CN111402878A - Garbage classification intelligent education machine system - Google Patents
Garbage classification intelligent education machine system Download PDFInfo
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- CN111402878A CN111402878A CN202010194673.0A CN202010194673A CN111402878A CN 111402878 A CN111402878 A CN 111402878A CN 202010194673 A CN202010194673 A CN 202010194673A CN 111402878 A CN111402878 A CN 111402878A
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Abstract
The invention provides a garbage classification intelligent education machine system which comprises an on-site intelligent machine device and a remote server terminal, wherein the on-site intelligent machine device comprises a video monitoring acquisition device, a voice interaction device, a human body sensing device, a light sensing device, an illuminating device, a control device, a network transmission device and a data storage device. This smart machine sets up by school's garbage bin or special teaching culture point etc. ground, through with the student between action, the interdynamic between the pronunciation, cultivates the habit and nurses.
Description
Technical Field
The invention relates to the technical field of garbage classification and treatment, in particular to an intelligent garbage classification education machine system.
Background
With the most severe policy of garbage classification in history implemented in Shanghai, Shanghai people have to make garbage classified souls copy each day. However, garbage classification is a custom development, and there is no way to maintain the classification for a long time by strict regulation and supervision alone, and studies show that the time required for consolidating the classification behavior of residents varies from 6 months to 2 years. Garbage classification is obviously a process that is easy to regain moisture and requires repeated consolidation.
Japan has been afflicted with waste classification as early as the eighties of the last century, which has established a nearly rigorous system of waste classification. The garbage classification is fine, garbage bags are made, different garbage throwing methods are different, specific time and place are provided for garbage throwing, government publicity is in place, the treatment process is complete, people have strong consciousness and the like, and the characteristics of clear garbage classification are provided.
Roman was not built a day and japanese garbage classification was not done all at once. The Japanese garbage classification is the core of grasping habit formation, environment-friendly education is implemented in primary and secondary schools, Japanese residents learn garbage classification from kindergartens through school education and family language teaching, the garbage classification habit formation is cultivated, the primary schools establish special social disciplines, and classified recovery of garbage factories is visited.
Germany is also one of the most perfect countries of environmental protection education, and the garbage classification is written into a primary school textbook and repeatedly educated in class, so that students can directly participate in experiencing the garbage classification in similar activities such as school class taking, mobile teaching and the like.
Therefore, how to classify garbage is through the education industry, and the cultivation of the garbage classification habit of Chinese people from childhood is the basis for realizing the classification of the garbage of all people. Based on the above, the invention provides the intelligent garbage classification education machine for schools and kindergartens, which realizes interaction with teenagers, infuses garbage classification knowledge and cultivates habits through behavior recognition and voice interaction technologies.
Technical scheme
The invention provides a garbage classification intelligent education machine system, which is characterized in that intelligent equipment is arranged beside a school garbage can or at a special teaching culture point and the like, and culture habits are developed through the interaction between behaviors and voices of students.
Based on the above, the invention provides a garbage classification intelligent education machine system, which comprises on-site intelligent machine equipment and a remote server terminal, wherein the on-site intelligent machine equipment comprises video monitoring acquisition equipment, voice interaction equipment, human body sensing equipment, light sensing equipment, lighting equipment, control equipment, network transmission equipment and data storage equipment.
In one embodiment of the invention, the light sensing device in the intelligent education device detects the light intensity information of a scene needing to be video-collected in the current environment, compares the obtained light intensity information with a preset video-collected light threshold range, and controls the lighting device to adjust the lighting brightness to reach the light threshold range by the control device if the obtained light intensity information is lower than the light threshold range.
In one embodiment of the invention, the garbage classification teaching is realized by adopting the following method,
the device is started, after the human body sensing device senses learning, information is fed back to the remote server terminal, the remote server terminal transmits an instruction to the control device, the lighting device is started, the voice interaction device plays welcome or suggestive audio information, meanwhile, the light sensing device collects light intensity information and feeds the light intensity information back to the local control device, the local control device compares the light intensity information with an optimal light threshold range of video information collection stored in the local storage device, the control device controls the light intensity of the lighting device, the light intensity information is collected again, and when the threshold range is met, the light intensity is not adjusted;
voice prompt, wherein the students can shout preset awakening words stored on local equipment, voice instruction information of the students is collected and recognized by the voice interaction equipment, and the interaction requirements of garbage classification education are determined and a garbage classification teaching mode is started after judgment;
the teaching of the classification of the garbage,
when the voice interaction device collects voice problem information provided by students and displays junk problem information for a real object in a database, for example, "what is junk? The voice information is transmitted to a remote server terminal, a feedback control device controls a video monitoring acquisition device to acquire the image information of the garbage displayed by the student, the image information is transmitted to the remote server terminal, image recognition and comparison are carried out through a garbage classification database of the remote server terminal, and a comparison result is broadcasted to the student through a voice interaction device;
when the voice interaction device collects voice question information provided by students as pure knowledge question-answer question words in a database, for example, "what garbage a battery belongs to? And transmitting the voice information to a remote server terminal, retrieving the information in the database to obtain an answer, and controlling a loudspeaker in the voice interaction equipment to play a garbage classification answer by the feedback control equipment.
In one embodiment of the invention, the garbage classification interactive test is realized by adopting the following method,
the voice interaction equipment collects voice information or action information provided by students, when the information in a remote server terminal database is met, an interaction test link is prompted, if 'I want to test', the remote server terminal feedback control equipment controls the video monitoring collection equipment to collect garbage image information displayed by the students, the video monitoring collection equipment captures behavior information thrown into a garbage can by the students, the behavior information is fed back to the remote server terminal, whether a test result of the students is correct is judged, a judgment conclusion is played through a loudspeaker in the voice interaction equipment, and if the answer is incorrect, correct answers and answer analysis can be played through the loudspeaker in the voice interaction equipment.
In one embodiment of the invention, the behavior analysis and deep learning of the garbage delivery students are realized by adopting an artificial intelligence behavior recognition algorithm of deep learning.
In one embodiment of the invention, the edge computing technology is adopted to realize local behavior recognition and remote deep learning.
In one embodiment of the invention, the remote server terminal is provided with an artificial intelligence behavior recognition algorithm for deep learning, after the video monitoring acquisition equipment acquires video data, the video data is transmitted to the remote server terminal through the network transmission equipment, the behavior characteristics of the video data are compared and analyzed, the characteristics of identity information, garbage throwing quantity, garbage classification throwing behavior and the like of participants are recognized in real time, and the remote server terminal summarizes, summarizes and displays the result as an important reference index for evaluating the development of the garbage classification habit of students.
In one embodiment of the invention, the field intelligent machine device further comprises a video data analysis device.
In one embodiment of the invention, the video data analysis device is used for analyzing the captured image information and video information on site, and an artificial intelligence behavior recognition algorithm of deep learning is adopted, after the video monitoring and collecting device collects the video data, the video data analysis device performs behavior characteristic comparison analysis on the video data, identifies the identity information, the garbage throwing quantity, the garbage classification throwing behavior and other characteristics of the participators in real time, transmits the identification result to the remote server terminal through the network transmission device, and the remote server terminal analyzes, summarizes and displays the result as an important reference index for evaluating the garbage classification management.
Advantageous effects
This smart machine sets up by school's garbage bin or special teaching culture point etc. ground, through with the student between action, the interdynamic between the pronunciation, cultivates the habit and nurses.
Drawings
FIG. 1 is a schematic diagram of the intelligent education system for garbage classification provided by the present invention;
FIG. 2 is a schematic diagram of a field intelligent machine device of the intelligent education system for garbage classification provided by the present invention;
FIG. 3 is an exploded view of the intelligent machine device on site of the intelligent education system for garbage classification provided by the present invention;
FIG. 4 is a flow chart of light adjustment for the intelligent on-site machine of the intelligent education system for garbage classification according to the present invention.
FIG. 5 is a flow chart of a garbage classification teaching using the system of the present invention;
FIG. 6 is a flow chart of a garbage classification test using the system of the present invention;
FIG. 7 is a schematic diagram of garbage classification monitoring and habit formation by using the system of the present invention.
Detailed Description
The invention provides a garbage classification intelligent education machine system which comprises an on-site intelligent machine device and a remote server terminal, wherein the on-site intelligent machine device comprises a video monitoring acquisition device, a voice interaction device, a human body sensing device, a light sensing device, a lighting device, a control device, a network transmission device and a data storage device.
When the video monitoring and collecting equipment is used for recording the behavior process of personnel, the biggest difficulty is that the video equipment is difficult to accurately acquire behavior identification information under the condition of very dark light. The light sensing equipment in the intelligent education equipment detects the light intensity information of a scene needing to be subjected to video acquisition in the current environment, compares the obtained light intensity information with a preset video acquisition light threshold range, and controls the lighting equipment to adjust the lighting brightness to reach the light threshold range if the obtained light intensity information is lower than the light threshold range. The intelligent education machine system for garbage classification provided by the invention can realize data acquisition under the optimal light of the image monitoring and acquisition equipment no matter under the illumination of any environment.
The light sensing device is a light sensor.
The network transmission mode can be 4G, Wifi, 5G, network cable and optical fiber.
The network transmission device used for implementing the network transmission mode can be a hub, a switch, a bridge, a router, a modem, a fiber transceiver, an optical cable and the like.
The intelligent teaching machine is designed into a magic cube structure, the number of n is selected according to the garbage classification types of different cities, the lighting device adopts an L ED light source, the lighting power of the whole lighting device is between 20W and 30W, and after testing, the intelligent teaching machine for garbage classification is generally arranged at a height of between 2.5 and 3.5 meters based on the limitation of application scenes, and in the height range, when the lighting power of a light source exceeds 30W, dazzling feeling and uncomfortable feeling are caused.
The center position of the on-site intelligent machine equipment is a shell main body, a pickup device and a control device in a video monitoring assembly, a human body induction device and a voice interaction device are arranged in the shell main body, and intelligent sound boxes in a lighting device and the voice interaction device are arranged at n corners.
The lighting device comprises an L ED light source, a light source plate and a diffusion plate, wherein the diffusion plate is designed to be frosted, the light source plate is used for attaching a fixed light source, and the light source plate is arranged at the bottom of four corners of the shell.
The video monitoring and collecting device comprises a camera monitoring fixing plate and a camera, and the camera is fixed on the camera monitoring fixing plate. The camera is preferably an infrared dome network camera. When the video monitoring and collecting equipment is used, the starting state is kept for 24 hours, and monitoring and management are carried out in real time.
Intelligent audio amplifier among the voice interaction equipment includes loudspeaker, horn cover and waterproof sound-transmitting membrane, the horn cover is installed in the side of shell, is provided with waterproof sound-transmitting membrane between horn cover and the loudspeaker for avoid loudspeaker to intake.
The sound pickup device in the voice interaction device is a microphone or a microphone array.
And 1-2 personal induction devices and 1 light induction device are arranged on a bottom cover plate of a shell of the intelligent machine device on site, and 1 projection device is arranged at each corner of the n-corner magic cube.
The pickup equipment is installed on the bottom cover plate.
A round hole is formed in the middle of the bottom cover plate, the camera penetrates through the round hole, supports are arranged on two sides of the cover plate, and the camera fixing plate is fixed on the supports.
The control driving component comprises two drivers and a control main board, wherein one is L ED constant current driver for supplying power to the light source, and the other is constant voltage power driver for supplying power to the video monitoring acquisition equipment, the voice interaction equipment and the control main board.
The control driving assembly is fixed through a metal frame, and the metal frame is fixed on the inner wall of the shell.
Adopt this intelligent machine system to carry out student's waste classification knowledge education and teaching, install in classroom, school's corridor or special education and training space:
the device is started, after the human body sensing device senses learning, information is fed back to the remote server terminal, the remote server terminal transmits an instruction to the control device, the lighting device is started, the voice interaction device plays welcome or suggestive audio information, meanwhile, the light sensing device collects light intensity information and feeds the light intensity information back to the local control device, the local control device compares the light intensity information with an optimal light threshold range of video information collection stored in the local storage device, the control device controls the light intensity of the lighting device, the light intensity information is collected again, and when the threshold range is met, the light intensity is not adjusted;
voice prompt, wherein the students can shout preset awakening words stored on local equipment, voice instruction information of the students is collected and recognized by the voice interaction equipment, and the interaction requirements of garbage classification education are determined and a garbage classification teaching mode is started after judgment;
the teaching of the classification of the garbage,
when the voice interaction device collects voice problem information provided by students and displays junk problem information for a real object in a database, for example, "what is junk? The voice information is transmitted to a remote server terminal, a feedback control device controls a video monitoring acquisition device to acquire the image information of the garbage displayed by the student, the image information is transmitted to the remote server terminal, image recognition and comparison are carried out through a garbage classification database of the remote server terminal, and a comparison result is broadcasted to the student through a voice interaction device;
when the voice interaction device collects voice question information provided by students as pure knowledge question-answer question words in a database, for example, "what garbage a battery belongs to? Sending voice information to a remote server terminal, retrieving information in a database to obtain an answer, and controlling a loudspeaker in voice interaction equipment to play a garbage classification answer by feedback control equipment;
the garbage classification interactive test is carried out,
the voice interaction equipment collects voice information or action information provided by students, when the information in a remote server terminal database is met, an interaction test link is prompted, if 'I want to test', the remote server terminal feedback control equipment controls the video monitoring collection equipment to collect garbage image information displayed by the students, the video monitoring collection equipment captures behavior information thrown into a garbage can by the students, the behavior information is fed back to the remote server terminal, whether a test result of the students is correct is judged, a judgment conclusion is played through a loudspeaker in the voice interaction equipment, and if the answer is incorrect, correct answers and answer analysis can be played through the loudspeaker in the voice interaction equipment.
This intelligent machine system also can realize that student's waste classification custom is formed, installs this intelligent machine system by the garbage bin of school, utilizes the artificial intelligence action recognition algorithm of degree of depth study, constructs the action storehouse for the individual, knows the student and throws away rubbish action custom, in time corrects.
The intelligent education machine system for garbage classification provided by the invention can realize on-site rapid behavior recognition analysis and deep learning of the remote server terminal by means of edge calculation, and can also directly realize behavior recognition analysis and deep learning at the remote server terminal without adopting edge calculation.
For the situation that behavior recognition and deep learning are directly carried out by adopting a remote server terminal, the remote server terminal is provided with an artificial intelligence behavior recognition algorithm for deep learning, video monitoring and collecting equipment transmits video data to the remote server terminal through network transmission equipment after collecting the video data, behavior characteristic comparison analysis is carried out on the video data, characteristics such as identity information of participants, garbage throwing quantity, garbage classification throwing behaviors and the like are recognized in real time, and the remote server terminal sums up, summarizes and displays results and serves as an important reference index for evaluating the maintenance of garbage classification habits of students.
The method has the defect that the participators and the garbage throwing behavior thereof can not be quickly and accurately identified in any application scene, so that the method also selects the means of edge calculation to realize on-site quick behavior identification analysis and deep learning of the remote server terminal, thereby solving the defects existing in behavior identification and deep learning by adopting a single remote server terminal.
In this case, a video data analysis device is also included in the field intelligent machine device.
When behavior recognition analysis is performed by using video data analysis equipment, the biggest difficulty is how to quickly and accurately recognize the participants and the garbage throwing behaviors thereof. The invention adopts the means of edge calculation, and installs the data storage device and the video data analysis device in the field intelligent machine device, the data storage device can store the image information and the video information captured by the video monitoring in a short time, generally stores the data for 3-5 days, and the long-term storage of the data still needs to be stored in the remote server terminal database.
The video data analysis equipment is used for analyzing captured image information and video information on site, a deep learning artificial intelligence behavior recognition algorithm is adopted, after the video monitoring and acquisition equipment acquires video data, the video data analysis equipment performs behavior characteristic comparison analysis on the video data, identifies characteristics of identity information, garbage throwing quantity, garbage classification throwing behaviors and the like of participators in real time, transmits the identification result to the remote server terminal through the network transmission equipment, and the remote server terminal analyzes, summarizes and displays the result to serve as an important reference index for evaluating garbage classification management.
The specific method for cultivating the behavior habit is as follows:
the equipment is started, after the human body sensing equipment senses a student who falls rubbish before, information is fed back to the remote server terminal, the remote server terminal transmits an instruction to the control equipment, the lighting equipment and the voice interaction equipment are started, meanwhile, the light sensing equipment collects light intensity information and feeds the light intensity information back to the local control equipment, the local control equipment compares the light intensity information with an optimal light threshold value range of video information collection stored in the local storage equipment, the control equipment controls the light intensity of the lighting equipment, the light intensity information is collected again, and when the threshold value range is met, the light intensity is not adjusted;
the video monitoring and collecting device collects image information of students, an artificial intelligence behavior recognition algorithm of deep learning is adopted, behavior characteristic analysis and comparison are carried out on video data through a remote server terminal or a video data analysis device of an edge calculation base number, identity information, garbage throwing quantity and garbage classification throwing behaviors of participants are recognized in real time and transmitted to a database of the remote server terminal, a behavior recognition data packet of a single student is constructed, the remote server terminal sums up results, the garbage throwing behavior habits of the student are counted, the results are hooked with the credits of the student, and the habit of the student in garbage classification cultivation is supervised.
The following embodiments are described in detail to solve the technical problems by applying technical means to the present invention, and the implementation process of achieving the technical effects can be fully understood and implemented.
Example 1
Fig. 1 shows a garbage classification intelligent education machine system, which includes a field intelligent machine device and a remote server terminal, wherein the field intelligent machine device includes a video monitoring and collecting device, a voice interaction device, a human body sensing device, a light sensing device, a lighting device, a control device, a network transmission device and a data storage device.
Fig. 2 to 3 show the structure of the on-site intelligent machine equipment of the intelligent education system for garbage classification provided by the present invention, which adopts a 4-corner magic cube structure, and four corners are designed to be prismatic structures.
The angle of prismatic structure contains components of a whole that can function independently lid 1, shell and built-in lighting apparatus, the mutual equipment of pronunciation wherein, and the loudspeaker lid 3 of the intelligent audio amplifier of the mutual equipment of pronunciation sets up on the lateral wall of shell, and loudspeaker 7 is connected with loudspeaker lid 3, sets up waterproof sound-transmitting membrane 6 between the two, and built-in L ED light source is fixed on light source board 2, and the bottom of shell is provided with diffuser plate 5.
The central part of the shell is internally provided with a control device 8, and the control device 8 is fixed on the inner wall of the shell through a metal frame. The bottom of the shell is provided with a cover plate 12, the supports at two sides of the cover plate 12 support a camera monitoring fixing plate 9, and the fixing plate is used for fixing a camera 10. A human body sensor 13, a light sensor 14 and a microphone 11 are further provided on the cover plate 12.
Example 2
Fig. 4 shows the process of the field intelligent machine device of the present invention to adjust the camera 10 to collect image and video information through the light sensor and the lighting device. The light sensor 14 collects light intensity information and feeds the light intensity information back to the local control device 8, the local control device 8 compares the light intensity information with an optimal light threshold range of video information collection stored in a local storage device arranged in the camera, then the control device controls the light intensity of the lighting device, collects the light intensity information again, and collects images and video information when the threshold range is met.
Example 3
As shown in fig. 5, garbage classification tutoring: after the human body sensing device senses learning, information is fed back to the remote server terminal, the remote server terminal transmits an instruction to the control device, the lighting device and the voice interaction device are started, welcome or prompting audio information is played, meanwhile, the light sensing device collects light intensity information and feeds the light intensity information back to the local control device, the local control device compares the light intensity information with an optimal light threshold value range of video information collection stored in the local storage device, the control device controls the light intensity of the lighting device, the light intensity information is collected again, and when the threshold value range is met, the light intensity is not adjusted;
the students can shout preset awakening words stored on the local equipment, the voice interaction equipment collects and identifies voice instruction information of the students, and after judgment, the interaction requirements of garbage classification education are determined, and a garbage classification teaching mode is started;
when the voice interaction device collects voice problem information provided by students and displays junk problem information for a real object in a database, for example, "what is junk? The voice information is transmitted to a remote server terminal, a feedback control device controls a video monitoring acquisition device to acquire the image information of the garbage displayed by the student, the image information is transmitted to the remote server terminal, image recognition and comparison are carried out through a garbage classification database of the remote server terminal, and a comparison result is broadcasted to the student through a voice interaction device;
when the voice interaction device collects voice question information provided by students as pure knowledge question-answer question words in a database, for example, "what garbage a battery belongs to? And transmitting the voice information to a remote server terminal, retrieving the information in the database to obtain an answer, and controlling a loudspeaker in the voice interaction equipment to play a garbage classification answer by the feedback control equipment.
Example 4
As shown in fig. 6, the garbage classification test: after the human body sensing device senses learning, information is fed back to the remote server terminal, the remote server terminal transmits an instruction to the control device, the lighting device and the voice interaction device are started, welcome or prompting audio information is played, meanwhile, the light sensing device collects light intensity information and feeds the light intensity information back to the local control device, the local control device compares the light intensity information with an optimal light threshold value range of video information collection stored in the local storage device, the control device controls the light intensity of the lighting device, the light intensity information is collected again, and when the threshold value range is met, the light intensity is not adjusted;
the voice interaction equipment collects voice information or action information provided by students, when the information in a remote server terminal database is met, an interaction test link is prompted, if 'I want to test', the remote server terminal feedback control equipment controls the video monitoring collection equipment to collect garbage image information displayed by the students, the video monitoring collection equipment captures behavior information of the students thrown into a garbage can, the behavior information is fed back to the remote server terminal, whether the test result of the students is correct or not is judged, if the test result is incorrect, correct answers are broadcast through a loudspeaker in the voice interaction equipment.
Example 5
The deep learning habit of the remote server terminal is developed as follows:
when a human body sensing device senses a student who falls garbage, information is fed back to a remote server terminal, the remote server terminal transmits an instruction to a control device, a lighting device and a voice interaction device are started, meanwhile, light sensing devices collect light intensity information and feed the light intensity information back to a local control device, the local control device compares the light intensity information with an optimal light threshold value range of video information collection stored in a local storage device, the control device controls the light intensity of the lighting device, the light intensity information is collected again, and when the threshold value range is met, the light intensity is not adjusted;
the video monitoring and collecting device collects image information of students, an artificial intelligence behavior recognition algorithm of deep learning is adopted, behavior characteristic analysis and comparison are carried out on video data through the remote server terminal, identity information, garbage throwing quantity and garbage classification throwing behaviors of participants are recognized in real time and are transmitted to a database of the remote server terminal, a behavior recognition data packet of a single student is constructed, the remote server terminal sums up results, the garbage throwing behavior habit of the student is counted, the results are hooked with the credit of the student, and the habit of supervising the student to cultivate garbage classification is developed.
Example 6
Adopting the edge computing technology to carry out behavior recognition analysis locally, and developing the remote deep learning habit:
in this case, a video data analysis device is also included in the field intelligent machine device.
As shown in fig. 7, after the human body sensing device senses a student who falls garbage, the information is fed back to the remote server terminal, the remote server terminal transmits an instruction to the control device, the lighting device and the voice interaction device are started, meanwhile, the light sensing device collects light intensity information and feeds the light intensity information back to the local control device, the local control device compares the light intensity information with an optimal light threshold range of video information collection stored in the local storage device, the control device controls the light intensity of the lighting device, the light intensity information is collected again, and when the threshold range is met, the light intensity is not adjusted again;
the video monitoring and collecting device collects image information of students, an artificial intelligence behavior recognition algorithm of deep learning is adopted, local video data analysis equipment adopting an edge computing technology carries out behavior characteristic analysis and comparison on video data, identity information, garbage throwing quantity and garbage classification throwing behaviors of participants are recognized in real time and transmitted to a database of a remote server terminal, a behavior recognition data packet of a single student is constructed, the remote server terminal sums up results, the garbage throwing behavior habit of the student is counted, the results are hooked with the student credit score, and the habit of the student in garbage classification cultivation is supervised.
All of the above mentioned intellectual property rights are not intended to be restrictive to other forms of implementing the new and/or new products. Those skilled in the art will take advantage of this important information, and the foregoing will be modified to achieve similar performance. However, all modifications or alterations are based on the new products of the invention and belong to the reserved rights.
The foregoing is directed to preferred embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow. However, any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present invention are within the protection scope of the technical solution of the present invention.
Claims (9)
1. The utility model provides a rubbish classification intelligence education machine system which characterized in that: the intelligent on-site machine comprises on-site intelligent machine equipment and a remote server terminal, wherein the on-site intelligent machine equipment comprises video monitoring and collecting equipment, voice interaction equipment, human body sensing equipment, light sensing equipment, lighting equipment, control equipment, network transmission equipment and data storage equipment.
2. The intelligent educational machine system for garbage classification of claim 1, wherein: light sensing equipment in the intelligent education equipment detects the light intensity information of a scene needing to be subjected to video acquisition in the current environment, the obtained light intensity information is compared with a preset video acquisition light threshold range, and if the obtained light intensity information is lower than the light threshold range, the control equipment controls the lighting equipment to adjust the lighting brightness to reach the light threshold range.
3. The intelligent educational machine system for garbage classification of claim 1 or 2, wherein: the garbage classification teaching is realized by adopting the following method,
the device is started, after the human body sensing device senses learning, information is fed back to the remote server terminal, the remote server terminal transmits an instruction to the control device, the lighting device and the voice interaction device are started, welcome or suggestive audio information is played, meanwhile, the light sensing device collects light intensity information and feeds the light intensity information back to the local control device, the local control device compares the light intensity information with an optimal light threshold range of video information collection stored in the local storage device, the control device controls the light intensity of the lighting device, the light intensity information is collected again, and when the threshold range is met, the light intensity is not adjusted;
voice prompt, wherein the students can shout preset awakening words stored on local equipment, voice instruction information of the students is collected and recognized by the voice interaction equipment, and the interaction requirements of garbage classification education are determined and a garbage classification teaching mode is started after judgment;
the teaching of the classification of the garbage,
when the voice interaction device collects voice problem information provided by students and displays junk problem information for a real object in a database, for example, "what is junk? The voice information is transmitted to a remote server terminal, a feedback control device controls a video monitoring acquisition device to acquire the image information of the garbage displayed by the student, the image information is transmitted to the remote server terminal, image recognition and comparison are carried out through a garbage classification database of the remote server terminal, and a comparison result is broadcasted to the student through a voice interaction device;
when the voice interaction device collects voice question information provided by students as pure knowledge question-answer question words in a database, for example, "what garbage a battery belongs to? And transmitting the voice information to a remote server terminal, retrieving the information in the database to obtain an answer, and controlling a loudspeaker in the voice interaction equipment to play a garbage classification answer by the feedback control equipment.
4. The intelligent educational machine system for garbage classification of claim 1 or 2, wherein: the garbage classification interactive test is realized by adopting the following method,
the voice interaction equipment collects voice information or action information provided by students, when the information in a remote server terminal database is met, an interaction test link is prompted, if 'I want to test', the remote server terminal feedback control equipment controls the video monitoring collection equipment to collect garbage image information displayed by the students, the video monitoring collection equipment captures behavior information thrown into a garbage can by the students, the behavior information is fed back to the remote server terminal, whether a test result of the students is correct is judged, a judgment conclusion is played through a loudspeaker in the voice interaction equipment, and if the answer is incorrect, correct answers and answer analysis can be played through the loudspeaker in the voice interaction equipment.
5. The intelligent educational machine system for garbage classification of claim 1 or 2, wherein: and adopting an artificial intelligent behavior recognition algorithm of deep learning to realize behavior analysis and deep learning of the garbage delivery personnel.
6. The intelligent educational machine system for garbage classification of claim 1 or 2, wherein: and local behavior recognition and remote deep learning are realized by adopting an edge computing technology.
7. The intelligent educational machine system for garbage classification of claim 1 or 2, wherein: the remote server terminal is provided with an artificial intelligence behavior recognition algorithm for deep learning, after video data are collected by the video monitoring and collecting device, the video data are transmitted to the remote server terminal through the network transmission device, behavior characteristic comparison analysis is carried out on the video data, characteristics such as identity information of participants, garbage throwing quantity, garbage classification throwing behaviors and the like are recognized in real time, and the remote server terminal sums up, summarizes and displays results and serves as an important reference index for evaluating the development of garbage classification habits of students.
8. The intelligent educational machine system for garbage classification of claim 1 or 2, wherein: the intelligent field machine equipment also comprises video data analysis equipment.
9. The intelligent educational machine system for garbage classification of claim 8, wherein: the video data analysis equipment is used for analyzing captured image information and video information on site, a deep learning artificial intelligence behavior recognition algorithm is adopted, after the video monitoring and acquisition equipment acquires video data, the video data analysis equipment performs behavior characteristic comparison analysis on the video data, identifies characteristics of identity information, garbage throwing quantity, garbage classification throwing behaviors and the like of participators in real time, transmits the identification result to the remote server terminal through the network transmission equipment, and the remote server terminal sums up, summarizes and displays the result to serve as an important reference index for evaluating garbage classification management.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111814757A (en) * | 2020-08-20 | 2020-10-23 | 许昌学院 | Garbage classification simulation system based on computer software |
| CN112037605A (en) * | 2020-10-20 | 2020-12-04 | 广州市萌酷信息科技有限责任公司 | Information technology consultation terminal based on big data analysis |
| CN112597804A (en) * | 2020-11-27 | 2021-04-02 | 上海阅目环境科技有限公司 | Voice prompt and video image supervision method for garbage classification delivery site |
| CN113421473A (en) * | 2021-07-05 | 2021-09-21 | 赛飞特工程技术集团有限公司 | Talent training system and method based on VR and AR technologies |
-
2020
- 2020-03-19 CN CN202010194673.0A patent/CN111402878A/en not_active Withdrawn
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111814757A (en) * | 2020-08-20 | 2020-10-23 | 许昌学院 | Garbage classification simulation system based on computer software |
| CN111814757B (en) * | 2020-08-20 | 2024-01-09 | 许昌学院 | Garbage classification simulation system based on computer software |
| CN112037605A (en) * | 2020-10-20 | 2020-12-04 | 广州市萌酷信息科技有限责任公司 | Information technology consultation terminal based on big data analysis |
| CN112597804A (en) * | 2020-11-27 | 2021-04-02 | 上海阅目环境科技有限公司 | Voice prompt and video image supervision method for garbage classification delivery site |
| CN113421473A (en) * | 2021-07-05 | 2021-09-21 | 赛飞特工程技术集团有限公司 | Talent training system and method based on VR and AR technologies |
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