CN114066330A - Distribution method of gymnasium coach manager based on artificial intelligence - Google Patents

Distribution method of gymnasium coach manager based on artificial intelligence Download PDF

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CN114066330A
CN114066330A CN202210039808.5A CN202210039808A CN114066330A CN 114066330 A CN114066330 A CN 114066330A CN 202210039808 A CN202210039808 A CN 202210039808A CN 114066330 A CN114066330 A CN 114066330A
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叶丽兰
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Nantong Gaoqiao Sporting Goods Co ltd
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Abstract

The invention relates to the technical field of artificial intelligence, in particular to a distribution method of training managers of a gymnasium based on artificial intelligence. The method comprises the steps of obtaining an action standard rate of using corresponding fitness equipment according to a three-dimensional action sequence of a fitness worker; obtaining the demand of each type of fitness equipment area on coach management personnel according to the action standard rate, obtaining the initial number of distribution personnel required by each type of fitness equipment area according to the demand, carrying out area integration based on the position relation of each type of fitness equipment area to obtain a plurality of integration areas, and obtaining the new number of distribution personnel of each integration area by combining the integration areas and the initial number of distribution personnel; and carrying out corresponding personnel scheduling on the coach management personnel by combining the new number of the distributed personnel and the total number of the coach management personnel. Through the personnel allocation of pertinence, the rationality of personnel allocation and the utilization rate of personnel are greatly improved, the action of coach managers is fully exerted, and the body building efficiency and the body building quality of body building personnel are improved.

Description

Distribution method of gymnasium coach manager based on artificial intelligence
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a distribution method of training managers of a gymnasium based on artificial intelligence.
Background
With the increasing living standard, the requirements of people on self health are higher and higher, and more people choose to exercise bodies in gymnasiums. In order to improve the body-building experience of the body-building personnel, the coach manager in the gymnasium can provide help aiming at the body-building action, the body-building requirement and the like of the body-building personnel. Due to the fact that the exercise equipment is different in use difficulty, the standard use rate of the exercise personnel for different exercise equipment is different, and therefore more coaches need to be equipped for the exercise equipment with high use rate and low use standard rate.
When distributing coach managers at present, the coach managers are generally distributed based on the body-building person density, and the demand condition of the action standard rate of the body-building persons on the coach managers is not considered, so that the distribution reasonability is reduced, and the effects of the coach managers are weakened.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a gymnasium coach manager distribution method based on artificial intelligence, which adopts the following technical scheme:
the embodiment of the invention provides a gymnasium coach manager distribution method based on artificial intelligence, which comprises the following specific steps:
acquiring a three-dimensional action sequence of a fitness person using the fitness equipment, and acquiring an action standard rate by using the three-dimensional action sequence and a corresponding standard action sequence;
obtaining the demand degree of each type of fitness equipment area for coach managers according to the action standard rate, and obtaining the initial distribution number of people required by each type of fitness equipment area according to the demand degree; performing region integration based on the position relation of each type of the key equipment region to obtain a plurality of integration regions, and acquiring a new number of distribution persons of each integration region by combining the integration regions and the initial number of distribution persons;
and carrying out corresponding personnel scheduling on the coaching management personnel by combining the new number of the distributed personnel and the total number of the coaching management personnel.
Preferably, the method for obtaining the demand degree of each type of fitness equipment area for the trainer manager from the action standard rate comprises the following steps:
counting a first number of the fitness personnel using each type of the fitness equipment, and combining the action standard rate and the first number of each fitness personnel to obtain the nonstandard degree of each type of the fitness equipment when used;
and obtaining the demand degree of the fitness equipment area corresponding to the fitness equipment to the coach manager according to the nonstandard degree.
Preferably, the method for obtaining the initial number of people required for each type of the exercise equipment area according to the demand degree includes:
and multiplying the demand degree of each type of fitness equipment area by the total number of the coaches to obtain the initial distribution number of people of each type of fitness equipment area.
Preferably, the method for performing area integration based on the position relationship of each type of the key device area to obtain a plurality of integrated areas includes:
dividing the fitness equipment area of the whole fitness room into M closed areas and 1 open area according to a floor plan of the fitness room; the closed area refers to each room area in the gymnasium, and the open area refers to a public area outside the room area;
performing zone integration based on the positional relationship of each type of exercise equipment zone in the closed zone and the open zone to obtain a plurality of the integrated zones.
Preferably, the method for performing area integration based on the position relationship between each type of the exercise equipment area in the closed area and the open area to obtain a plurality of the integration areas comprises:
regarding each of the closed regions as one of the integrated regions;
for the open area, the open area is divided into a plurality of integration areas according to the position relation of different fitness equipment areas in the open area and the demand degree of each type of fitness equipment area.
Preferably, the method for dividing the open area into a plurality of the integrated areas includes:
acquiring the area center point position of each type of fitness equipment area, and respectively acquiring the matching degree between the area center point position and each type of fitness equipment area in the surrounding 8 adjacent areas by taking any type of fitness equipment area as the center according to the initial distribution number of people and the area center point position so as to obtain a matching result with the highest matching degree;
setting an initial integration area, and integrating the exercise equipment areas capable of forming a closed loop into one integration area if the matching result of the initial integration area forms a closed loop from the initial integration area; integrating the exercise equipment regions in the 8 surrounding vicinity of the initial integration region into one integration region if the matching result of the initial integration region fails to form a closed loop.
Preferably, the exercise equipment area with the minimum number of the initially distributed persons in the open area is the initial integration area.
Preferably, the method for obtaining the new number of people for each of the integrated areas by combining the integrated areas and the initial number of people for distribution comprises:
and taking the sum of the initial distribution population corresponding to all the fitness equipment areas in each integration area as the new distribution population of the integration area.
Preferably, the method for performing corresponding staff scheduling on the coaching managers by combining the new number of distributed staff and the total number of the coaching managers comprises the following steps:
setting a distribution number threshold, and when the new distribution number is smaller than the distribution number threshold, not distributing the coach manager to the corresponding integration area; for the integration area corresponding to the distribution number threshold value, rounding the new distribution number in the integration area to obtain the actual distribution number of people in each integration area;
and carrying out corresponding personnel scheduling on the coach management personnel by combining the actual number of the distributed personnel and the total number of the coach management personnel.
Preferably, the method for performing corresponding staff scheduling on the coaching managers by combining the actual number of distributed staff and the total number of the coaching managers comprises the following steps:
calculating the predicted total number of the coach managers according to the actual number of the distributed persons in each integration area, and adjusting the actual number of the distributed persons in each integration area based on the size relation between the predicted total number and the actual total number to obtain the final number of the distributed persons in each integration area;
dispatching a relative number of the trainer managers to the respective integration zones by the final number of people assigned to each of the integration zones.
The embodiment of the invention at least has the following beneficial effects: carry out the regional integration of fitness equipment based on the positional information of gymnasium overall arrangement and fitness equipment region, and then carry out the pertinence personnel allocation to the integration region according to action standard rate and the train managers's total number of the body-building action when fitness equipment is used to the fitness equipment, greatly improved personnel's distribution's rationality and personnel's utilization ratio for full play train managers's effect, and then promote fitness personnel's body-building efficiency and body-building quality.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart illustrating the steps of a method for assigning gym trainer managers based on artificial intelligence according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention for achieving the predetermined objects, the following detailed description of the present invention will be provided in conjunction with the accompanying drawings and the preferred embodiments for the method for distributing training managers for gymnasium based on artificial intelligence, the detailed implementation, structure, features and effects thereof. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all 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.
The following describes a specific scheme of the allocation method of the gym coach manager based on artificial intelligence in detail with reference to the accompanying drawings.
Referring to FIG. 1, a flow chart of the steps of a method for assigning gym trainer managers based on artificial intelligence according to an embodiment of the invention is shown, the method comprising the following steps:
and S001, acquiring a three-dimensional action sequence of the fitness equipment used by the fitness personnel, and obtaining an action standard rate by the three-dimensional action sequence and the corresponding standard action sequence.
Specifically, because a plurality of monitoring devices are installed in the gymnasium to monitor each gymnasium area, image data can be acquired based on the monitoring devices in the gymnasium, so that image information of the gymnastics and the gymnasiums in each gymnasium area can be acquired in real time.
Analyzing the body-building action of the body-building personnel based on the acquired image, acquiring a three-dimensional action sequence of the body-building personnel, and further acquiring an action standard rate of the body-building personnel when the body-building personnel uses corresponding body-building equipment according to the three-dimensional action sequence, wherein the specific process comprises the following steps:
(1) and acquiring human body key points of the fitness personnel by adopting a key point detection network, and acquiring a three-dimensional action sequence of the fitness personnel according to the human body key points.
Specifically, a DNN network with an encoder-decoder structure is used for detecting key points of a human body; labeling label data of DNN network training, wherein labeled human key points comprise: 15 human body key points of the head, the neck, the left and right shoulder joints, the left and right elbow joints, the left and right wrist joints, the central point of the spine, the left and right hip joints, the left and right knee joints and the left and right ankle joints; forming key point hot spots on the marked points by adopting Gaussian blur to obtain a human body key point thermodynamic diagram conforming to Gaussian distribution, and carrying out normalization processing on the label data to enable the value domain of the output hot spots to be positioned at [0,1 ]; inputting image data and thermodynamic diagram label data into a DNN network, and training a human body key point encoder and a human body key point decoder end to end; and training the DNN network by adopting a mean square error loss function.
The input of the DNN network is normalized image data, and a human body key point thermodynamic diagram as large as the input image is output in a 16-channel form, that is, the human body key point thermodynamic diagram includes 15 human body key points and 1 background.
Further, after acquiring a human body key point thermodynamic diagram, matching human body key points based on PAFs, and connecting the human body key points corresponding to each fitness person in a combined manner, namely, returning the relation between the human body key points by using network branches to obtain a component Affinity vector field (PAFs) of each human body key point, wherein the network branches and the key point detection network belong to two branches of the same network.
The training process of the network branch is as follows: the label data is a human body key point vector diagram containing the positions and directions of all human body key points, is marked as a unit vector pointing to the direction of another human body key point from one human body key point, and is output as a vector diagram correspondingly connected with all human body key points; the network branch also adopts a mean square error loss function to carry out iterative training.
After obtaining the multi-frame human key point vector diagram, extracting the three-dimensional action sequence of each fitness person from the human key point vector diagram through the TCN network model for accurately analyzing the movement condition of the fitness person, wherein the selected frame number and the length of the three-dimensional action sequence can be set according to the actual condition.
(2) And after the three-dimensional action sequence of each fitness worker is obtained, the three-dimensional action sequence is compared and analyzed with the standard fitness action in the fitness action simulator, and the action standard rate when the corresponding fitness equipment is used is obtained by obtaining the similarity between the three-dimensional action sequence and the corresponding standard action sequence.
Step S002, obtaining the demand degree of each type of fitness equipment area for coach managers according to the action standard rate, and obtaining the initial distribution number of people required by each type of fitness equipment area according to the demand degree; and performing region integration based on the position relation of each type of key equipment region to obtain a plurality of integration regions, and acquiring a new distribution number of each integration region by combining the integration regions and the initial distribution number.
Specifically, according to the action standard rate of fitness personnel when using various types of fitness equipment, the demand degree of each type of corresponding fitness equipment area for coach managers is obtained, and then the initial number of people required by each type of fitness equipment area is obtained according to the demand degree, and the specific method comprises the following steps:
(1) and counting the first number of the fitness personnel using each type of fitness equipment, and combining the action standard rate and the first number of each fitness personnel to obtain the nonstandard degree of each type of fitness equipment when used.
In particular, in the following
Figure 713909DEST_PATH_IMAGE001
An example of a fitness device is
Figure 427787DEST_PATH_IMAGE002
Using at all times
Figure 614049DEST_PATH_IMAGE001
The body-building personnel like the body-building equipment have
Figure 540417DEST_PATH_IMAGE003
According to
Figure 10581DEST_PATH_IMAGE003
The standard rate of action of the individual body-building person is obtained
Figure 505148DEST_PATH_IMAGE001
Similar to body-building equipment
Figure 303340DEST_PATH_IMAGE002
Degree of dissimilarity corresponding to time when used
Figure 659497DEST_PATH_IMAGE004
Figure DEST_PATH_IMAGE005
Wherein the content of the first and second substances,
Figure 125113DEST_PATH_IMAGE006
is as follows
Figure 525002DEST_PATH_IMAGE007
Standard rate of motion of individual exercisers.
It should be noted that the larger the nonstandard degree is, the smaller the corresponding minimum standard rate is, and further the exercise area of the exercise equipment needs the exercise manager.
(2) And obtaining the demand degree of the fitness equipment area corresponding to the fitness equipment to the coach manager according to the nonstandard degree.
Specifically, the nonstandard degree of each type of fitness equipment is normalized, and the normalized value is used as the initial demand degree of the type of fitness equipment
Figure 200702DEST_PATH_IMAGE001
The initial requirement degree of the body-building-like equipment is
Figure 468873DEST_PATH_IMAGE008
The smaller the minimum action standard rate corresponding to each type of fitness equipment is, the higher the demand degree corresponding to a coach manager is, the larger the corresponding correction coefficient is, so that the minimum action standard rate of each type of fitness equipment is normalized to obtain a corresponding normalized value, and then the correction coefficient corresponding to each type of fitness equipment is obtained according to the normalized value, namely according to the second step
Figure 398783DEST_PATH_IMAGE001
Minimum action standard rate of fitness equipment-like
Figure 359785DEST_PATH_IMAGE009
Obtaining corresponding normalized values
Figure 761598DEST_PATH_IMAGE010
Then it is first
Figure 567880DEST_PATH_IMAGE001
Correction coefficient corresponding to fitness equipment
Figure 617875DEST_PATH_IMAGE011
Obtaining the demand degree of the corresponding fitness equipment area of each type of fitness equipment by combining the initial demand degree and the correction coefficient
Figure 484200DEST_PATH_IMAGE001
The requirement degree of the similar body-building equipment is
Figure 868914DEST_PATH_IMAGE012
. Normalizing the demand degrees of various fitness equipment to obtain the final demand degree
Figure 478887DEST_PATH_IMAGE001
The final demand degree of the fitness equipment-like corresponding to the fitness equipment area is
Figure 383389DEST_PATH_IMAGE013
(3) Based on the final demand degree of various fitness equipment areas, the total number of coaches and managers in the gym is combined
Figure 686194DEST_PATH_IMAGE014
Obtaining the initial distribution number of people required by the corresponding fitness equipment area of each type of fitness equipment, namely obtaining the initial distribution number of people of each type of fitness equipment area by multiplying the demand degree of each type of fitness equipment area by the total number of coach management personnel respectively
Figure 794090DEST_PATH_IMAGE001
The initial number of people distributed to the area of the fitness equipment corresponding to the fitness equipment is
Figure 207754DEST_PATH_IMAGE015
Further, due to the final demand
Figure 966762DEST_PATH_IMAGE013
Is in the range of [0,1]]In order to initially distribute the number of people
Figure 440469DEST_PATH_IMAGE016
In order to ensure that the number of the persons is distributed as an integer and improve the utilization rate of coach managers at the same time, the embodiment of the invention adjusts the initial distribution number of the persons to obtain the new distribution number of the persons based on the position information of each type of fitness equipment area, and the specific process is as follows:
(1) according to the floor layout diagram of the gymnasium, the gymnasium equipment area of the whole gymnasium is divided into M closed areas and 1 open area, wherein the closed area refers to each room area in the gymnasium, and the open area refers to a common area outside the room areas, and then area integration is carried out based on the position relationship of each type of gymnasium equipment area in the closed area and the open area to obtain a plurality of integration areas.
(2) Regarding the closed regions, each closed region is regarded as an integrated region
Figure 799775DEST_PATH_IMAGE017
And adding the initial distribution number corresponding to the multiple types of fitness equipment areas in the integration area to obtain the first distribution number corresponding to the integration area
Figure 751550DEST_PATH_IMAGE018
Then, the number of first distributors respectively corresponding to the M sealed areas is:
Figure 630645DEST_PATH_IMAGE019
(3) for the open area, the open area is divided into a plurality of integrated areas according to the position relation of different exercise equipment areas in the open area and the demand degree of each type of exercise equipment area.
a. The method comprises the steps of obtaining the area center point position of each type of fitness equipment area, taking any type of fitness equipment area as a center, and respectively obtaining the matching degree between the initial distribution number of people and each type of fitness equipment area in the surrounding 8 adjacent areas according to the area center point position so as to obtain the matching result with the highest matching degree.
In particular, in the following
Figure 275253DEST_PATH_IMAGE001
Exercise device area of exercise device-like
Figure 354811DEST_PATH_IMAGE020
For central, known exercise equipment area
Figure 110277DEST_PATH_IMAGE020
Location of regional center point in open area
Figure 578299DEST_PATH_IMAGE021
And corresponding initial distribution population
Figure 393808DEST_PATH_IMAGE016
. According to the area of the exercise equipment
Figure 196548DEST_PATH_IMAGE020
Initial distribution of the number of persons
Figure 755705DEST_PATH_IMAGE016
Respectively calculating the total number of the distributed people in the fitness equipment area 8 neighborhoods around the user
Figure 343812DEST_PATH_IMAGE022
Wherein
Figure 846336DEST_PATH_IMAGE023
. Obtaining the difference value of the total number of each distributor and the adjacent integers of the left and the right of the distributor
Figure 903416DEST_PATH_IMAGE024
And
Figure 141631DEST_PATH_IMAGE025
wherein
Figure 974457DEST_PATH_IMAGE024
The left difference is the difference between the left and right values,
Figure 990824DEST_PATH_IMAGE025
for the right difference, the left difference is compared
Figure 909101DEST_PATH_IMAGE024
And the difference value of right
Figure 685427DEST_PATH_IMAGE025
Get the minimum value of the two
Figure 107181DEST_PATH_IMAGE026
Meanwhile, according to the position of the central point of the area
Figure 58564DEST_PATH_IMAGE021
Separately calculating exercise device zones
Figure 198558DEST_PATH_IMAGE020
Distance from the surrounding 8 neighbourhood of the exercise equipment, i.e.
Figure 464061DEST_PATH_IMAGE027
In parallel to the distance
Figure 412425DEST_PATH_IMAGE028
Normalizing to obtain normalized value
Figure 347758DEST_PATH_IMAGE029
Combined minimum value
Figure 115994DEST_PATH_IMAGE026
And normalized value
Figure 358756DEST_PATH_IMAGE029
Separately obtaining areas of exercise equipment
Figure 879736DEST_PATH_IMAGE020
Degree of match with surrounding 8 neighbourhood fitness equipment areas, i.e.
Figure 549752DEST_PATH_IMAGE030
. Obtaining the fitness equipment area according to the maximum value of the matching degree
Figure 539705DEST_PATH_IMAGE020
The exercise device region with the highest degree of matching.
b. And respectively taking each type of fitness equipment area as a center to obtain a matching result with the highest matching degree.
c. Setting an initial integration area, wherein a fitness equipment area C with the minimum number of initial distribution persons in an open area is used as an initial integration area in the embodiment of the invention, and area integration is carried out according to different matching conditions to obtain the integration area:
first, from the initial integration area, if the matching result of the initial integration area forms a closed loop, the exercise device areas that can form the closed loop are integrated into one integration area.
As an example, if the exercise device area C and the exercise device area J are respectively the exercise device areas that are most closely matched with each other, that is, the initial integration area C and the exercise device area J form a closed loop, the exercise device area C and the exercise device area J are integrated into one integration area.
As another example, if the exercise device region C is most closely matched to the exercise device region J, the exercise device region K is most closely matched to the exercise device region J, and the exercise device region C is most closely matched to the exercise device region K, the three exercise device regions forming a closed loop are integrated into one integrated region.
Second, if the matching result of the initial integration region cannot form a closed loop, the exercise equipment regions around 8 of the initial integration region are integrated into one integration region.
As an example, for all exercise equipment areas that do not form a closed loop, the exercise equipment area located within the peripheral 8 neighborhood of exercise equipment area C is integrated with exercise equipment area C into one integrated area.
d. After the area integration is completed by taking the exercise equipment area C as the initial integration area, based on the exercise equipment area without area integration, the exercise equipment area with the minimum initial number of people is obtained again as the initial integration area, and the subsequent integration of the exercise equipment areas is performed by using the step (C).
(4) The open area can be divided into
Figure 212257DEST_PATH_IMAGE031
Each integrated area, and the sum of the initial distribution population corresponding to all the fitness equipment areas in each integrated area is used as the new distribution population of the integrated area, then
Figure 728689DEST_PATH_IMAGE031
The new number of people distributed corresponding to each integrated area is
Figure 444972DEST_PATH_IMAGE032
(5) M + can be obtained according to the region integration result of the closed region and the open region
Figure 46855DEST_PATH_IMAGE031
And each integrated area corresponds to a new distribution number.
And step S003, carrying out corresponding personnel scheduling on the coach management personnel by combining the newly distributed personnel number and the total number of the coach management personnel.
In particular, based on M +
Figure 365841DEST_PATH_IMAGE031
New distribution population pair of individual integration region
Figure 861413DEST_PATH_IMAGE014
The method for dispatching the coach managers comprises the following steps:
(1) setting a distribution number threshold value, and when the number of newly distributed persons is smaller than the distribution number threshold value, not distributing coach managers to the corresponding integration area; and for the integrated area corresponding to the distribution population threshold value, rounding off the new distribution population in the integrated area to obtain the actual distribution population of each integrated area.
Preferably, the threshold value of the number of people distributed in the embodiment of the invention is 0.5.
(2) And carrying out corresponding personnel scheduling on the coach management personnel by combining the actual number of the distributed personnel and the total number of the coach management personnel.
Specifically, the total number of predicted coaches is calculated based on the actual number of people assigned to each of the integrated areas
Figure 279756DEST_PATH_IMAGE033
Based on the predicted total number
Figure 103355DEST_PATH_IMAGE033
And the actual total number
Figure 132359DEST_PATH_IMAGE014
The actual number of people who are distributed in each integrated area is adjusted to obtain the final number of people who are distributed in each integrated area.
If the total quantity is predicted
Figure 357804DEST_PATH_IMAGE033
= actual total number of
Figure 681469DEST_PATH_IMAGE014
The actual distribution population is the final distribution population for each integration region.
If the total quantity is predicted
Figure 382577DEST_PATH_IMAGE034
Actual total number
Figure 308945DEST_PATH_IMAGE014
Then the number of unassigned trainers is
Figure 529842DEST_PATH_IMAGE035
For the integration area with the smaller number of actual distribution people during rounding up, the integration area is sorted from large to small according to the number of the actual distribution people corresponding to the rounded-up decimal, and the integration area is sorted from large to small
Figure 149042DEST_PATH_IMAGE036
The unassigned coach manager assigns to the front
Figure 838912DEST_PATH_IMAGE036
And 1 person is distributed in each integration area corresponding to the number of the points, and the final number of the distributed persons in each integration area is obtained according to the distribution result of the undistributed coaches.
If the total quantity is predicted
Figure 709916DEST_PATH_IMAGE037
Actual total number
Figure 644374DEST_PATH_IMAGE014
Then more is allocated
Figure 293530DEST_PATH_IMAGE038
The coach manager sorts the integration areas with larger actual distribution scores in rounding-off from small to large according to the decimal numbers corresponding to the actual distribution number, and the coach manager sorts the integration areas with larger actual distribution scores in front of the integration areas
Figure 844597DEST_PATH_IMAGE039
Subtracting 1 from the actual number of the distributed persons in the integration area corresponding to the number of the small persons so as to ensure that
Figure 722554DEST_PATH_IMAGE040
And then the final number of distributed persons in each integrated area is obtained by reducing the actual number of distributed persons in the integrated area.
(4) Dispatching a relative number of coach managers to the corresponding integration areas according to the final distribution number of the integration areas so as to realize
Figure 777098DEST_PATH_IMAGE014
Scheduling of individual trainer managers.
To sum up, the embodiment of the invention provides a distribution method of training managers in a gymnasium based on artificial intelligence, which detects key points of a human body of a gymnasium through a key point detection network to obtain a three-dimensional action sequence of the gymnasium, and obtains an action standard rate of using corresponding gymnasium equipment according to the three-dimensional action sequence; obtaining the demand of each type of fitness equipment area on coach management personnel according to the action standard rate, obtaining the initial number of distribution personnel required by each type of fitness equipment area according to the demand, carrying out area integration based on the position relation of each type of fitness equipment area to obtain a plurality of integration areas, and obtaining the new number of distribution personnel of each integration area by combining the integration areas and the initial number of distribution personnel; and carrying out corresponding personnel scheduling on the coach management personnel by combining the new number of the distributed personnel and the total number of the coach management personnel. Through the personnel allocation of pertinence, the rationality of personnel allocation and the utilization rate of personnel are greatly improved, the action of coach managers is fully exerted, and the body building efficiency and the body building quality of body building personnel are improved.
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent replacements, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. An artificial intelligence-based allocation method for gym coach managers, which is characterized by comprising the following steps:
acquiring a three-dimensional action sequence of a fitness person using the fitness equipment, and comparing the three-dimensional action sequence with a corresponding standard action sequence to obtain an action standard rate;
obtaining the demand degree of each type of fitness equipment area for coach managers according to the action standard rate, and obtaining the initial distribution number of people required by each type of fitness equipment area according to the demand degree; performing area integration based on the position relation of each type of fitness equipment area to obtain a plurality of integration areas, and acquiring a new number of distribution persons of each integration area by combining the integration areas and the initial number of distribution persons;
and carrying out corresponding personnel scheduling on the coaching management personnel by combining the new number of the distributed personnel and the total number of the coaching management personnel.
2. The method of claim 1, wherein said deriving a fitness equipment area requirement for a trainer manager from said action criteria rate comprises:
counting a first number of the fitness personnel using each type of the fitness equipment, and combining the action standard rate and the first number of each fitness personnel to obtain the nonstandard degree of each type of the fitness equipment when used;
and obtaining the demand degree of the fitness equipment area corresponding to the fitness equipment to the coach manager according to the nonstandard degree.
3. The method of claim 1, wherein said deriving an initial number of persons assigned to each type of said exercise equipment area based on said desirability comprises:
and multiplying the demand degree of each type of fitness equipment area by the total number of the coaches to obtain the initial distribution number of people of each type of fitness equipment area.
4. The method of claim 1, wherein the method for performing region integration based on the position relationship of each type of the key device region to obtain a plurality of integrated regions comprises:
dividing the fitness equipment area of the whole fitness room into M closed areas and 1 open area according to a floor plan of the fitness room; the closed area refers to each room area in the gymnasium, and the open area refers to a public area outside the room area;
performing zone integration based on the positional relationship of each type of exercise equipment zone in the closed zone and the open zone to obtain a plurality of the integrated zones.
5. The method of claim 4, wherein said method of zone integration based on the positional relationship of each of said exercise equipment zones in said closed zone and said open zone to obtain a plurality of said integrated zones comprises:
regarding each of the closed regions as one of the integrated regions;
for the open area, the open area is divided into a plurality of integration areas according to the position relation of different fitness equipment areas in the open area and the demand degree of each type of fitness equipment area.
6. The method of claim 5, wherein the dividing the open area into the plurality of the integrated areas comprises:
acquiring the area center point position of each type of fitness equipment area, and respectively acquiring the matching degree between the area center point position and each type of fitness equipment area in the surrounding 8 adjacent areas by taking any type of fitness equipment area as the center according to the initial distribution number of people and the area center point position so as to obtain a matching result with the highest matching degree;
setting an initial integration area, and integrating the exercise equipment areas capable of forming a closed loop into one integration area if the matching result of the initial integration area forms a closed loop from the initial integration area; integrating the exercise equipment regions in the 8 surrounding vicinity of the initial integration region into one integration region if the matching result of the initial integration region fails to form a closed loop.
7. The method of claim 6, wherein the exercise equipment area with the fewest number of initially assigned persons in the open area is the initially integrated area.
8. The method of claim 1, wherein said combining said integration area and said initial population of distributors to obtain a new population of distributors for each of said integration area comprises:
and taking the sum of the initial distribution population corresponding to all the fitness equipment areas in each integration area as the new distribution population of the integration area.
9. The method of claim 1, wherein the method of performing a corresponding staff schedule for the trainee manager in conjunction with the new allotment size and the total number of trainee managers comprises:
setting a distribution number threshold, and when the new distribution number is smaller than the distribution number threshold, not distributing the coach manager to the corresponding integration area; for the integration area corresponding to the distribution number threshold value, rounding the new distribution number in the integration area to obtain the actual distribution number of people in each integration area;
and carrying out corresponding personnel scheduling on the coach management personnel by combining the actual number of the distributed personnel and the total number of the coach management personnel.
10. The method of claim 9, wherein the method of performing a corresponding staff schedule for the trainee manager in conjunction with the actual number of people assigned and the total number of trainee managers comprises:
calculating the predicted total number of the coach managers according to the actual number of the distributed persons in each integration area, and adjusting the actual number of the distributed persons in each integration area based on the size relation between the predicted total number and the actual total number to obtain the final number of the distributed persons in each integration area;
dispatching a relative number of the trainer managers to the respective integration zones by the final number of people assigned to each of the integration zones.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115660323A (en) * 2022-10-09 2023-01-31 无锡棱光智慧物联技术有限公司 Sports facility equipment data intelligent supervision system and method based on big data

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101174346A (en) * 2006-11-01 2008-05-07 姚旺 Electric coach method and device in gymnasium
WO2014007652A2 (en) * 2012-01-19 2014-01-09 Oxenham Christine Anne Exercise information presentation system
CN107694046A (en) * 2017-07-19 2018-02-16 咪咕互动娱乐有限公司 A kind of body building training method, device and computer-readable recording medium
CN113627409A (en) * 2021-10-13 2021-11-09 南通力人健身器材有限公司 Body-building action recognition monitoring method and system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101174346A (en) * 2006-11-01 2008-05-07 姚旺 Electric coach method and device in gymnasium
WO2014007652A2 (en) * 2012-01-19 2014-01-09 Oxenham Christine Anne Exercise information presentation system
CN107694046A (en) * 2017-07-19 2018-02-16 咪咕互动娱乐有限公司 A kind of body building training method, device and computer-readable recording medium
CN113627409A (en) * 2021-10-13 2021-11-09 南通力人健身器材有限公司 Body-building action recognition monitoring method and system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115660323A (en) * 2022-10-09 2023-01-31 无锡棱光智慧物联技术有限公司 Sports facility equipment data intelligent supervision system and method based on big data
CN115660323B (en) * 2022-10-09 2024-03-08 无锡棱光智慧物联技术有限公司 Sports facility equipment data intelligent supervision system and method based on big data

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