 layers, 33 and 11 layers are designed for the convolutional layer, different convolutional kernels with the step length of 1 and 2 are used for weighting each small pixel region on the image of the previous layer to extract the characteristic information of the pixel region, wherein the small pixel region is called a local receptive field, and the weight of the region is the convolutional kernel. The image is convoluted and added with offset value to form a characteristic diagram, and the transformation process is as follows
The pooling layer is mainly designed with 33 and 85 sizes, and only retains maximum pixel value each time by adopting maximum pooling method to achieve the effects of feature dimension reduction and data compression
The network is ingenious in that a plurality of inclusion Module groups are designed, and the Module groups use a plurality of 1X 1 convolution kernels and multi-branch convolution aggregation, so that the parameters and the layer number of the network are greatly reduced, and the operation amount of the convolution neural network is reduced. The system adopts a self-defined data set as an input layer of the network, continues to use the shared weight of the inclusion V3 network, carries out fine-tuning on the output of the network, and redefines a full connection layer. Transforming the formula by the full connection layer, namely:
successfully integrated into a one-dimensional vector, selecting tf.nn.softmax function as the classifier of the output,
wherein i is a certain article category, thereby outputting probability distribution and realizing multi-classification.
The classification area comprises a plurality of garbage cans 31 and steering engines 32, and the garbage cans 31 are arranged along the axes of the steering engines 32; steering wheel 32 is big moment of torsion steering wheel, and big moment of torsion steering wheel sets up in the dustbin below, and the preferred dustbin of this embodiment divide into 4 dustbin, describes 4 kinds of rubbish respectively. Under initial condition, the dustbin is quiescent state, and the steering wheel also does not work, and after the singlechip was accomplished rubbish classification, the singlechip sent a control command for the steering wheel, and the steering wheel drives the dustbin according to this control command and rotates, makes the dustbin corresponding with rubbish aim at rubbish and falls the entry, and then singlechip control pivot 22 rotates to make put thing board 23 rotate along with the rotation of pivot, make rubbish drop in the corresponding dustbin, guarantee that rubbish can correctly throw and put into corresponding dustbin.
In this embodiment, the garbage detection device further comprises a reset module, which is used for controlling the single chip microcomputer to enable data of the motor, the rotating shaft, the sensor and the like to be initial data after garbage accurately falls into the corresponding garbage can, resetting the data in the components to zero, and ensuring that a detection result of an article is not influenced when a next article is put into detection; and then the object placing plate and the throwing plate are restored, namely the object placing plate and the throwing plate are parallel to the top of the garbage can. Finally, the single chip microcomputer controls and controls the motor 11 to enable the garbage can cover to be automatically closed.
The discernment of rubbish is carried out through neural network algorithm to this embodiment, whether someone is close to then judge whether open the garbage bin lid through pyroelectric infrared sensor discernment, detects the high position of rubbish in the dustbin through the ultrasonic module to judge the full load degree of dustbin, then pass to the singlechip through rubbish discernment's signal, put in the passageway with corresponding garbage bin rotation by single chip microcomputer control steering wheel. The accuracy of the combined use of the neural network algorithm, the capacitance module, the metal sensor and the temperature and humidity sensor is improved greatly. A monitoring means is provided for the residents to throw bagged garbage, and the integral system is introduced by matching with the identity recognition of the users. The correct throwing adds points to residents, and the wrong throwing reminds the residents of inquiry, so that the garbage classification consciousness of the residents is promoted, and the national garbage classification advocates. Is beneficial to garbage recovery, thereby having good environmental protection significance.
Example two
The embodiment provides a method for identifying garbage classification, as shown in fig. 5, including the steps of:
s11, acquiring garbage information thrown through a garbage throwing port;
s12, classifying the garbage according to the acquired garbage information to obtain a processing result, and sending a control instruction corresponding to the processing result according to the processing result;
and S13, controlling the garbage can to rotate according to the control instruction, so that the garbage falls into the garbage can corresponding to the garbage.
The method for identifying the garbage classification disclosed in the embodiment is based on the device for identifying the garbage classification in the first embodiment.
Before step S11, the method further includes:
s10, judging whether a person approaches the garbage can or not.
Whether people are close to the garbage can or not is detected through the infrared sensor arranged on the outer side of the garbage can, the time of the people staying at the garbage can exceeds the preset time, the single chip microcomputer control motor enables the garbage can cover to be opened, the people place garbage on the throwing plate at the moment, the single chip microcomputer control motor works, the traction mechanism connected with the motor is in a relaxing state, and then one end of the throwing plate connected with the traction mechanism falls down, so that the garbage placed on the throwing plate falls on the object placing plate.
In step S11, garbage information thrown through the garbage throwing port is acquired.
When rubbish drops on putting the thing board from throwing the board, the camera carries out the image acquisition to current rubbish from different angles, and the camera transmits the image information who obtains to the singlechip.
In step S12, the garbage is classified according to the acquired garbage information to obtain a processing result, and a control instruction corresponding to the processing result is sent according to the processing result.
The single chip microcomputer analyzes and processes the image information transmitted by the camera based on a neural network algorithm. The analysis processing of the neural network algorithm specifically comprises the following steps:
acquiring a training picture in advance, inputting the training picture into a neural network as input data for training to obtain a neural network model; then testing the neural network model, inputting test data into the neural network model, judging whether the output result is consistent with the actual result, and if so, obtaining the final neural network model; if not, the neural network model is corrected to obtain the final neural network model.
And after the single chip microcomputer acquires the image information transmitted by the camera, inputting the image information into a pre-trained neural network model to obtain a classification result.
In step S13, the trash can is controlled to rotate according to the control command, so that the trash falls into the trash can corresponding to the trash.
After the singlechip obtained the classification result of current rubbish, the steerable steering wheel of singlechip changes and changes, makes the dustbin that corresponds be in rubbish and falls into the entry, and then the control pivot makes rubbish fall into the garbage bin from putting the thing board, accomplishes throwing in of rubbish, and single chip microcomputer control motor makes the garbage bin lid closed at last.
The discernment of rubbish is carried out through neural network algorithm to this embodiment, whether someone is close to then judge whether open the garbage bin lid through pyroelectric infrared sensor discernment, detects the high position of rubbish in the dustbin through the ultrasonic module to judge the full load degree of dustbin, then pass to the singlechip through rubbish discernment's signal, put in the passageway with corresponding garbage bin rotation by single chip microcomputer control steering wheel.
EXAMPLE III
The difference between the method for identifying garbage classification provided in this embodiment and the second embodiment is that:
after the image that this embodiment singlechip obtained to the camera is handled, still include:
and classifying the garbage information acquired by the sensor.
Specifically, a capacitance sensor, a metal sensor and a temperature and humidity sensor which are arranged in the identification area respectively detect the capacitance, metal strength, temperature and humidity of the garbage, and transmit the detected information to a single chip microcomputer, and the single chip microcomputer can distinguish kitchen garbage from recyclable garbage by comparing the capacitance value and the dry and wet degree of the garbage on the basis of the primary identification based on a neural network algorithm; harmful garbage can be separated by detecting whether the garbage contains metal and the capacitance value; other garbage is left, so that the accuracy of garbage identification is improved.
The embodiment improves the combined use accuracy of the neural network algorithm, the capacitance module, the metal sensor and the temperature and humidity sensor, and greatly improves the combined use accuracy. A monitoring means is provided for the residents to throw bagged garbage, and the integral system is introduced by matching with the identity recognition of the users. The correct throwing adds points to residents, and the wrong throwing reminds the residents of inquiry, so that the garbage classification consciousness of the residents is promoted, and the national garbage classification advocates. Is beneficial to garbage recovery, thereby having good environmental protection significance.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A garbage classification recognition device comprises a garbage can, wherein a garbage throwing port is formed in the garbage can, and the garbage classification recognition device is characterized by further comprising a throwing area, a recognition area and a classification area; the putting area is positioned above the identification area, and the identification area is positioned above the classification area; the throwing area comprises a motor and a throwing plate, and the motor is connected with the throwing plate through a traction mechanism; the identification area comprises a camera, a rotating shaft and an object placing plate; the camera is arranged on the object placing plate, and the rotating shaft is connected with the object placing plate; the classification area comprises a plurality of garbage cans and steering engines, and the garbage cans are arranged along the axes of the steering engines.
2. The device of claim 1, wherein the identification area further comprises a plurality of sensors.
3. The garbage classification recognition device according to claim 2, further comprising a processing unit, wherein the processing unit is in communication connection with the camera, the motor, the sensor and the steering engine respectively.
4. The device for identifying trash classification of claim 2, wherein the plurality of sensors comprises one or more of a capacitive sensor, a metal sensor, a temperature and humidity sensor, an ultrasonic distance measuring sensor, and a smoke detecting sensor.
5. The device for identifying the classification of trash of claim 1, further comprising an infrared sensor disposed outside the trash can.
6. A waste classification apparatus as claimed in claim 5, characterised in that the traction means is a traction rope.
7. A method for identifying a garbage classification, which is based on the garbage classification identifying device of any one of claims 1-6, and comprises the following steps:
s1, acquiring garbage information thrown through a garbage throwing port;
s2, classifying the garbage according to the acquired garbage information to obtain a processing result, and sending a control instruction corresponding to the processing result according to the processing result;
and S3, controlling the garbage can to rotate according to the control instruction, so that the garbage falls into the garbage can corresponding to the garbage.
8. The method for identifying garbage classification as claimed in claim 7, wherein the garbage information in step S1 is obtained by a camera and/or several sensors.
9. The method for identifying spam according to claim 8, wherein the step S2 of classifying spam includes classifying spam acquired by the camera based on a neural network algorithm.
10. The method for identifying trash classification of claim 7, wherein the step S2 of classifying trash includes classifying trash information obtained by a sensor.
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112499051A (en) * | 2021-01-04 | 2021-03-16 | 中电建路桥集团有限公司 | Garbage can capable of classifying garbage |
| CN112660656A (en) * | 2020-12-16 | 2021-04-16 | 康鹏程 | Environmental protection has dustbin of waste classification function |
| CN112849814A (en) * | 2020-12-30 | 2021-05-28 | 西安建筑科技大学 | Garbage identification and throwing device and control method thereof |
| CN112918956A (en) * | 2021-02-20 | 2021-06-08 | 陆伟凤 | Garbage classification system based on image recognition technology |
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| CN113213005A (en) * | 2021-04-26 | 2021-08-06 | 长春工程学院 | Automatic change refuse classification processing apparatus |
| CN113213016A (en) * | 2021-05-31 | 2021-08-06 | 南京工业大学 | Garbage recognition and classification algorithm based on ViT, and device and control method thereof |
| CN113233033A (en) * | 2021-06-01 | 2021-08-10 | 陕西科技大学 | Intelligent classification dustbin |
| CN113401529A (en) * | 2021-06-15 | 2021-09-17 | 北京科技大学 | Automatic garbage classification device and method |
| CN113562355A (en) * | 2021-08-10 | 2021-10-29 | 南京航空航天大学 | Intelligent garbage sorting device and method based on deep learning technology |
| CN114030796A (en) * | 2021-04-14 | 2022-02-11 | 宜兴市苏嘉环保设备有限公司 | Use method of assembled household garbage transfer station |
| KR102412255B1 (en) * | 2021-12-07 | 2022-06-23 | 주식회사 그레이트퍼즐 | Recycling waste separation system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109389161A (en) * | 2018-09-28 | 2019-02-26 | 广州大学 | Rubbish identification evolutionary learning method, apparatus, system and medium based on deep learning |
| CN110271792A (en) * | 2019-06-24 | 2019-09-24 | 浙江云澎科技有限公司 | A kind of dustbin of the automatic sorting rubbish of energy |
| CN110395505A (en) * | 2019-08-06 | 2019-11-01 | 东莞弓叶互联科技有限公司 | Rotating disc type intelligence garbage-sorting bucket and garbage-sorting method |
| CN110817180A (en) * | 2019-11-13 | 2020-02-21 | 江苏方时远略科技咨询有限公司 | Intelligent garbage recycling and classifying barrel and application thereof |
| CN111332651A (en) * | 2020-03-16 | 2020-06-26 | 河海大学常州校区 | Photoelectric sensing garbage bin based on degree of depth study |
-
2020
- 2020-07-13 CN CN202010666890.5A patent/CN112061624A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109389161A (en) * | 2018-09-28 | 2019-02-26 | 广州大学 | Rubbish identification evolutionary learning method, apparatus, system and medium based on deep learning |
| CN110271792A (en) * | 2019-06-24 | 2019-09-24 | 浙江云澎科技有限公司 | A kind of dustbin of the automatic sorting rubbish of energy |
| CN110395505A (en) * | 2019-08-06 | 2019-11-01 | 东莞弓叶互联科技有限公司 | Rotating disc type intelligence garbage-sorting bucket and garbage-sorting method |
| CN110817180A (en) * | 2019-11-13 | 2020-02-21 | 江苏方时远略科技咨询有限公司 | Intelligent garbage recycling and classifying barrel and application thereof |
| CN111332651A (en) * | 2020-03-16 | 2020-06-26 | 河海大学常州校区 | Photoelectric sensing garbage bin based on degree of depth study |
Cited By (18)
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| CN112660656A (en) * | 2020-12-16 | 2021-04-16 | 康鹏程 | Environmental protection has dustbin of waste classification function |
| CN112849814A (en) * | 2020-12-30 | 2021-05-28 | 西安建筑科技大学 | Garbage identification and throwing device and control method thereof |
| CN112499051A (en) * | 2021-01-04 | 2021-03-16 | 中电建路桥集团有限公司 | Garbage can capable of classifying garbage |
| CN112918956A (en) * | 2021-02-20 | 2021-06-08 | 陆伟凤 | Garbage classification system based on image recognition technology |
| CN113019984A (en) * | 2021-03-05 | 2021-06-25 | 三峡大学 | Intelligent household garbage classification system |
| CN114030796A (en) * | 2021-04-14 | 2022-02-11 | 宜兴市苏嘉环保设备有限公司 | Use method of assembled household garbage transfer station |
| CN114212423B (en) * | 2021-04-14 | 2022-09-13 | 宜兴市苏嘉环保设备有限公司 | Household garbage transfer device |
| CN113104428A (en) * | 2021-04-14 | 2021-07-13 | 苏州大学 | Non-contact intelligent garbage classification system |
| CN114030796B (en) * | 2021-04-14 | 2022-09-06 | 宜兴市苏嘉环保设备有限公司 | Use method of assembled household garbage transfer station |
| CN114212423A (en) * | 2021-04-14 | 2022-03-22 | 宜兴市苏嘉环保设备有限公司 | Household garbage transfer device |
| CN113213005A (en) * | 2021-04-26 | 2021-08-06 | 长春工程学院 | Automatic change refuse classification processing apparatus |
| CN113060441A (en) * | 2021-04-29 | 2021-07-02 | 三峡大学 | Garbage classification throwing system and throwing method |
| CN113200259A (en) * | 2021-05-19 | 2021-08-03 | 山东大学 | Multi-throw single-separation intelligent garbage classified collection device and method |
| CN113213016A (en) * | 2021-05-31 | 2021-08-06 | 南京工业大学 | Garbage recognition and classification algorithm based on ViT, and device and control method thereof |
| CN113233033A (en) * | 2021-06-01 | 2021-08-10 | 陕西科技大学 | Intelligent classification dustbin |
| CN113401529A (en) * | 2021-06-15 | 2021-09-17 | 北京科技大学 | Automatic garbage classification device and method |
| CN113562355A (en) * | 2021-08-10 | 2021-10-29 | 南京航空航天大学 | Intelligent garbage sorting device and method based on deep learning technology |
| KR102412255B1 (en) * | 2021-12-07 | 2022-06-23 | 주식회사 그레이트퍼즐 | Recycling waste separation system |
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