CN108861183A - A kind of intelligent garbage classification method based on machine learning - Google Patents
A kind of intelligent garbage classification method based on machine learning Download PDFInfo
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- CN108861183A CN108861183A CN201810250127.7A CN201810250127A CN108861183A CN 108861183 A CN108861183 A CN 108861183A CN 201810250127 A CN201810250127 A CN 201810250127A CN 108861183 A CN108861183 A CN 108861183A
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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
-
- 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
- B65F2210/168—Sensing 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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Abstract
The present invention discloses a kind of intelligent garbage classification method based on machine learning, includes the following steps：Automatic garbage classification system is provided, it includes garbage sorting device, several refuse collectors, multiple sensors and computer；The several rubbish classification to be divided is preset on computers, and inputs the corresponding junk data of various rubbish classifications, and the corresponding characteristics of spam of various rubbish classifications is constructed using machine learning model based on the junk data inputted；The several rubbish classification provided is defaulted according to computer, user selects the rubbish classification needed；Material to be sorted is put into garbage sorting device, the data of sensor acquisition material, computer carries out feature extraction to collected data, and the material characteristics extracted are compared with the characteristics of spam in model, and automatic discrimination goes out the rubbish classification division result and its credibility of material；According to the rubbish classification division result of material, garbage sorting device is by material automatic sorting to corresponding refuse collector.
Description
Technical field
The invention belongs to field of refuse classification, in particular to a kind of intelligent garbage classification side based on machine learning
Method.
Background technique
With the economic development and urbanization process of China, the rubbish that resident living generates is also more and more；China have by
Nearly 2/3rds city is surrounded by rubbish annulus, and improperly garbage disposal, will cause a series of serious harms.Currently,
Urban is to better people's living environment, and issues a series of categorized consumer waste management policies successively, as Xiamen City is directed to life rubbish
Rubbish is classified, and is divided into Recyclable, rubbish from cooking, Harmful Waste, four class of Other Waste, by dividing from upstream rubbish
Class improves the destructor plant treatment effeciency in downstream.And garbage classification it is main at this stage or by sorting personnel manually into
Row, sorting personnel need the classification of do-it-yourself rubbish to judge and be sent into the dustbin accordingly classified, sort people according to statistics
Member's average minute clock makes 40 sorting operations, there are great work intensity, wrong after working efficiency is low and long-term work divides rate high
Disadvantage.
Summary of the invention
In order to overcome the shortcomings of the prior art, technical problem to be solved by the invention is to provide one kind to be based on machine
The intelligent garbage classification method of study, this method can reduce the working strength of sorting personnel, while improve garbage sorting efficiency
And accuracy rate.
In order to solve the above technical problems, the technical solution adopted by the present invention is that：A kind of intelligent garbage based on machine learning
Classification method comprising following steps：
S1, an automatic garbage classification system is provided, the automatic garbage classification system includes garbage sorting device, several rubbish
Collection device, multiple sensors and the computer that the garbage sorting device work is connect and controlled with the sensor, institute
Sensor is stated to be arranged in the garbage sorting device；
S2, the several rubbish classification to be divided is preset on the computer, and it is corresponding to input various rubbish classifications
Junk data constructs the corresponding characteristics of spam of various rubbish classifications using machine learning model based on the junk data inputted；
S3, the several rubbish classification provided is defaulted according to the computer, user selects the rubbish classification needed；
S4, material to be sorted is put into the garbage sorting device, the sensor acquires the data of the material, the meter
Calculation machine carries out feature extraction to the collected material data of the sensor, and by the rubbish in the material characteristics and model that extract
Rubbish feature is compared, and automatic discrimination goes out the rubbish classification division result and its credibility of the material；
S5, according to the computer to the rubbish classification division result of material, the garbage sorting device is automatic by the material
It is sorted to corresponding refuse collector；
S6, after whole material automatic sortings, the computer provide sorting result statistics.
Scheme as a further preference, in S2 step, the preset rubbish classification of computer includes that can return
Receive rubbish, rubbish from cooking, Harmful Waste and Other Waste.
Scheme as a further preference, in the S3 step, if the rubbish classification that user needs does not appear in computer and writes from memory
In the rubbish classification option recognized, then new rubbish classification is defined on the computer.
Scheme as a further preference, the new rubbish classification include metal garbage, wooden rubbish and Other Waste.
Scheme as a further preference, in S4 step, after sensor acquires end of data, first by the material hand
Dynamic to be sorted to corresponding refuse collector, after manual sortation runs up to predetermined sorting quantity, the computer can be fed back to
The accuracy rate that user currently divides allows user to automatically select termination or be to continue with manual sortation, until accuracy rate reaches user
Stop manual sortation after it is expected that, switchs to automatic sorting later.
Scheme as a further preference, if the computer discriminant mistake, passes through manual correction in S4 step,
Model is set to export correct rubbish classification.
Scheme as a further preference, in S6 step, the sorting result statistics is comprising time-consuming, sorting quantity and divides
Pick one of speed or a variety of.
Scheme as a further preference, in S1 step, the garbage sorting device includes sorting platform and sorter
Tool hand.
Scheme as a further preference, in S1 step, the refuse collector is dustbin.
Scheme as a further preference, in S1 step, the sensor include imaging sensor, weight sensor,
One of Tansducer For Color Distiguishing, humidity sensor, hardness transducer, volume-measuring sensors and profile measurement sensor or
It is a variety of.
Compared with prior art, the invention has the advantages that：Using automatic garbage classification system to be sorted
Material carries out intelligent recognition and classification, liberated the both hands and eyes of sorting personnel, by machine learning realize to material from
Dynamic classification, sorting personnel at most only need to be monitored automatic sorting in early period, avoid manpower waste, improve rubbish point
The working efficiency picked, while mistake point rate is reduced, it ensure that the accuracy rate of garbage sorting.
Detailed description of the invention
Fig. 1 is the architecture diagram of the embodiment of the present invention.
Fig. 2 is the functional block diagram of automatic garbage classification system.
Specific embodiment
In order to allow features described above and advantage of the invention to be clearer and more comprehensible, below spy fors embodiment, and cooperate attached drawing, make in detail
Carefully it is described as follows.
As shown in Fig. 1~2, a kind of intelligent garbage classification method based on machine learning comprising following steps：
S1, an automatic garbage classification system is provided, the automatic garbage classification system includes garbage sorting device, several rubbish
Collection device, multiple sensors and the computer that the garbage sorting device work is connect and controlled with the sensor, institute
Sensor is stated to be arranged in the garbage sorting device；
S2, the several rubbish classification (i.e. label layer) to be divided is preset on the computer, and input various rubbish
The corresponding junk data of classification constructs various rubbish using machine learning model (i.e. model layer) based on the junk data inputted
The corresponding characteristics of spam of classification；Wherein, the preset rubbish classification of the computer including but not limited to recyclable rubbish,
Rubbish from cooking, Harmful Waste and Other Waste, naturally it is also possible to be other classification forms；
S3, the several rubbish classification provided is defaulted according to the computer, user selects the rubbish classification needed；Due to system
Interior rubbish classification can adjust at any time, provide a variety of different classifications combinations and select for user, and adjust these specific names
Do not influence the use of whole system with quantity, it is very easy to use；
S4, material (i.e. original layers) to be sorted is put into the garbage sorting device, the sensor acquires the material
Data (or information, i.e. characteristic layer), the computer carry out feature extraction to the collected material data of the sensor, and
The material characteristics extracted are compared with the characteristics of spam in model, the rubbish classification that automatic discrimination goes out the material divides
And its credibility (i.e. accuracy rate) as a result；
S5, according to the computer to the rubbish classification division result of material, the garbage sorting device is automatic by the material
It is sorted to corresponding refuse collector；
S6, after whole material automatic sortings, the computer provide sorting result statistics；For example, the sorting result
Statistics includes time-consuming, sorting one of quantity and sorting speed or a variety of.
In embodiments of the present invention, in S2 step, the machine learning model can be the machines such as LR, SVM or GBDT
Learning method is also possible to deep learning method, such as CNN, RNN or LSTM etc..
In embodiments of the present invention, in the S3 step, if the rubbish classification that user needs does not appear in computer default
In rubbish classification option, then new rubbish classification is defined on the computer, realizing user can be with customized classification.Example
Such as, the new rubbish classification can also be other certainly including but not limited to metal garbage, wooden rubbish and Other Waste
New classification form.
In embodiments of the present invention, in S4 step, after sensor acquires end of data, first the material is divided manually
It picks to corresponding refuse collector, after manual sortation runs up to predetermined sorting quantity, the computer can feed back to user
The accuracy rate currently divided allows user to automatically select termination or is to continue with manual sortation, is expected until accuracy rate reaches user
After stop manual sortation, switch to automatic sorting later.
In embodiments of the present invention, in S4 step, if the computer discriminant mistake, by manual correction, make mould
Type exports correct rubbish classification.
In embodiments of the present invention, in S1 step, the garbage sorting device includes to sort platform and sorting manipulator,
It certainly can also include multiple conveying mechanisms；An entrance and multiple outlets, each outlet difference can be set in the sorting platform
It is connected to corresponding refuse collector by corresponding conveying mechanism, the refuse collector can be dustbin.
In embodiments of the present invention, in S1 step, the sensor includes imaging sensor, weight sensor, color
One of identification sensor, humidity sensor, hardness transducer, volume-measuring sensors and profile measurement sensor are more
Kind, it is image, weight, color, humidity, hardness, volume and shape using the data that sensor technology can monitor material respectively.Its
In, described image sensor can be at least one of ccd image sensor and cmos image sensor, such as rubbish from
The scanner with ccd image sensor and the camera with cmos image sensor are used in dynamic categorizing system.Wherein, institute
Stating hardness transducer is supersonic hardness sensor.
The above, only presently preferred embodiments of the present invention not do limitation in any form to the present invention, any ripe
Those skilled in the art is known in every case without departing from the content of technical solution of the present invention, according to the technical essence of the invention to the above reality
It applies example and makes any simple modification, equivalent changes and modifications, be all covered by the present invention.
Claims (10)
1. a kind of intelligent garbage classification method based on machine learning, which is characterized in that include the following steps：
S1, an automatic garbage classification system is provided, the automatic garbage classification system includes garbage sorting device, several rubbish
Collection device, multiple sensors and the computer that the garbage sorting device work is connect and controlled with the sensor, institute
Sensor is stated to be arranged in the garbage sorting device；
S2, the several rubbish classification to be divided is preset on the computer, and it is corresponding to input various rubbish classifications
Junk data constructs the corresponding characteristics of spam of various rubbish classifications using machine learning model based on the junk data inputted；
S3, the several rubbish classification provided is defaulted according to the computer, user selects the rubbish classification needed；
S4, material to be sorted is put into the garbage sorting device, the sensor acquires the data of the material, the meter
Calculation machine carries out feature extraction to the collected material data of the sensor, and by the rubbish in the material characteristics and model that extract
Rubbish feature is compared, and automatic discrimination goes out the rubbish classification division result and its credibility of the material；
S5, according to the computer to the rubbish classification division result of material, the garbage sorting device is automatic by the material
It is sorted to corresponding refuse collector；
S6, after whole material automatic sortings, the computer provide sorting result statistics.
2. the intelligent garbage classification method according to claim 1 based on machine learning, which is characterized in that in S2 step
In, the preset rubbish classification of computer includes recyclable rubbish, rubbish from cooking, Harmful Waste and Other Waste.
3. the intelligent garbage classification method according to claim 1 based on machine learning, which is characterized in that in S3 step
In, it is fixed on the computer if the rubbish classification that user needs does not appear in the rubbish classification option of computer default
The new rubbish classification of justice.
4. the intelligent garbage classification method according to claim 3 based on machine learning, which is characterized in that the new rubbish
Rubbish classification includes metal garbage, wooden rubbish and Other Waste.
5. the intelligent garbage classification method according to claim 3 based on machine learning, which is characterized in that in S4 step
In, after sensor acquires end of data, first by the material manual sortation to corresponding refuse collector, in manual sortation
After running up to predetermined sorting quantity, the computer can feed back to the accuracy rate that user currently divides, and user is allowed to automatically select end
Only or it is to continue with manual sortation, stops manual sortation until accuracy rate reaches after user is expected, switch to automatic sorting later.
6. the intelligent garbage classification method based on machine learning according to claim 1 or 5, which is characterized in that walked in S4
In rapid, if the computer discriminant mistake, by manual correction, model is made to export correct rubbish classification.
7. the intelligent garbage classification method according to claim 1 based on machine learning, which is characterized in that in S6 step
In, the sorting result statistics includes time-consuming, sorting one of quantity and sorting speed or a variety of.
8. the intelligent garbage classification method according to claim 1 based on machine learning, which is characterized in that in S1 step
In, the garbage sorting device includes sorting platform and sorting manipulator.
9. the intelligent garbage classification method according to claim 1 based on machine learning, which is characterized in that in S1 step
In, the refuse collector is dustbin.
10. the intelligent garbage classification method according to claim 1 based on machine learning, which is characterized in that in S1 step
In, the sensor include imaging sensor, weight sensor, Tansducer For Color Distiguishing, humidity sensor, hardness transducer,
One of volume-measuring sensors and profile measurement sensor are a variety of.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110276405A (en) * | 2019-06-26 | 2019-09-24 | 北京百度网讯科技有限公司 | Method and apparatus for output information |
| CN110276300A (en) * | 2019-06-24 | 2019-09-24 | 北京百度网讯科技有限公司 | The method and apparatus of rubbish quality for identification |
| CN110321972A (en) * | 2019-07-22 | 2019-10-11 | 上海五赫自动化科技中心 | A kind of wet refuse classification acceptance test method and its realization device |
| CN110329672A (en) * | 2019-07-29 | 2019-10-15 | 北京绿博伟业环保科技有限责任公司 | A kind of garbage classification device and classification method |
| CN110487370A (en) * | 2019-08-14 | 2019-11-22 | 六安智华工业自动化技术有限公司 | A kind of device recording household kitchen wastes |
| CN110535734A (en) * | 2019-08-14 | 2019-12-03 | 六安智华工业自动化技术有限公司 | A kind of rubbish from cooking recording method based on family's networking |
| CN110780618A (en) * | 2019-09-27 | 2020-02-11 | 江苏骥坤新能源工程有限公司 | Garbage classification processor and classification processing system |
| CN110861853A (en) * | 2019-11-29 | 2020-03-06 | 三峡大学 | Intelligent garbage classification method combining vision and touch |
| CN111661508A (en) * | 2020-06-12 | 2020-09-15 | 广东嘉源环境科技有限公司 | Intelligent garbage classification recycling device based on interaction of Internet and Internet of things |
| CN111992516A (en) * | 2020-08-19 | 2020-11-27 | 淮北速达医疗转运服务有限公司 | Intelligent garbage classification system |
| WO2021022475A1 (en) * | 2019-08-06 | 2021-02-11 | 中国长城科技集团股份有限公司 | Refuse disposal method and apparatus, and terminal device |
| CN112487044A (en) * | 2019-09-11 | 2021-03-12 | 珠海格力电器股份有限公司 | Target identification sorting method, device and storage medium |
| CN112722612A (en) * | 2020-12-25 | 2021-04-30 | 上海交通大学 | Garbage detection method and system based on YOLO network |
| CN113083732A (en) * | 2021-03-19 | 2021-07-09 | 浙江博城机器人科技有限公司 | Method for sorting large-size organic light objects in garbage by robot |
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| CN110276300A (en) * | 2019-06-24 | 2019-09-24 | 北京百度网讯科技有限公司 | The method and apparatus of rubbish quality for identification |
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| CN110321972A (en) * | 2019-07-22 | 2019-10-11 | 上海五赫自动化科技中心 | A kind of wet refuse classification acceptance test method and its realization device |
| CN110329672B (en) * | 2019-07-29 | 2022-04-15 | 北京绿博伟业环保科技有限责任公司 | Garbage classification device and classification method |
| CN110329672A (en) * | 2019-07-29 | 2019-10-15 | 北京绿博伟业环保科技有限责任公司 | A kind of garbage classification device and classification method |
| WO2021022475A1 (en) * | 2019-08-06 | 2021-02-11 | 中国长城科技集团股份有限公司 | Refuse disposal method and apparatus, and terminal device |
| CN110535734A (en) * | 2019-08-14 | 2019-12-03 | 六安智华工业自动化技术有限公司 | A kind of rubbish from cooking recording method based on family's networking |
| CN110487370A (en) * | 2019-08-14 | 2019-11-22 | 六安智华工业自动化技术有限公司 | A kind of device recording household kitchen wastes |
| CN112487044A (en) * | 2019-09-11 | 2021-03-12 | 珠海格力电器股份有限公司 | Target identification sorting method, device and storage medium |
| CN110780618A (en) * | 2019-09-27 | 2020-02-11 | 江苏骥坤新能源工程有限公司 | Garbage classification processor and classification processing system |
| CN110861853A (en) * | 2019-11-29 | 2020-03-06 | 三峡大学 | Intelligent garbage classification method combining vision and touch |
| CN110861853B (en) * | 2019-11-29 | 2021-10-19 | 三峡大学 | Intelligent garbage classification method combining vision and touch |
| CN111661508A (en) * | 2020-06-12 | 2020-09-15 | 广东嘉源环境科技有限公司 | Intelligent garbage classification recycling device based on interaction of Internet and Internet of things |
| CN111992516A (en) * | 2020-08-19 | 2020-11-27 | 淮北速达医疗转运服务有限公司 | Intelligent garbage classification system |
| CN112722612A (en) * | 2020-12-25 | 2021-04-30 | 上海交通大学 | Garbage detection method and system based on YOLO network |
| CN113083732A (en) * | 2021-03-19 | 2021-07-09 | 浙江博城机器人科技有限公司 | Method for sorting large-size organic light objects in garbage by robot |
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Application publication date: 20181123 |