CN111680927A - AI artificial intelligence training device and training method thereof - Google Patents
AI artificial intelligence training device and training method thereof Download PDFInfo
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Abstract
The invention discloses an AI artificial intelligence training device and a training method thereof, which particularly designs the technical field of AI artificial intelligence control. The system has simple and easy-to-operate system functions, the system is rich and flexible to debug, and the product is easy to update, maintain and use. The technical principle of the training device is as follows: IOT (input output) synopsis data acquisition, which takes 5G communication as a channel, transmits the sensing data to a training device for cloud computing processing, and realizes artificial intelligence understanding and judgment. That is, the actual sensor is connected to the training device, and the data source generated by the actual sensor controls the operation of the equipment in the simulation scene of the training device, so as to generate the associated real-time dynamic effect.
Description
Technical Field
The invention belongs to the technical field of Artificial Intelligence (AI), and particularly relates to an AI artificial intelligence training device and a training method thereof.
Background
The new technology is fast to update, the commonly used hardware training device consumes much expenses and is not beneficial to updating, and the training mode is also innovative under the background of a new era, so that the AI artificial intelligence training device is independently researched and developed. Compared with the traditional development platform, the AI artificial intelligence training device has the following advantages: the system can provide a plurality of common industry application scenes in life for students, the students can build artificial intelligence projects in each scene, the building process of the artificial intelligence is further deeply understood on the whole, and the platform is used for carrying out professional experiments, professional practice, project teaching, graduation design and the like.
Disclosure of Invention
The invention aims to solve the technical problem of providing an AI artificial intelligence training device and a training method thereof aiming at the defects of the background technology, wherein an actual sensor is accessed into the training device, and the operation of equipment in a simulation scene of the training device is controlled through a data source generated by the real sensor, so that a relevant real-time dynamic effect is generated.
The invention adopts the following technical scheme for solving the technical problems:
an AI artificial intelligence training device comprises a planning budget module, a system installation module, a system debugging module and a client creating development module;
the planning budget module comprises project planning and budget and is used for seeking for allocating resources, analyzing equipment, tools and materials used in the process of the artificial intelligent project and further selecting a scheme to complete project planning;
the system installation module is used for selecting a corresponding specific scene in the selected artificial intelligence project to install equipment according to the selected artificial intelligence project;
the system debugging module is used for simulating all equipment at the cloud-pipe-end of the artificial intelligent system, and further can freely control various execution equipment through the integrated controller;
and the system installation module and the system debugging module are combined with the sensor equipment and the AI intelligent equipment to simulate industry AI information logic, strategies and forms and perform industry innovation development and AI industry development, so that strategy big data analysis and AI understanding, expert system intelligent control execution and cloud + big data whole-process analysis and monitoring are realized.
As a further preferable scheme of the AI artificial intelligence training apparatus of the present invention, the system installation includes scene selection, equipment installation, cable connection, and VR operation;
the scene selection is used for selecting to enter a specific application scene for installing related artificial intelligence equipment according to various real and visual 3D application scenes provided by the AI artificial intelligence training device;
the equipment installation is used for selecting the functional area according to the selected scene, and installing corresponding artificial intelligence equipment in the corresponding functional area, wherein the equipment comprises a sensor module, a transmission module, a gateway module, communication equipment, a cloud server and an application terminal; selecting relevant equipment to be installed from the equipment part, and directly dragging the equipment to a corresponding position;
the cable connection is used for selecting a corresponding cable to carry out equipment connection and comprises various wireless communication cables such as a control bus, a serial bus, WIFI (wireless fidelity), GPRS (general packet radio service), Bluetooth, Zigbee, UWB (ultra wideband) and NFC (near field communication);
VR operation for physically roaming around its place in the scene by wearing a VR helmet.
As a further preferred scheme of the AI artificial intelligence training apparatus of the present invention, the system debugging includes centralized network management, data configuration, data signal generation, device control, device operation protocol alarm;
the system comprises a centralized network manager, a control layer, a transmission layer, a gateway layer, a communication layer, a service layer and a terminal layer, wherein the centralized network manager is used as the centralized network manager of the artificial intelligent equipment and supports direct synchronous equipment installation, all the equipment is synchronously online, and an artificial intelligent 7-layer structure is automatically generated and comprises a sensing layer, a control layer, a transmission layer, a gateway layer, a communication layer, a service layer and a terminal layer, so that data configuration and management can be conveniently carried out on each module;
the data configuration is used for selecting a right key of the single device, and can see the operation of the single device, including starting, stopping the device, deleting the device, importing an export script and configuring related data operation; the method comprises the following specific steps:
generating data signals, setting corresponding parameter data according to time and a mathematical model mode, and freely controlling various agricultural production execution devices through an integrated controller;
the device control comprises the steps that the device is in an automatic function control process through a data input function, the device is in intelligent control through an intelligent control algorithm arranged at a cloud end, a cruising circuit of the unmanned aerial vehicle device can be directly controlled through the cloud end, and a monitoring visual angle of the device is controlled;
the equipment runs, the running information of the relevant executing mechanism is checked through the background management system, the system state information and the A/D and D/A conversion process are checked through the operation of the relevant equipment, and relevant learning is carried out;
protocol alarms, including
The alarm of single equipment, the relevant alarm information can be viewed in the data configuration part of the single equipment, and then the operation, configuration and data modification are carried out according to the relevant alarm information;
and the in-system alarm comprises an alarm interface alarm between the equipment, and the butt joint data of the two ends of the equipment is modified according to the alarm.
As a further preferable scheme of the AI artificial intelligence training apparatus of the present invention, the system debugging specifically is as follows: by adopting a modular design, corresponding equipment is selected and called, the equipment is connected through the building of a cable platform, then the simulation debugging of the equipment is carried out, and the application scene of the artificial intelligent equipment is simulated through the generation of a data source, so that students can flexibly network in the platform and carry out project learning; comprises a heating system, a humidifying system, a spraying system, an illumination roller shutter and a fan; through analyzing and counting the collected and recorded sensing information of air temperature and humidity, soil temperature and humidity and illuminance, a sensing data change curve can be dynamically displayed, the sensing data is compared with a specified value, a control instruction is sent out when the sensing data exceeds the specified value, the spraying, ventilation, heating, humidification and rolling equipment is automatically controlled to work, after relevant parameter values in a greenhouse return to the specified value, a control platform can send a work stopping instruction to intelligent terminal equipment, and a user can also control the intelligent terminal equipment through a mobile phone.
As a further preferable scheme of the AI artificial intelligence training apparatus of the present invention, the creator development module is specifically as follows: according to a sensor data access interface, an application control interface and a big data analysis processing interface which provide standards, development sample programs, cases and source codes are provided for students to study, through a network + a general Json interface + a UDP/TCP protocol, by means of software and hardware platforms such as Android/Hongmon/Linux/AliOS and the like, new technical industry scene application is adopted, sensor equipment and AI intelligent equipment are combined, industry AI information logic, strategies and forms are simulated, industry innovation development and AI industry development are carried out, and therefore strategy big data analysis and AI understanding, expert system intelligent control execution and cloud + big data whole-process analysis and monitoring are achieved, wherein the new technology comprises 5G, cloud computing, big data, an internet of things and AI artificial intelligence.
As a further preferred scheme of the AI artificial intelligence training device, the AI artificial intelligence training device further comprises an examination system module, wherein the examination system module comprises three parts of report submission, online examination and score evaluation;
the report submitting module is used for automatically generating an experiment report by the system after the student completes the experiment, and the teacher can check the corresponding report at the management terminal after the completed experiment report is uploaded;
and the online examination is used in the AI artificial intelligence training device, teachers can make and upload theoretical questions as question banks and store the questions in the server, and the examination questions are issued to students during examination so as to take examinations on the students. After the students submit the answer sheets, the system can automatically score, and the scores are recorded into the teacher system.
Performance evaluation: the teacher can score and evaluate the comprehensive scores of the students by checking the reports and the online examination scores submitted by the students on the AI training device.
As a further preferable scheme of the AI artificial intelligence training device, the AI artificial intelligence training device further comprises a teaching management module, wherein the teaching management module is used for providing a management center for a management terminal, managing student accounts, adding, deleting and modifying account information, and logging in the student accounts to check experimental conditions.
A training method based on an AI artificial intelligence training device specifically comprises the following steps;
As a further preferable scheme of the training method based on the AI artificial intelligence training device of the present invention, the step 4 specifically includes the following steps:
step 4.1, designing environmental data: the AI artificial intelligence training device needs environmental data and growth condition data to carry out strategy design, combines a crop growth model, agricultural weather forecast, pest and disease monitoring and early warning and crop four-condition monitoring, provides production decision support by using big data statistical analysis, provides corresponding theoretical environmental data aiming at different seasons, carries out data design on the growth conditions of crops according to different growth periods, and comprises humiture, illuminance, soil fertility and carbon dioxide concentration required by growth;
step 4.2, environment monitoring: according to the weather change outside the greenhouse and the real-time information of the crop growth in the greenhouse, making corresponding protective measures, and keeping proper illumination supply and temperature and humidity control in the greenhouse;
and 4.3, automatic strategy generation: the automatic strategy mainly takes automatic control as a main part, corresponding parameter data including temperature, humidity and photosensitivity are set according to the time and mathematical model, various agricultural production execution devices can be freely controlled through the integrated controller, the automatic strategy comprises heating, humidifying, a spraying system, an illumination roller shutter and a fan, the collected and recorded sensing information is analyzed and counted, wherein the sensing information comprises air temperature and humidity, soil temperature and humidity and illumination intensity, a sensing data change curve can be dynamically displayed, the sensing data is compared with a specified value, a control instruction is sent out when the sensing data exceeds the specified value, the automatic control spraying, ventilating, heating, humidifying and roller shutter are automatically controlled to work, and when relevant parameter values in a greenhouse return to the specified value, a control platform can send out a work stop instruction to the intelligent terminal device.
And 4.4, equipment operation and control: in the operation process of the intelligent agriculture, the operation information of the relevant actuating mechanism can be checked through the background management system, the system state information and the A/D and D/A conversion process can be checked through operating relevant equipment, and relevant learning is carried out;
step 4.5, cloud control: after the system normally operates, the equipment can be in the automatic process of function control through the input function of data; the equipment is in intelligent control through an intelligent control algorithm arranged at the cloud end, the cruising line of the unmanned aerial vehicle equipment can be directly controlled through the cloud end, and the monitoring visual angle of the equipment is controlled;
step 4.6, protocol alarm: the operation process of the equipment can generate an alarm, and the alarm is divided into:
the alarm of the single device only needs to be seen in the data configuration part of the single device, and students operate, configure and modify data according to the relevant alarm information;
and the system internal alarm comprises an alarm interface alarm between the equipment, and the student modifies the butt data of the two ends according to the alarm.
As a further preferable scheme of the training method based on the AI artificial intelligence training device of the present invention, the AI artificial intelligence training device provides 3 data source generation modes: accurately generating data by a mathematical model, and importing the data by a real-time data acquisition and import system and a commercial system data interface;
the data source can be generated through a simulation data model provided in the platform, and supports: constant distribution, linear distribution, sinusoidal distribution, logarithmic distribution, exponential distribution, Gaussian normal distribution, sine distribution and Fourier series distribution, and students can flexibly call the model to generate required simulation data.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
1. the AI artificial intelligence training device provided by the invention has rich highly-simulated three-dimensional scenes, and is suitable for training in multiple industries such as intelligent agriculture, intelligent traffic, intelligent logistics, intelligent medical treatment, intelligent industry, intelligent safety, intelligent buildings and the like;
2. the system has simple and easy-to-operate system functions, the system is rich and flexible to debug, and the product is easy to update, maintain and use;
3. the technical principle of the training device is as follows: IOT (input output) synopsis data acquisition, which takes 5G communication as a channel, transmits the sensing data to a training device for cloud computing processing, and realizes artificial intelligence understanding and judgment;
4. the actual sensor is connected to the training device, and the operation of equipment in a simulation scene of the training device is controlled through a data source generated by the real sensor, so that a relevant real-time dynamic effect is generated.
Drawings
FIG. 1 is a schematic diagram of an artificial intelligence training device product architecture of the present invention;
FIG. 2 is a schematic diagram of an AI innovation development of the AI artificial intelligence training device industry of the present invention;
FIG. 3 is a schematic diagram of the artificial intelligence device model selection and budget of the present invention;
FIG. 4 is a schematic diagram illustrating the type selection and budget of consumables such as an actuator according to the present invention;
FIG. 5 is a schematic diagram of the total budget of the system of the present invention;
FIG. 6 is a schematic diagram of the present invention artificial intelligence simulation platform-system installation function;
FIG. 7 is a schematic illustration of the Artificial Intelligence research institute of the present invention;
FIG. 8 is a preview of actuator selection in accordance with the present invention;
FIG. 9 is a sensor type preview of the present invention;
FIG. 10 is a schematic diagram of the system installation scenario of the present invention;
FIG. 11 is a cable overview diagram of the present invention;
FIG. 12 is a schematic diagram of the wiring path of the apparatus of the present invention;
FIG. 13 is a schematic diagram of the logical process of debugging the system of the present invention;
FIG. 14 is a schematic view of a centralized grid management system of the present invention;
FIG. 15 is a data configuration GUI interface presentation schematic of the present invention;
FIG. 16 is a graphical representation of growth condition data according to the present invention;
FIG. 17 is a graphical illustration of environmental data trends of the present invention;
FIG. 18 is an overview of the environmental, real-time weather, actuator operating state information for the present invention;
FIG. 19 is a schematic view of a real-time weather data information overview of the present invention;
FIG. 20 is an overview of the environment information of the present invention;
FIG. 21 is a schematic view of the actuator operating condition of the present invention;
FIG. 22 is a schematic view of the operation of the sensor and actuator of the present invention;
FIG. 23 is a schematic view of a handset control interface of the present invention;
FIG. 24 is a diagrammatic illustration of an alarm and protocol interface display in accordance with the present invention;
FIG. 25 is a schematic diagram of the artificial intelligence creator development of the invention;
figure 26 is a schematic view of an examination system of the present invention;
FIG. 27 is a schematic view of a management center of the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the attached drawings:
the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An AI + intelligent agricultural ecological development platform configures basic working parameters by installing corresponding sensors, AI intelligent equipment, network communication and other equipment, and builds a complete agricultural AIoT system (AI Internet of things system). The agricultural modern intelligent development is carried out by providing interfaces such as sensor access, agricultural growth strategy control, actuator control and the like. During the operation of the system, the parameters of agricultural growth factors such as light, temperature, water, vapor and fertilizer are collected in real time, then the control strategy of an actuating mechanism is set according to the sequence (obtained by big data analysis), the intelligent growth of crops in seedling stage, growth stage, flowering stage, overdue stage and other stages is completed, and the development work is evaluated according to the growth result.
The AI + intelligent agricultural ecological development platform provides a development interface, and a user can innovate and develop on any software and hardware system providing a TCP/IP protocol system by adopting any related programming language. FIG. 1 is a diagram of the architectural relationship of a product and related developments. The platform provides an industrial intelligent development platform for students, the students build various types of development systems, the industrial intelligent innovation development is carried out through standard communication protocols and related interfaces, the latest cloud/object/big/intelligent/5G hot spot technologies are fused, and the intelligent development of various industries is studied and promoted. For the unified name of the whole text, the AI + intelligent agricultural development platform is collectively called an AI development platform, and the student industry innovation development system is collectively called a user development system.
Fig. 2 shows that students are required to master basic AI mathematical knowledge, are familiar with statistics/machine learning/deep learning related theories, are interested in learning graphic image/voice related processing, and can use open source frames such as tensflo/Caffe/Torch/systemll to perform related AI development work according to documents, based on an AI development platform.
The AI development platform provides real-time image and voice recognition functions of entrance guard, monitoring, insect damage, disease and the like, and in the development process, scenes or voices of the development platform are collected through camera equipment or voice equipment. And performing AI deep network training by utilizing a provided or on-site acquired big data source of characters, targets or voice in advance. After the training result is confirmed to be reliable through testing, scene content of the AI development platform is predicted and analyzed in real time according to the training result, a related control instruction is sent according to the analysis result, and meanwhile, the real-time analysis result is transmitted into the AI development platform in real time, so that the platform can synthesize industrial intelligent development and AI development results and comprehensively evaluate development work effects.
The AI artificial intelligence training device provides a network + a general Json interface + a UDP/TCP protocol, and by adopting a new technology (5G, cloud computing, big data, the Internet of things and AI artificial intelligence) industry scene application through Android/Hongmon/Linux/AliOS software and hardware platforms, the sensor equipment and the AI intelligent equipment are combined, industry AI information logic, strategies and forms are simulated, industry innovation development and AI industry development are carried out, and therefore strategy big data analysis and AI understanding, expert system intelligent control execution and cloud + big data whole-process analysis monitoring are achieved. Can carry out professional project practice, professional project experiment and graduation design etc. through AI artificial intelligence trainer.
The training device comprises a whole set of project process of planning budget, system installation and system debugging and development of a creator, wherein the system installation comprises scene selection, equipment installation and cable connection, and the system debugging comprises centralized network management, data configuration, protocol alarm, data signal generation, equipment control and equipment operation.
1. Planning budget
As shown in fig. 3 to 5, the project planning and budget are simply referred to as planning budget, and in order to seek the most effective allocated resources, the modules required by the experiment are specified to achieve the objective systematic method. In the budget planning stage, equipment, tools and materials used in the artificial intelligence project process need to be analyzed, and a set of optimal schemes is selected to complete the project planning.
The students can clearly understand the physical conditions and cost budget required by the experiment, understand the functional action of each module instrument and improve the overall planning capability of a project by researching the environment, the module consumables and the instrument tools and confirming the budget in the virtual simulation software.
2. System installation
As shown in fig. 6, the system installation module of the AI artificial intelligence training apparatus mainly selects different artificial intelligence items, and selects a corresponding specific scene from the selected items to perform device installation.
The system installation needs the scene that uses there are big-arch shelter and artificial intelligence institute, can install equipment such as sensor, transmission module, transmission gateway, controller in the big-arch shelter, can install equipment such as router, cloud ware, cell-phone, Pad in artificial intelligence institute, connects each equipment through the cable.
(1) Scene selection: the AI artificial intelligence training device provides various real and visual artificial intelligence 3D application scenes, and students can choose to enter specific application scenes to install relevant artificial intelligence equipment.
(2) Equipment installation: after entering the selected scene, the functional area can be selected, and corresponding artificial intelligence equipment is installed in the corresponding functional area, wherein the equipment comprises a sensor module, a transmission module, a gateway module, communication equipment, a cloud server and an application terminal. And selecting relevant equipment needing to be installed from the equipment part, and directly dragging the equipment to the corresponding position. As shown in fig. 7-10.
(3) Cable connection: various required cables are provided, corresponding cables are selected to be connected with equipment, and the equipment comprises various wireless communication cables such as a control bus, a serial bus, WIFI, GPRS, Bluetooth, Zigbee, UWB and NFC. As shown in fig. 11-12.
(4) VR operation: when the system installation process of the AI artificial intelligence training device is completed, people can roam around the scene by wearing the VR helmet.
3. Debugging the system: as shown in fig. 13, the system debugging function of the AI artificial intelligence training apparatus emulates all the devices of the "cloud-pipe-end" of the artificial intelligence system. The equipment adopts the modular design, students can call corresponding equipment through selection, the equipment is connected through the building of a cable platform, then the simulation debugging of the equipment is carried out, and the application scene of the artificial intelligence equipment is simulated through the data source generation, and the students can flexibly network in the platform and carry out project learning.
(1) Centralized network management: the system debugging function of the AI artificial intelligence training device is used as a centralized network manager of artificial intelligence equipment, and supports direct synchronous equipment installation, all equipment is synchronously online, and an artificial intelligence 7-layer structure is automatically generated: the system comprises a sensing layer, a control layer, a transmission layer, a gateway layer, a communication layer, a service layer and a terminal layer, and data configuration and management of each module are facilitated for students. As shown in fig. 14.
(2) Data configuration: for right key selection of a single device, operations of the single device can be seen, including starting, stopping the device, deleting the device, importing an export script and configuring related data operations. As shown in fig. 15.
The data configuration interface platform adopts a GUI interface, in data configuration, students can flexibly select equipment to correspondingly install in various application scenes, each equipment has corresponding equipment information, the equipment automatically generates a unique SN code as a unique identifier in a system after installation, and the students can also know parameters required to be configured for normal operation of the module, wherein the parameters comprise: node address, topology network, node type, channel, network number, user number, authentication, etc.
4. Strategy design: the system debugging provides a strategy design function, and the function can freely control various execution devices including heating, humidifying, spraying systems, illumination roller shutters, fans and other devices through the integrated controller. In the experimental process, the system analyzes and counts the acquired and recorded sensing information such as air temperature and humidity, soil temperature and humidity, illuminance and the like, can dynamically display a sensing data change curve, compares the sensing data with a specified value, and sends a control instruction when the sensing data exceeds the specified value so as to automatically control the equipment such as spraying, ventilation, heating, humidification, roller shutters and the like to work. And when the relevant parameter values in the greenhouse return to the specified values, the control platform sends a work stopping instruction to the intelligent terminal equipment, and the user can also control the intelligent terminal equipment through a mobile phone.
(1) Designing environmental data: the AI artificial intelligence training device needs environmental data and growth condition data to carry out strategy design, combines a crop growth model, agricultural weather forecast, pest and disease damage monitoring and early warning and crop 'four-condition' monitoring, and provides production decision support by using big data statistical analysis. The system provides corresponding theoretical environmental data aiming at different seasons, and the growth conditions of crops are subjected to data design according to different growth period requirements, wherein the data comprise the temperature, humidity, illuminance, soil fertility and carbon dioxide concentration required by growth. The strategy design influences the growth condition of the crops, and the final growth result of the crops can be seen through simulation. As shown in fig. 16-17.
(2) Environmental monitoring: according to the weather change outside the greenhouse and the real-time information of the crop growth in the greenhouse, corresponding protective measures are taken, and the proper illumination supply and temperature and humidity control in the greenhouse are kept. As shown in fig. 18-20.
(3) Automatic policy generation: the automatic strategy mainly takes automatic control as a main part, corresponding parameter data (temperature, humidity, photosensitivity and the like) are set according to the time and a mathematical model, and various agricultural production execution devices including heating, humidifying, spraying systems, illumination roller shutters, fans and the like can be freely controlled through the integrated controller. By analyzing and counting the collected and recorded sensing information such as air temperature and humidity, soil temperature and humidity, illuminance and the like, a sensing data change curve can be dynamically displayed, the sensing data is compared with a specified value, and when the sensing data exceeds the specified value, a control instruction is sent out to automatically control the equipment such as spraying, ventilation, heating, humidification, roller shutters and the like to work. And when the relevant parameter values in the greenhouse return to the specified values, the control platform sends a work stopping instruction to the intelligent terminal equipment.
The intelligent sensor is used as sensing equipment for the interconnection of everything, and the collected data is mainly generated through real environment change so as to achieve the purpose of being consistent with a real data source. The AI artificial intelligence training device provides 3 data source generation modes: the method comprises the steps of accurately generating data by a mathematical model, acquiring and importing the data in a real-time data acquisition and importing system and importing the data through a commercial system data interface.
The data source may be generated by a simulation data model provided in the platform, which supports: constant distribution, linear distribution, sinusoidal distribution, logarithmic distribution, exponential distribution, Gaussian normal distribution, sine distribution and Fourier series distribution, and students can flexibly call the model to generate required simulation data.
(4) Equipment operation and control: the experiment is started, and the intelligent agriculture can check the running information of the relevant executing mechanism through the background management system in the running process. Students can check the system state information and the A/D and D/A conversion process by operating related equipment to carry out related learning. As shown in fig. 21 to 22.
(5) Cloud control: after the system normally operates, the equipment can be in the automatic process of function control through the input function of data; through the intelligent control algorithm that high in the clouds set up, make equipment be in among the intelligent control, through high in the clouds can the cruise line of direct control unmanned aerial vehicle equipment, controlgear's control visual angle etc.. As shown in fig. 23.
(6) Protocol alarming: as shown in fig. 24, the operation process of the device generates an alarm, which is divided into:
the alarm of the single device only needs to check the related alarm information in the data configuration part of the single device, and the student operates, configures and modifies the data according to the related alarm information;
the system alarm mainly comprises alarm interface alarm between devices and the like, and students modify the butt data of the two ends according to the alarm and the like.
Meanwhile, the message protocol generated in the running process of the equipment can be checked and seen, so that students can learn related knowledge.
5. And (3) artificial intelligence innovation and development: as shown in fig. 25, artificial intelligence creative project development is performed on the basis of a system installation module and a system debugging module; the training device provides a standard sensor data access interface, an application control interface and a big data analysis processing interface, provides a development sample program, a case and a source code for students to study, combines sensor equipment and AI intelligent equipment by using a network + a general Json interface + a UDP/TCP protocol and using Android/Hongmon/Linux/AliOS software and hardware platforms and adopting a new technology (5G, cloud computing, big data, Internet of things and AI artificial intelligence) industry scene application, simulates industry AI information logic, strategies and forms, and carries out industry innovation development and AI industry development, thereby realizing strategy big data analysis and AI understanding, expert system intelligent control execution and cloud + big data whole-process analysis monitoring.
6. An examination system: as shown in fig. 26, the examination center is divided into three parts, namely report submission, online examination and score evaluation, according to the actual conditions of the experimental item.
Report submission: after the students finish the experiment, the system automatically generates an experiment report, and after the finished experiment report is uploaded, the teacher can check the corresponding report at the management end.
And (3) online examination: in the AI artificial intelligence training device, a teacher can make and upload theoretical questions as a question bank and store the questions on a server, and the questions are sent to students for examination during examination, so that the students are examined. After the students submit the answer sheets, the system can automatically score, and the scores are recorded into the teacher system.
Performance evaluation: the teacher can score and evaluate the comprehensive scores of the students by checking the reports and the online examination scores submitted by the students on the AI training device.
7. Teaching management: the management terminal provides a management center, as shown in fig. 27, which can manage the student accounts, add, delete, modify account information, and log in the student accounts to check experimental conditions. The experiment end provides a personal center, the operation process of user registration and login is mainly realized, and the operation of login learning, examination and the like can be performed on a personal account provided at the service end.
The AI artificial intelligence training device provided by the invention has rich highly-simulated three-dimensional scenes, and is suitable for training in multiple industries such as intelligent agriculture, intelligent traffic, intelligent logistics, intelligent medical treatment, intelligent industry, intelligent safety, intelligent buildings and the like; the system has simple and easy-to-operate system functions, the system is rich and flexible to debug, and the product is easy to update, maintain and use; the technical principle of the training device is as follows: IOT (input output) synopsis data acquisition, which takes 5G communication as a channel, transmits the sensing data to a training device for cloud computing processing, and realizes artificial intelligence understanding and judgment; the actual sensor is connected to the training device, and the operation of equipment in a simulation scene of the training device is controlled through a data source generated by the real sensor, so that a relevant real-time dynamic effect is generated.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It should also be understood that the protection scope of the present invention, such as the general words used herein, and any modifications made on the basis of the technical solutions according to the technical ideas proposed by the present invention, fall within the protection scope of the present invention. While the embodiments of the present invention have been described in detail, the present invention is not limited to the embodiments, and various changes and modifications can be made without departing from the spirit and scope of the present invention by those skilled in the art
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. The utility model provides an AI artificial intelligence trainer which characterized in that: the system comprises a planning budget module, a system installation module, a system debugging module and a creator development module;
the planning budget module comprises project planning and budget and is used for seeking for allocating resources, analyzing equipment, tools and materials used in the process of the artificial intelligent project and further selecting a scheme to complete project planning;
the system installation module is used for selecting a corresponding specific scene in the selected artificial intelligence project to install equipment according to the selected artificial intelligence project;
the system debugging module is used for simulating all equipment at the cloud-pipe-end of the artificial intelligent system, and further can freely control various execution equipment through the integrated controller;
and the system installation module and the system debugging module are combined with the sensor equipment and the AI intelligent equipment to simulate industry AI information logic, strategies and forms and perform industry innovation development and AI industry development, so that strategy big data analysis and AI understanding, expert system intelligent control execution and cloud + big data whole-process analysis and monitoring are realized.
2. The AI artificial intelligence training device of claim 1, wherein: the system installation comprises scene selection, equipment installation, cable connection and VR operation;
the scene selection is used for selecting to enter a specific application scene for installing related artificial intelligence equipment according to various real and visual 3D application scenes provided by the AI artificial intelligence training device;
the equipment installation is used for selecting the functional area according to the selected scene, and installing corresponding artificial intelligence equipment in the corresponding functional area, wherein the equipment comprises a sensor module, a transmission module, a gateway module, communication equipment, a cloud server and an application terminal; selecting relevant equipment to be installed from the equipment part, and directly dragging the equipment to a corresponding position;
the cable connection is used for selecting a corresponding cable to carry out equipment connection and comprises various wireless communication cables such as a control bus, a serial bus, WIFI (wireless fidelity), GPRS (general packet radio service), Bluetooth, Zigbee, UWB (ultra wideband) and NFC (near field communication);
VR operation for physically roaming around its place in the scene by wearing a VR helmet.
3. The AI artificial intelligence training device of claim 1, wherein: the system debugging comprises centralized network management, data configuration, data signal generation, equipment control and equipment operation protocol alarm;
the system comprises a centralized network manager, a control layer, a transmission layer, a gateway layer, a communication layer, a service layer and a terminal layer, wherein the centralized network manager is used as the centralized network manager of the artificial intelligent equipment and supports direct synchronous equipment installation, all the equipment is synchronously online, and an artificial intelligent 7-layer structure is automatically generated and comprises a sensing layer, a control layer, a transmission layer, a gateway layer, a communication layer, a service layer and a terminal layer, so that data configuration and management can be conveniently carried out on each module;
the data configuration is used for selecting a right key of the single device, and can see the operation of the single device, including starting, stopping the device, deleting the device, importing an export script and configuring related data operation; the method comprises the following specific steps:
generating data signals, setting corresponding parameter data according to time and a mathematical model mode, and freely controlling various agricultural production execution devices through an integrated controller;
the device control comprises the steps that the device is in an automatic function control process through a data input function, the device is in intelligent control through an intelligent control algorithm arranged at a cloud end, a cruising circuit of the unmanned aerial vehicle device can be directly controlled through the cloud end, and a monitoring visual angle of the device is controlled;
the equipment runs, the running information of the relevant executing mechanism is checked through the background management system, the system state information and the A/D and D/A conversion process are checked through the operation of the relevant equipment, and relevant learning is carried out;
protocol alarms, including
The alarm of single equipment, the relevant alarm information can be viewed in the data configuration part of the single equipment, and then the operation, configuration and data modification are carried out according to the relevant alarm information;
and the in-system alarm comprises an alarm interface alarm between the equipment, and the butt joint data of the two ends of the equipment is modified according to the alarm.
4. An AI artificial intelligence training apparatus according to claim 1 or 3, characterized in that: the system debugging specifically comprises the following steps: by adopting a modular design, corresponding equipment is selected and called, the equipment is connected through the building of a cable platform, then the simulation debugging of the equipment is carried out, and the application scene of the artificial intelligent equipment is simulated through the generation of a data source, so that students can flexibly network in the platform and carry out project learning; comprises a heating system, a humidifying system, a spraying system, an illumination roller shutter and a fan; through analyzing and counting the collected and recorded sensing information of air temperature and humidity, soil temperature and humidity and illuminance, a sensing data change curve can be dynamically displayed, the sensing data is compared with a specified value, a control instruction is sent out when the sensing data exceeds the specified value, the spraying, ventilation, heating, humidification and rolling equipment is automatically controlled to work, after relevant parameter values in a greenhouse return to the specified value, a control platform can send a work stopping instruction to intelligent terminal equipment, and a user can also control the intelligent terminal equipment through a mobile phone.
5. The AI artificial intelligence training device of claim 1, wherein: the creator development module is specifically as follows: according to a sensor data access interface, an application control interface and a big data analysis processing interface which provide standards, development sample programs, cases and source codes are provided for students to study, through a network + a general Json interface + a UDP/TCP protocol, by means of software and hardware platforms such as Android/Hongmon/Linux/AliOS and the like, new technical industry scene application is adopted, sensor equipment and AI intelligent equipment are combined, industry AI information logic, strategies and forms are simulated, industry innovation development and AI industry development are carried out, and therefore strategy big data analysis and AI understanding, expert system intelligent control execution and cloud + big data whole-process analysis and monitoring are achieved, wherein the new technology comprises 5G, cloud computing, big data, an internet of things and AI artificial intelligence.
6. The AI artificial intelligence training device of claim 1, wherein: the system also comprises an examination system module, wherein the examination system module comprises three parts of report submission, online examination and score evaluation;
the report submitting module is used for automatically generating an experiment report by the system after the student completes the experiment, and the teacher can check the corresponding report at the management terminal after the completed experiment report is uploaded;
and the online examination is used in the AI artificial intelligence training device, teachers can make and upload theoretical questions as question banks and store the questions in the server, and the examination questions are issued to students during examination so as to take examinations on the students. After the students submit the answer sheets, the system can automatically score, and the scores are recorded into the teacher system.
Performance evaluation: the teacher can score and evaluate the comprehensive scores of the students by checking the reports and the online examination scores submitted by the students on the AI training device.
7. The AI artificial intelligence training device of claim 1, wherein: still contain teaching management module, teaching management module for the management end provides management center, manages student's account, adds, deletes, revises account information, can log in student's account and look over the experimental condition.
8. A training method based on the AI artificial intelligence training apparatus of any one of claims 1 to 7, characterized in that: the method specifically comprises the following steps;
step 1, planning budget: planning and budget of a project are abbreviated as planning budget, modules required by experiments are further defined so as to realize a target system method, equipment, tools and materials used in the process of an artificial intelligence project need to be analyzed in the budget planning stage, and then a set of optimal schemes are selected to complete the planning of the project;
step 2, system installation: a system installation module of the AI artificial intelligence training device selects different artificial intelligence projects and selects a corresponding specific scene in the selected projects to install equipment;
step 3, debugging the system: all equipment at the cloud-pipe-end of the artificial intelligence system is simulated through the system debugging function of the AI artificial intelligence training device, the equipment adopts a modular design, the corresponding equipment can be selected and called, the simulation debugging of the equipment is carried out through the building connection of a cable platform, the application scene of the artificial intelligence equipment is simulated through the generation of a data source, and the flexible networking and project learning can be carried out in the platform;
step 4, strategy design: during the experiment process, the system can dynamically display a change curve of sensing data by analyzing and counting the acquired and recorded sensing information of air temperature, humidity, soil temperature, humidity, illumination and the like, compare the sensing data with a specified value, send a control instruction when the sensing data exceeds the specified value, automatically control the devices such as spraying, ventilating, heating, humidifying, rolling the curtain and the like to work, send a work stopping instruction to the intelligent terminal device by the control platform after relevant parameter values in the greenhouse return to the specified value, and a user can also control the devices by a mobile phone;
step 5, artificial intelligence innovation development: carrying out artificial intelligence creative project development on the basis of system installation and system debugging; the training device provides a standard sensor data access interface, an application control interface and a big data analysis processing interface, provides a development sample program, a case and a source code for students to study, combines sensor equipment and AI intelligent equipment by using a network + a general Json interface + a UDP/TCP protocol and by using Android/Hongmon/Linux/AliOS software and hardware platforms and adopting new technical industry scene application, simulates industry AI information logic, strategies and forms, carries out industry innovation development and AI industry development, and accordingly realizes strategy big data analysis and AI understanding, expert system intelligent control execution and cloud + big data whole-process analysis and monitoring.
9. The AI artificial intelligence training apparatus-based training method according to claim 8, wherein: the step 4 specifically comprises the following steps:
step 4.1, designing environmental data: the AI artificial intelligence training device needs environmental data and growth condition data to carry out strategy design, combines a crop growth model, agricultural weather forecast, pest and disease monitoring and early warning and crop four-condition monitoring, provides production decision support by using big data statistical analysis, provides corresponding theoretical environmental data aiming at different seasons, carries out data design on the growth conditions of crops according to different growth periods, and comprises humiture, illuminance, soil fertility and carbon dioxide concentration required by growth;
step 4.2, environment monitoring: according to the weather change outside the greenhouse and the real-time information of the crop growth in the greenhouse, making corresponding protective measures, and keeping proper illumination supply and temperature and humidity control in the greenhouse;
and 4.3, automatic strategy generation: the automatic strategy mainly takes automatic control as a main part, corresponding parameter data including temperature, humidity and photosensitivity are set according to the time and mathematical model, various agricultural production execution devices can be freely controlled through the integrated controller, the automatic strategy comprises heating, humidifying, a spraying system, an illumination roller shutter and a fan, the collected and recorded sensing information is analyzed and counted, wherein the sensing information comprises air temperature and humidity, soil temperature and humidity and illumination intensity, a sensing data change curve can be dynamically displayed, the sensing data is compared with a specified value, a control instruction is sent out when the sensing data exceeds the specified value, the automatic control spraying, ventilating, heating, humidifying and roller shutter are automatically controlled to work, and when relevant parameter values in a greenhouse return to the specified value, a control platform can send out a work stop instruction to the intelligent terminal device.
And 4.4, equipment operation and control: in the operation process of the intelligent agriculture, the operation information of the relevant actuating mechanism can be checked through the background management system, the system state information and the A/D and D/A conversion process can be checked through operating relevant equipment, and relevant learning is carried out;
step 4.5, cloud control: after the system normally operates, the equipment can be in the automatic process of function control through the input function of data; the equipment is in intelligent control through an intelligent control algorithm arranged at the cloud end, the cruising line of the unmanned aerial vehicle equipment can be directly controlled through the cloud end, and the monitoring visual angle of the equipment is controlled;
step 4.6, protocol alarm: the operation process of the equipment can generate an alarm, and the alarm is divided into:
the alarm of the single device only needs to be seen in the data configuration part of the single device, and students operate, configure and modify data according to the relevant alarm information;
and the system internal alarm comprises an alarm interface alarm between the equipment, and the student modifies the butt data of the two ends according to the alarm.
10. The AI artificial intelligence training apparatus-based training method according to claim 9, wherein: the AI artificial intelligence training device provides 3 data source generation modes: accurately generating data by a mathematical model, and importing the data by a real-time data acquisition and import system and a commercial system data interface;
the data source can be generated through a simulation data model provided in the platform, and supports: constant distribution, linear distribution, sinusoidal distribution, logarithmic distribution, exponential distribution, Gaussian normal distribution, sine distribution and Fourier series distribution, and students can flexibly call the model to generate required simulation data.
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