CN113325773A - Intelligent pilot physical training monitoring system based on big data - Google Patents
Intelligent pilot physical training monitoring system based on big data Download PDFInfo
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- CN113325773A CN113325773A CN202110596125.5A CN202110596125A CN113325773A CN 113325773 A CN113325773 A CN 113325773A CN 202110596125 A CN202110596125 A CN 202110596125A CN 113325773 A CN113325773 A CN 113325773A
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
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- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
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Abstract
The invention belongs to the technical field of physical training monitoring, and discloses a big data-based intelligent pilot physical training monitoring system, which comprises a data acquisition and reading module; a physical ability monitoring and alarming module; a central processing module; a local storage module; a cloud storage module; a physical fitness evaluation module; the invention monitors the physical ability condition of the pilot in real time through the plurality of sensors and transmits back the integral data on the pilot, thereby ensuring the whole body signal which is rapidly mastered when abnormal conditions occur in the training of the pilot, and rapidly judging the analysis of the abnormal condition of the pilot so as to rapidly take measures. Through setting up physical stamina monitoring alarm module and having guaranteed the warning staff that can be timely in the twinkling of an eye that abnormal data appears, prevent that the staff from not discovering the appearance of pilot physical stamina abnormal conditions in time, having guaranteed the rescue promptness. The data storage module stores real-time data of the pilot, and ensures data input of a judging program and data query after judgment.
Description
Technical Field
The invention belongs to the technical field of physical training monitoring, and particularly relates to an intelligent pilot physical training monitoring system based on big data.
Background
At present: physical ability is the basic athletic ability of a human body expressed by the sports qualities of strength, speed, endurance, coordination, flexibility, sensitivity and the like, and is an important component factor of athletic ability of athletes. The physical performance level is closely related to the morphological characteristics of a human body and the functional characteristics of the human body, the physical performance of a pilot is monitored in real time because the physical performance of the pilot is usually trained in high altitude, so that the personal safety of the pilot is ensured, the monitoring of the physical performance training is very important, the existing physical performance training is mainly judged by a coach manually, the physical limit of a trainer is judged by the experience of the coach, errors and errors are more, and sudden death in the training can be caused.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) the existing monitoring on the physical training of the pilot does not have a complete data system for managing the physical training of the pilot, and the internet data cannot be fully utilized.
(2) Most of the existing physical training monitoring still stays at the stage of manual experience judgment, the error is large, and the personal safety of athletes cannot be guaranteed.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an intelligent pilot physical training monitoring system based on big data.
The invention is realized in this way, a big data based intelligent pilot physical training monitoring system, the big data based intelligent pilot physical training monitoring system includes:
the data acquisition and reading module is connected with the central processing module and comprises acquisition equipment and reading equipment, the acquisition equipment acquires required data, the data acquired by the acquisition equipment is an electric signal, the electric signal is converted into a digital signal through an A/D converter and is transmitted to the central processing module through a transmission line, and the reading equipment is used for checking the content acquired in real time;
the physical ability monitoring and alarming module is connected with the central processing module and comprises a monitoring CPU and an alarm, the monitoring CPU monitors the physical ability state of the trainer data transmitted in real time, the monitoring CPU is stimulated to generate an electric signal once the physical ability data is abnormal, and if the electric signal is analyzed to be abnormal change by the CPU, the alarm is called immediately to send an alarm to remind monitoring personnel and medical personnel;
the central processing module is connected with the data acquisition and reading module, the physical ability monitoring and alarming module, the local storage module, the cloud storage module and the physical ability judging module, and the main controller acquires external signals (data and requests transmitted by the modules) and outputs the external signals to the output channel after analysis and processing. When analog quantity output is required from the outside, the system is converted into a standard electric signal through a D/A converter and is output to control each module to work normally;
the data acquisition and reading module packs and sends the converted digital signals to the central processing module, and the digital signals are subjected to label operation by the central processing module and are transmitted to the local storage module and the cloud storage module;
the cloud storage module is connected with the central processing module, uses cloud storage service, firstly creates a cloud storage platform in a local server deployment data center, and realizes a storage protocol through a third-party gateway, wherein the storage protocol can realize conversion from NFS to SMB, and a user finishes data cloud storage in a cloud storage available area;
the physical ability evaluation module is composed of a server and an evaluation program, the evaluation program sends a request for data to the central processing unit, the request information reaches the switch, the switch sends the request information to the router, the router sends the request information to the server, the DNS server reaches the main controller, the server receives the request for data, the data to be counted are packaged and packaged, the original path returns to the physical ability evaluation module, the data are decoded, and the evaluation program uses the trained deep convolutional neural network to calculate and evaluate the data. Used for analyzing the current physical ability state of the athlete through the judging program.
Further, the data acquisition reading module comprises a plurality of sensors, each sensor corresponds to a different training item, and the trainer wears the sensors on the body for acquiring the physical ability condition of the trainer in real time in the whole training process.
Further, the connection mode of the cloud storage module cloud server at least includes but is not limited to 3G, 4G, 5G, WIFI and network cable connection.
Further, the storage service used in the local storage module uses an SQL service, and the SQL service needs to be configured for the local computer before use.
Furthermore, the abnormal condition occurring in the physical ability monitoring and alarming module means that data with overlarge difference suddenly occurs in stable real-time data, and then the generation of electric signals of the physical ability monitoring CPU is caused.
Further, the model core establishing process in the evaluation program of the physical ability evaluation module is as follows:
s1: acquiring physical training data of athletes on a network;
s2: establishing an initial model, wherein a framework is a convolutional neural network, and initializing parameters of the model in a random value-taking mode;
s3: inputting the collected data into an initial model for training, and continuously optimizing parameters through continuous training of the data until the parameters are not obviously changed and stable;
s4: and selecting physical training data out of the training samples, inputting the physical training data into the model to verify the accuracy of the physical training data, finishing training if the physical training data is accurate, and repeating S3 if the physical training data is not accurate.
By combining all the technical schemes, the invention has the advantages and positive effects that:
(1) the invention monitors the physical ability condition of the pilot in real time through the plurality of sensors and transmits back the integral data on the pilot, thereby ensuring the whole body signal which is rapidly mastered when abnormal conditions occur in the training of the pilot, and rapidly judging the analysis of the abnormal condition of the pilot so as to rapidly take measures.
(2) According to the invention, the physical ability monitoring and alarming module is arranged, so that the working personnel can be timely reminded at the moment of abnormal data, the situation that the working personnel do not timely find the abnormal physical ability of the pilot is prevented, and the timeliness of rescue is ensured.
(3) The data storage module of the invention classifies, compresses and stores the corresponding data information, clusters the data, can accurately classify the data, effectively realizes the storage of the data, stores the real-time data of the pilot, and ensures the data input of the judging program and the data query after the judgment.
Drawings
FIG. 1 is a schematic structural diagram of a big data-based intelligent pilot physical training monitoring system according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a cloud storage principle provided in an embodiment of the present invention.
Fig. 3 is a flowchart of the steps of establishing an evaluation procedure according to an embodiment of the present invention.
In the figure: 1. a data acquisition and reading module; 2. a physical ability monitoring and alarming module; 3. a central processing module; 4. a local storage block module; 5. a cloud storage module; 6. a physical fitness evaluation module;
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides an intelligent pilot physical training monitoring system based on big data, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, an embodiment of the present invention provides a big-data-based intelligent pilot physical training monitoring system, which includes:
the data acquisition and reading module 1 is connected with the central processing module and comprises acquisition equipment and reading equipment, the acquisition equipment acquires required data, the data acquired by the acquisition equipment is an electric signal, the electric signal is converted into a digital signal through an A/D converter and is transmitted to the central processing module through a transmission line, and the reading equipment is used for checking the content acquired in real time;
the physical ability monitoring alarm module 2 is connected with the central processing module and comprises a monitoring CPU and an alarm, the monitoring CPU monitors the physical ability state of the trainer data transmitted in real time, the monitoring CPU is stimulated to generate an electric signal once the physical ability data is abnormal, and if the electric signal is analyzed to be abnormal change by the CPU, the alarm is called immediately to send an alarm to remind monitoring personnel and medical personnel;
the central processing module 3 is connected with the data acquisition and reading module 1, the physical ability monitoring and alarming module 2, the local storage module 4, the cloud storage module 5 and the physical ability judging module 6, and the main controller acquires external signals (data and requests transmitted by the modules) and outputs the external signals to the output channel after analysis and processing. When analog quantity output is required from the outside, the system is converted into a standard electric signal through a D/A converter and is output to control each module to work normally;
the local storage module 4 is connected with the central processing module and used for storing the acquired equipment, the data acquisition and reading module packs and sends the converted digital signals to the central processing module 3, and the digital signals are subjected to label operation through the central processing module and are transmitted to the local storage module and the cloud storage module;
the cloud storage module 5 is connected with the central processing module, uses cloud storage service, firstly creates a cloud storage platform in a local server deployment data center, and realizes a storage protocol through a third-party gateway, wherein the storage protocol can realize conversion from NFS to SMB, and a user finishes data cloud storage in a cloud storage available area;
the physical ability evaluation module 6 is composed of a server and an evaluation program, the evaluation program sends a request for data to the central processing unit, the request information reaches the switch, the switch sends the request to the router, the router sends the request to the server of the DNS server, the server receives the request for data, the data to be counted are packaged and packaged, the original path is returned to the physical ability evaluation module 6, the data are decoded, and the evaluation program uses a trained deep convolutional neural network to calculate and evaluate the data. Used for analyzing the current physical ability state of the athlete through the judging program.
The data acquisition reading module 1 comprises a plurality of sensors, each sensor corresponds to a different training item, and a trainer wears the sensors on the body for acquiring the physical ability condition of the trainer in real time in the whole training process.
The connection mode of the cloud storage module 5 and the cloud server at least includes but is not limited to 3G, 4G, 5G, WIFI and network cable connection.
The storage service used in the local storage module 4 uses SQL service, and the local computer needs to be configured with SQL service before use.
The abnormal condition of the physical ability monitoring and alarming module 6 means that data with overlarge difference suddenly appears in stable real-time data, and then the generation of electric signals of the physical ability monitoring CPU is caused.
As shown in fig. 2, the cloud storage module principle is: the cloud storage service is used, firstly, a cloud storage platform is created in a local server deployment data center, a storage protocol is realized through a third-party gateway, a user writes local data into the cloud storage gateway through a network cable, the cloud storage gateway transmits the data to a boundary route, the boundary route transmits the data to the cloud platform through a private-line public network, an object storage request is initiated in the cloud platform, the data is transmitted to the cloud storage gateway in the cloud platform, and the cloud storage gateway transmits the data to a cloud storage available area through a vSwitch to finish data cloud storage.
The VSwitch refers to a virtual switch or a virtual network switch, works in a two-layer data network, and realizes the two-layer (and partial three-layer) network function of a physical switch in a software mode. Compared with the traditional physical switch, the virtual switch has the advantages of flexible configuration and strong expansibility. Dozens of or even hundreds of virtual switches can be configured on a common server, and the number of ports can be flexibly selected.
As shown in fig. 3, the model core establishing process in the evaluation program is:
s1: acquiring physical training data of athletes on a network;
s2: establishing an initial model, wherein a framework is a convolutional neural network, and initializing parameters of the model in a random value-taking mode;
s3: inputting the collected data into an initial model for training, and continuously optimizing parameters through continuous training of the data until the parameters are not obviously changed and stable;
s4: and selecting physical training data out of the training samples, inputting the physical training data into the model to verify the accuracy of the physical training data, finishing training if the physical training data is accurate, and repeating S3 if the physical training data is not accurate.
The working principle provided by the invention is as follows: data acquisition read module 1 gathers pilot's real-time physical stamina information, real-time transmission is to central processing module 3, there is central processing module 3 to send data to physical stamina detection alarm module 2, real-time supervision real-time data, in case unusual data appear report to the police immediately, local storage module 4, with data storage in local SQL database, carry out the data backup, cloud storage module 5, with data backup in the high in the clouds, physical stamina judge module 6, with data input evaluation program, through model processing, reach the real-time physical stamina situation of pilot.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A big data based intelligent pilot physical training monitoring system, the big data based intelligent pilot physical training monitoring system comprising:
the data acquisition and reading module is connected with the central processing module and comprises acquisition equipment and reading equipment, the acquisition equipment acquires required data, the data acquired by the acquisition equipment is an electric signal, the electric signal is converted into a digital signal through an A/D converter and is transmitted to the central processing module through a transmission line, and the reading equipment is used for checking the content acquired in real time;
the physical ability monitoring and alarming module is connected with the central processing module and comprises a monitoring CPU and an alarm, the monitoring CPU monitors the physical ability state of the trainer data transmitted in real time, the monitoring CPU is stimulated to generate an electric signal once the physical ability data is abnormal, and if the electric signal is analyzed to be abnormal change by the CPU, the alarm is called immediately to send an alarm to remind monitoring personnel and medical personnel;
the central processing module is connected with the data acquisition and reading module, the physical ability monitoring and alarming module, the local storage module, the cloud storage module and the physical ability judging module, and the main controller acquires external signals (data and requests transmitted by the modules) and outputs the external signals to the output channel after analysis and processing. When analog quantity output is required from the outside, the system is converted into a standard electric signal through a D/A converter and is output to control each module to work normally;
the data acquisition and reading module packs and sends the converted digital signals to the central processing module, and the digital signals are subjected to label operation by the central processing module and are transmitted to the local storage module and the cloud storage module;
the cloud storage module is connected with the central processing module, cloud storage service is used, a cloud storage platform is firstly created in a local server deployment data center, a storage protocol is realized through a third-party gateway, the storage protocol can realize conversion from NFS to SMB, a user writes local data into the cloud storage gateway through a network cable, the cloud storage gateway transmits the data to a boundary router, the boundary router transmits the data to the cloud platform through a private-line public network, a request for object storage is initiated in the cloud platform, the data are transmitted to the cloud storage gateway in the cloud platform, and the cloud storage gateway transmits the data to a cloud storage available area through vSwitch to finish data cloud storage;
the physical ability evaluation module is composed of a server and an evaluation program, the evaluation program sends a request for data to the central processing unit, the request information reaches the switch, the switch sends the request information to the router, the router sends the request information to the server, the DNS server reaches the main controller, the server receives the request for data, the data to be counted are packaged and packaged, the original path returns to the physical ability evaluation module, the data are decoded, and the evaluation program uses the trained deep convolutional neural network to calculate and evaluate the data. Used for analyzing the current physical ability state of the athlete through the judging program.
2. The big-data-based intelligent pilot physical training monitoring system as claimed in claim 1, wherein the data collection and reading module comprises a plurality of sensors, each sensor corresponds to a different training item, and the trainer wears the sensors on the body for collecting the physical performance of the trainer in real time during the whole training process.
3. The big-data-based smart pilot physical training monitoring system of claim 1, wherein the cloud storage module cloud servers are connected in a manner at least including, but not limited to, 3G, 4G, 5G, WIFI, network cable connection.
4. The big-data-based smart pilot physical training monitoring system of claim 1, wherein the storage service used in the local storage module is SQL service, requiring the local computer to be configured with SQL service before use.
5. The big-data-based intelligent pilot physical training monitoring system as claimed in claim 1, wherein the abnormal condition occurring in the physical monitoring alarm module is a sudden occurrence of data with an excessive difference value in the stationary real-time data, which may cause the generation of the electrical signal of the physical monitoring CPU.
6. The big-data-based intelligent pilot physical training monitoring system of claim 1, wherein the model core establishing process in the evaluation program of the physical judgment module is as follows:
s1: acquiring physical training data of athletes on a network;
s2: establishing an initial model, wherein a framework is a convolutional neural network, and initializing parameters of the model in a random value-taking mode;
s3: inputting the collected data into an initial model for training, and continuously optimizing parameters through continuous training of the data until the parameters are not obviously changed and stable;
s4: and selecting physical training data out of the training samples, inputting the physical training data into the model to verify the accuracy of the physical training data, finishing training if the physical training data is accurate, and repeating S3 if the physical training data is not accurate.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114288629A (en) * | 2021-12-08 | 2022-04-08 | 广东技术师范大学 | Physical ability information acquisition and analysis system and method based on big data |
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Application publication date: 20210831 |