Fitness equipment management method and system based on Internet of Things

Abstract

The invention is suitable for the technical field of fitness equipment management, and particularly relates to a fitness equipment management method and system based on the Internet of Things, and the method comprises the steps: delimiting a use scene of fitness equipment, setting a distribution rule of Bluetooth equipment, building a one-to-one correspondence relationship between a user and the Bluetooth equipment, and carrying out the one-to-one correspondence relationship between the user and the Bluetooth equipment; the method comprises the following steps: acquiring Bluetooth beacon signals of Bluetooth equipment by using a plurality of signal receivers pre-deployed in a use scene, and calculating a real-time position of a user through a multilateral positioning algorithm; editing a use rule of the fitness equipment, and segmenting the use scene into a plurality of sub-regions. By sending the recommendation information to the user, the fitness experience and efficiency of the user can be remarkably improved, the user is prevented from waiting for a long time due to the fact that common equipment is occupied after the user arrives at a use scene, the fitness efficiency of the user is greatly improved, digital and intelligent operation of the use scene is effectively promoted, and the user experience is improved. And meanwhile, transition from a passive registration mode to active perception is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fitness equipment management, and particularly relates to a fitness equipment management method and system based on Internet of Things. BACKGROUND

[0002] Fitness equipment management refers to the process of scheduling, monitoring and data analysis of all fitness equipment in a gym or sports venue.

[0003] However, in the existing fitness equipment management, manual or code scanning registration methods are generally used. First, since users need to manually scan the equipment two-dimensional code for check-in before each use of the fitness equipment, the operation is cumbersome, and the experience is poor. Especially during peak hours, it will cause queuing and resource waste. Second, the code scanning method cannot judge whether the fitness equipment is actually used in real time, and cannot distinguish multiple users in the same area, which is easy to cause data deviation of "scanned code but not actually used", affecting the statistical accuracy. In addition, manual or code scanning registration methods completely rely on user active operation. If the user forgets or does not want to register, the real use record cannot be obtained. Finally, the code scanning method lacks self-identification ability, and cannot combine user identity, use behavior and equipment state to control the fitness equipment, resulting in low overall intelligent level of fitness equipment management.

[0004] Therefore, how to use the Bluetooth beacon signal to digitally manage the fitness equipment is a technical problem to be solved by the present application. SUMMARY

[0005] The present application aims to provide a fitness equipment management method and system based on Internet of Things to solve the problem of "how to use the Bluetooth beacon signal to digitally manage the fitness equipment" in the background art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions: A fitness equipment management method based on Internet of Things, the method comprising: Delimiting the use scene of the fitness equipment, setting the distribution rule of the Bluetooth device, establishing the one-to-one correspondence between the user and the Bluetooth device, using a plurality of signal receivers pre-deployed in the use scene to collect the Bluetooth beacon signal of the Bluetooth device, and calculating the real-time position of the user through the multilateral positioning algorithm. editing the use rule of the fitness equipment, dividing the use scene into a plurality of sub-regions, wherein each fitness equipment corresponds to a sub-region, when the real-time position enters the sub-region, collecting the use data of the fitness equipment by using the Internet of Things device embedded in the fitness equipment in advance, and sending the use data to the user terminal corresponding to the Bluetooth device, wherein the use data at least includes training behavior data, generation time and end time, verifying the real-time position by using the use data, collecting the current state of the fitness equipment, and constructing a use state table; generating a fitness event with the generation time and the end time as endpoints, creating a plurality of blocks corresponding to the fitness equipment one by one, writing the use data of each fitness equipment in the fitness event into the blocks, and sorting the blocks according to the generation time, and integrating to generate a data chain; when the real-time Bluetooth beacon signal of the user is monitored, finding out the data chain corresponding to the user, popping up the block at the top of the data chain and defining it as a target block, querying the use state table to determine whether the fitness equipment corresponding to the target block is all used, if yes, continuing to determine the blocks after the target block in the data chain, if no, reading the attribute data of the fitness equipment corresponding to the target block and writing it into a preset template to generate recommendation information and send it to the user terminal, and building a reservation management mechanism.

[0007] Further, the step of collecting the Bluetooth beacon signal of the Bluetooth device by using a plurality of signal receivers deployed in the use scene comprises: editing the use method of the Bluetooth device, finding out the display device in the use scene, and sending the use method to the display device; reading the unique identifier in the Bluetooth beacon signal, collecting the communication information of the user, and establishing the correspondence between the communication information and the unique identifier.

[0008] Further, the step of editing the use rule of the fitness equipment and dividing the use scene into a plurality of sub-regions comprises: collecting multi-source data in the use scene, wherein the multi-source data at least includes WIFI signal and video monitoring data, and cross-verifying the real-time position; calculating the use frequency of each sub-region through the fitness event, and adjusting the deployment position of the signal receiver.

[0009] Further, the step of collecting the use data of the fitness equipment and sending it to the user terminal corresponding to the Bluetooth device comprises: constructing a feature set composed of a plurality of risk features, wherein each fitness equipment corresponds to a feature set, and determining whether there is a risk feature in the use data; Corresponding to the risk characteristics, a treatment rule is configured, an edge device in a use scene is located, and the risk characteristics and the treatment rule are written into the edge device.

[0010] Further, the step of writing the use data of each fitness equipment in the fitness event into the blocks and sorting according to the generation time to integrate to generate the data chain comprises: From the data chain, key features are extracted, wherein the key features at least include: intermittent duration and repetition times, training preferences are generated, and a user portrait is drawn; Receiving a training target uploaded by a user, activating a pre-constructed reminder strategy via the key features.

[0011] Further, the step of querying the use state table to determine whether the fitness equipment corresponding to the target block is all used comprises: The reservation management mechanism is integrated into the edge device; A feedback interface is written into the recommendation information to generate a reservation record, wherein the reservation record at least includes: a unique identifier and a reservation time, and the control authority of the fitness equipment is opened to the edge device.

[0012] Further, the system comprises: A calculation module is configured to delimit a use scene of the fitness equipment, set a distribution rule of the Bluetooth device, establish a one-to-one correspondence between the user and the Bluetooth device, collect a Bluetooth beacon signal of the Bluetooth device by using a plurality of signal receivers pre-deployed in the use scene, and calculate a real-time position of the user by using a multi-lateral positioning algorithm; An editing module is configured to edit a use rule of the fitness equipment, divide the use scene into a plurality of sub-regions, wherein each fitness equipment corresponds to a sub-region, collect use data of the fitness equipment by using an Internet of Things device pre-embedded in the fitness equipment when the real-time position enters the sub-region, and send the use data to a user terminal corresponding to the Bluetooth device, wherein the use data at least includes: training behavior data, generation time and end time, verify the real-time position by using the use data, collect a current state of the fitness equipment, and construct a use state table; An integration module is configured to generate a fitness event with the generation time and the end time as endpoints, create a plurality of blocks corresponding to the fitness equipment one by one, write the use data of each fitness equipment in the fitness event into the blocks, and sort according to the generation time to integrate to generate a data chain; The construction module is used for finding out the data chain corresponding to the user after monitoring the real-time Bluetooth beacon signal of the user, popping up a number of blocks in the data chain in the first order, defining the target block, inquiring the use state table, judging whether the fitness equipment corresponding to the target block is all used, if yes, continuing to judge the number of blocks after the target block in the data chain, if not, reading the attribute data of the fitness equipment corresponding to the target block and writing into the preset template to generate the recommendation information and send to the user terminal, and constructing the reservation management mechanism.

[0013] Further, the calculation module comprises: The editing unit is used for editing the use method of the Bluetooth device, finding out the display device in the use scene and sending the use method to the display device. The establishment unit is used for reading the unique identifier in the Bluetooth beacon signal, collecting the communication information of the user and establishing the corresponding relationship between the communication information and the unique identifier.

[0014] Further, the editing module comprises: The verification unit is used for collecting multi-source data in the use scene, wherein the multi-source data at least comprises WIFI signal and video monitoring data, and cross verifying the real-time position. The adjustment unit is used for calculating the use frequency of each sub-region via the fitness event and adjusting the deployment position of the signal receiver. The judgment unit is used for constructing a feature set composed of a plurality of risk features, wherein each fitness equipment corresponds to a feature set, and judging whether the risk feature exists in the use data. The configuration unit is used for configuring the disposal rule corresponding to the risk feature one by one, positioning the edge device in the use scene and writing the risk feature and the disposal rule into the edge device.

[0015] Further, the integration module comprises: The construction unit is used for extracting the key feature from the data chain, wherein the key feature at least comprises intermittent duration and repetition times, generating the training preference and drawing the user portrait. The receiving unit is used for receiving the training target uploaded by the user and activating the pre-constructed reminding strategy via the key feature.

[0016] Compared with the prior art, the present application has the following beneficial effects: By determining the real-time position of the user, the flow density of people in the use scene can be monitored and dynamically managed in real time, and the appearance of personnel congestion and idle fitness equipment can be avoided. By collecting use data, automatic matching of the user and the use of the fitness equipment can be realized, and the tedious process of manual registration or code scanning confirmation is avoided, which greatly improves the intelligence and convenience of the fitness experience. By constructing a data chain, the equipment use order, training combination and movement rhythm of the user in a single exercise can be clearly reflected, thereby providing a data basis for user fitness plan adjustment, equipment scheduling and maintenance. By sending recommended information to the user, the user's fitness experience and efficiency can be significantly improved, the user can avoid long waiting time after reaching the use scene due to the occupation of commonly used equipment, the user's fitness efficiency is greatly improved, and the digital and intelligent operation of the use scene is effectively promoted, and the transition from passive registration mode to active perception is realized. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 A flow chart of a fitness equipment management method based on the Internet of Things is provided for the embodiment of the present application. Figure 2 A first sub-flow chart of a fitness equipment management method based on the Internet of Things is provided for the embodiment of the present application. Figure 3 A second sub-flow chart of a fitness equipment management method based on the Internet of Things is provided for the embodiment of the present application. Figure 4 A third sub-flow chart of a fitness equipment management method based on the Internet of Things is provided for the embodiment of the present application. Figure 5 A fourth sub-flow chart of a fitness equipment management method based on the Internet of Things is provided for the embodiment of the present application. Figure 6 A composition chart of a fitness equipment management system based on the Internet of Things is provided for the embodiment of the present application. Figure 7 A composition chart of a computing module in a fitness equipment management system based on the Internet of Things is provided for the embodiment of the present application. Figure 8 A composition chart of an editing module in a fitness equipment management system based on the Internet of Things is provided for the embodiment of the present application. Figure 9 A composition chart of an integration module in a fitness equipment management system based on the Internet of Things is provided for the embodiment of the present application. Figure 10 A composition chart of a construction module in a fitness equipment management system based on the Internet of Things is provided for the embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and not to limit the present application.

[0019] In Example 1, Figure 1 The implementation flow of the body-building equipment management method based on the Internet of Things is shown, and the following is described in detail as follows. S100: The use scenario of the body-building equipment is delimited, the distribution rule of the Bluetooth device is set, the one-to-one correspondence between the user and the Bluetooth device is established, the Bluetooth beacon signal of the Bluetooth device is collected by using a plurality of signal receivers pre-deployed in the use scenario, and the real-time position of the user is calculated by using a multilateral positioning algorithm.

[0020] The use scenario of the body-building equipment is delimited, which can be a gym or other shared fitness place. The distribution rule of the Bluetooth device is formulated, wherein the Bluetooth device is a wearable Bluetooth device, and the user can tie the Bluetooth device to the shoelace or the trouser leg. This wearing mode is mainly to position the user without affecting the user's fitness. The user refers to the fitness personnel in the gym. The distribution rule refers to: setting a unique digital number for each Bluetooth device, and distributing the Bluetooth devices in turn according to the order of the users. When the user enters the use scenario, the one-to-one correspondence between the user and the Bluetooth device is established by using the user's fitness record, consumption record or pre-registered information, so as to quickly and accurately identify the user's identity after receiving the Bluetooth beacon signal.

[0021] The signal receivers are deployed in the use scenario. The signal receivers can collect the Bluetooth beacon signal in the Bluetooth device worn on the user's shoelace or trouser leg in real time. Each signal receiver records the strength of the Bluetooth signal, the receiving time and the unique identifier in the Bluetooth device, and combines the multilateral positioning algorithm in the prior art to calculate the real-time position of the user in the use scenario. It should be noted that the positioning accuracy requirement here does not need to be too high, and the meter-level positioning accuracy can meet the use requirement. In the subsequent data processing process, the user's position is verified by using the use data of the body-building equipment.

[0022] S200: The use scenario is divided into a plurality of sub-areas, wherein each body-building equipment corresponds to a sub-area. When the real-time position enters the sub-area, the use data of the body-building equipment is collected by using the Internet of Things device pre-embedded in the body-building equipment, and is sent to the user terminal corresponding to the Bluetooth device. The use data at least includes: training behavior data, generation time and end time. The real-time position is verified by using the use data, the current state of the body-building equipment is collected, and the use state table is constructed.

[0023] According to the type, function and placement position of the fitness equipment, the use scene is divided into several sub-regions, each sub-region corresponds to a fitness equipment, and the boundary of each sub-region is determined; when the user enters a certain sub-region, the corresponding fitness equipment is found out, and the Internet of Things device in the fitness equipment is activated, wherein the Internet of Things device can be a rotating speed sensor, an angle sensor and a pressure sensor, etc., and should also include a communication module and a vibration feedback module, etc.; the use data of the fitness equipment is collected by using the Internet of Things device, wherein the use data includes training behavior data, generation time and end time, etc., the training behavior data includes repetition times and movement amplitude, etc., the real-time position of the user is verified by using the use data; the current state of the fitness equipment is collected, such as idle, in use or in maintenance, and a use state table is constructed, wherein the use state table is composed of the current state and the Bluetooth beacon signal of the user, and the use state table is mainly used to reflect the current use of each fitness equipment.

[0024] For example, when the real-time position of the user is located in the sub-region corresponding to the fitness equipment A, and it is monitored that A has generated use data at the same time, it indicates that the user is using A; the use state table is constructed by using the Bluetooth beacon signal of the user and the current state (in use).

[0025] S300: generating a fitness event with the generation time and the end time as endpoints, creating a number of blocks corresponding to the fitness equipment one by one, writing the use data of each fitness equipment in the fitness event into the blocks, and sorting according to the generation time to integrate and generate a data chain.

[0026] A time window is constructed with the generation time as the starting point and the end time as the endpoint, the time window and the corresponding training behavior data are integrated, a fitness event is generated, each fitness process of the user corresponds to a fitness event, and the fitness event is also a complete record of the fitness process of the user. A number of blocks corresponding to each fitness equipment are created, wherein the blocks are logical nodes and not physical devices, and a small amount of data can be stored in the blocks, that is, each block records the use information of a single fitness equipment in the fitness event; in the fitness event, the use data of each fitness equipment is written into the blocks, and all the blocks are sorted according to the order of use of the fitness equipment (i.e. the generation time), to generate a data chain, wherein the data chain is also a set obtained by arranging the blocks in the order of use, similar to the queue in the prior art. Since the user may use different fitness equipment in each fitness event, and the order of use may also be different, in other words, each user may correspond to multiple data chains.

[0027] S400: After detecting the user's real-time Bluetooth beacon signal, it finds the data chain corresponding to the user, pops out the first and first blocks in the data chain and defines them as target blocks, queries the usage status table to determine whether all the fitness equipment corresponding to the target block is used. If so, it continues to check the blocks after the target block in the data chain. If not, it reads the attribute data of the fitness equipment corresponding to the target block and writes it into a preset template, generates recommendation information, sends it to the user terminal, and builds a reservation management mechanism.

[0028] When a signal receiver detects a user's real-time Bluetooth beacon signal, it indicates that the user is about to enter the usage scenario. Signal receivers can be deployed outside the usage scenario area or along the user's route. By collecting Bluetooth beacon signals from the user's mobile terminal, the user's movement and entry time can be detected in advance, allowing the user to better plan their fitness program.

[0029] Once the user's real-time Bluetooth beacon signal is detected, it indicates that the user is about to enter a usage scenario. All data chains corresponding to the user are located, and the top-ranked blocks are identified and defined as target blocks. These target blocks represent the fitness equipment the user first used in previous fitness events. The number of target blocks is the same as the number of data chains; there can be one or more. The usage status is checked to determine if the fitness equipment corresponding to the aforementioned target blocks is currently in use. If all are in use, the system checks if the fitness equipment corresponding to the second-ranked blocks in the data stack is also in use. If there are multiple target blocks and the corresponding fitness equipment is not in use, attribute data of the fitness equipment is collected, including equipment type, functional characteristics, applicable training movements, and load levels. This data is written into a preset recommendation information template to generate recommendation information. This recommendation information is then sent to the corresponding user terminal (the user's mobile terminal) via the communication link between the user and the edge device. A reservation management mechanism for the fitness equipment is established, receiving user reservation records and scheduling and managing the usage of the fitness equipment according to time sequence.

[0030] In Example 2, Figure 2 The present invention illustrates the implementation flow of an IoT-based fitness equipment management method according to an embodiment of the present invention. The following details the steps of collecting Bluetooth beacon signals from Bluetooth devices using several signal receivers pre-deployed in the usage scenario: S101: Edit the usage method of the Bluetooth device, find the display device in the usage scenario, and send the usage method to the display device.

[0031] The use method of the Bluetooth device is determined, wherein the use method can be tied on a shoelace, or connected on clothes of the user through sticking, magnetic attraction or the like, a display device in the use scene is found out, wherein the display device can be a display screen in the use scene, or a user terminal, and the use method is sent to the display device.

[0032] S102: read the unique identifier in the Bluetooth beacon signal, collect the communication information of the user, and establish the correspondence between the communication information and the unique identifier.

[0033] When the signal receiver receives the Bluetooth beacon signal of the user, the unique identifier in the Bluetooth beacon signal is read out, and the correspondence between the communication information and the unique identifier is established according to the communication information reserved by the user before the start of the fitness activity, wherein the communication information mainly includes a contact number; by establishing the correspondence between the communication information and the unique identifier, the corresponding user can be locked, and the quick delivery of the recommendation information can be realized.

[0034] In embodiment 3, Figure 3 The implementation process of the fitness equipment management method based on the Internet of Things is shown, and the steps of editing the use rules of the fitness equipment and dividing the use scene into a plurality of sub-regions are described in detail as follows: S201: collect multi-source data in the use scene, wherein the multi-source data at least includes WIFI signals and video monitoring data, and the real-time position is cross-verified.

[0035] When the user is positioned, in addition to being able to refer to the Bluetooth beacon signal, the real-time position of the user can also be verified by using multi-source data, and the multi-source data includes WIFI signals and video monitoring data; the advantage of this way is that the accuracy of the real-time position of the user can be greatly improved.

[0036] S202: calculate the use frequency of each sub-region via the fitness event, and adjust the deployment position of the signal receiver.

[0037] The fitness equipment used in each fitness event is recorded, the use frequency of each sub-region in a preset period is calculated, the deployment position of the signal receiver is adjusted according to the use frequency; for example, more signal receivers can be deployed near the sub-region with higher use frequency.

[0038] In embodiment 4, Figure 3 The implementation process of the fitness equipment management method based on the Internet of Things is shown, and the steps of collecting the use data of the fitness equipment and sending the use data to the user terminal corresponding to the Bluetooth device are described in detail as follows: S203: Construct a feature set composed of a plurality of risk features, wherein each fitness equipment corresponds to a feature set, and it is judged whether the risk features exist in the use data.

[0039] A feature set composed of a plurality of risk features is constructed for each fitness equipment, and the risk features include: equipment use anomaly (such as continuous overtime occupation), use mode anomaly (action use error), and equipment state anomaly (sensor data anomaly).

[0040] S204: Configure a disposal rule corresponding to each risk feature, locate an edge device in the use scene, and write the risk features and the disposal rule into the edge device.

[0041] A corresponding disposal rule is set for each risk feature, an edge device in the use scene is located, and the edge device can be an edge server, a computing box, and other devices with data processing capabilities, etc. The risk features and the disposal rule are written into the edge device for storage. This method has the advantages of: it can greatly improve the real-time performance and response speed of risk feature monitoring and disposal.

[0042] In embodiment 5, Figure 4 The implementation flow of the fitness equipment management method based on the Internet of Things is shown, and the step of writing the use data of each fitness equipment in the fitness event into a plurality of blocks, sorting according to the generation time, and integrating to generate a data chain is described in detail as follows: S301: Extract key features from the data chain, wherein the key features at least include: intermittent duration and repetition times, generate training preferences, and draw a user portrait.

[0043] The key features are extracted from the data chain, and the key features include: intermittent duration and repetition times, etc. The intermittent duration can show the rest time and training rhythm of the user between different fitness equipment, and the repetition times reflect the training intensity and endurance level of the user in each group of actions. The key features are used to generate training preferences, such as: high-intensity short-intermittent training or low-intensity long-intermittent training, etc., and a user portrait is drawn. The user portrait is a digital display method of the training preferences.

[0044] S302: Receive the training target uploaded by the user, and activate the pre-constructed reminding strategy via the key features.

[0045] Receiving a user uploaded training target, the training target should include: training duration, equipment usage frequency and the number of specific fitness actions completed, etc.;Using key features, dynamically match and analyze the training target, and real-time evaluate the gap between the user's current training state and the training target.;In the user's fitness process, activate the reminder strategy, where the reminder strategy refers to using a loudspeaker, a vibration sensor, etc. to real-time remind the user of the number of completed fitness actions and the training duration, etc.

[0046] In embodiment 6, Figure 5 The query usage state table is shown, and the step of determining whether the target block corresponds to all used fitness equipment is described in detail as follows: S401: integrate the reservation management mechanism into the edge device.

[0047] The reservation management mechanism is integrated into the edge device, and the reservation management mechanism refers to: a specific reservation method of the fitness equipment, which can be realized through a reservation platform or a short message, etc. to arrange the time of the fitness equipment.

[0048] S402: write a feedback interface into the recommendation information to generate a reservation record, wherein the reservation record at least includes: a unique identifier and a reservation time, and open the control authority of the fitness equipment to the edge device.

[0049] The feedback interface is written into the recommendation information, and the user uploaded reservation record is received through the feedback interface. The reservation record should include: a unique identifier and a reservation time, and open the control authority of the corresponding fitness equipment to the edge device. For example, when it is detected that the reservation time has arrived and the unique identifier of the user is identified, the edge device powers on and initializes the fitness equipment, so that the user can safely use the fitness equipment in the reservation order.

[0050] Figure 6 The composition structure block diagram of the fitness equipment management system based on the Internet of Things is shown, and the fitness equipment management system based on the Internet of Things 1 includes: The computing module 11 is used for delimiting the use scene of the fitness equipment, setting the distribution rule of the Bluetooth device, establishing the one-to-one correspondence between the user and the Bluetooth device, collecting the Bluetooth beacon signal of the Bluetooth device by using a plurality of signal receivers deployed in the use scene, and calculating the real-time position of the user through the multilateral positioning algorithm. The editing module 12 is used for editing the use rules of the fitness equipment, cutting the use scene into a plurality of sub-regions, wherein each fitness equipment corresponds to a sub-region, when the real-time position enters the sub-region, the use data of the fitness equipment is collected by using the Internet of Things device embedded in the fitness equipment in advance, and is sent to the user terminal corresponding to the Bluetooth device, wherein the use data at least includes: training behavior data, generation time and end time, the real-time position is verified by using the use data, the current state of the fitness equipment is collected, and a use state table is constructed; The integration module 13 is used for generating a fitness event with the generation time and the end time as end points, creating a plurality of blocks corresponding to the fitness equipment one by one, writing the use data of each fitness equipment in the fitness event into the blocks, and sorting according to the generation time, and integrating to generate a data chain; The construction module 14 is used for finding out the data chain corresponding to the user after monitoring the real-time Bluetooth beacon signal of the user, popping up the block at the first position in the data chain and defining as a target block, querying the use state table, judging whether the fitness equipment corresponding to the target block is all used, if yes, continuing to judge the blocks after the target block in the data chain, if no, reading the attribute data of the fitness equipment corresponding to the target block and writing into a preset template, generating recommendation information, sending to the user terminal, and constructing a reservation management mechanism.

[0051] Figure 7 The composition structure block diagram of the fitness equipment management system based on the Internet of Things is shown, and the calculation module 11 includes: The editing unit 111 is used for editing the use method of the Bluetooth device, finding out the display device in the use scene, and sending the use method to the display device; The establishment unit 112 is used for reading the unique identifier in the Bluetooth beacon signal, collecting the communication information of the user, and establishing the corresponding relationship between the communication information and the unique identifier.

[0052] Figure 8 The composition structure block diagram of the fitness equipment management system based on the Internet of Things is shown, and the editing module 12 includes: The verification unit 121 is used for collecting a plurality of source data in the use scene, wherein the plurality of source data at least includes: WIFI signal and video monitoring data, and cross verifying the real-time position; The adjustment unit 122 is used for calculating the use frequency of each sub-region through the fitness event, and adjusting the deployment position of the signal receiver; The judgment unit 123 is used for constructing a feature set composed of a plurality of risk features, wherein each fitness equipment corresponds to a feature set, and judging whether the risk features exist in the use data; The configuration unit 124 is configured to configure a treatment rule corresponding to a risk feature, position an edge device in a use scene, and write the risk feature and the treatment rule into the edge device.

[0053] Figure 9 The application provides a fitness equipment management system based on an Internet of Things, and a component structure block diagram of the fitness equipment management system is shown. The component unit 131 is configured to extract key features from the data chain, wherein the key features at least include an intermittent duration and a repetition number, generate a training preference, and draw a user portrait. The receiving unit 132 is configured to receive a training target uploaded by a user, and activate a pre-constructed reminding strategy via the key features.

[0054] Figure 10 The application provides a fitness equipment management system based on an Internet of Things, and a component structure block diagram of the fitness equipment management system is shown. The integration unit 141 is configured to integrate the reservation management mechanism into an edge device. The writing unit 142 is configured to write a feedback interface into recommended information, generate a reservation record, and open a control right of the fitness equipment to the edge device, wherein the reservation record at least includes a unique identifier and a reservation time.

[0055] The calculation module 11 is mainly configured to complete the step S100, the editing module 12 is mainly configured to complete the step S200, the integration module 13 is mainly configured to complete the step S300, and the construction module 14 is mainly configured to complete the step S400. The editing unit 111 is mainly configured to complete the step S101, and the establishing unit 112 is mainly configured to complete the step S102. The verification unit 121 is mainly configured to complete the step S201, the adjustment unit 122 is mainly configured to complete the step S202, the judgment unit 123 is mainly configured to complete the step S203, and the configuration unit 124 is mainly configured to complete the step S204. The component unit 131 is mainly configured to complete the step S301, and the receiving unit 132 is mainly configured to complete the step S302. The integration unit 141 is mainly configured to complete the step S401, and the writing unit 142 is mainly configured to complete the step S402.

[0056] The technical features of the above-described embodiments can be combined in any manner, and for the sake of brevity, all possible combinations of the technical features in the above-described embodiments are not described, however, as long as the combinations of the technical features do not contradict each other, they should be considered as the scope of the present disclosure.

[0057] The above embodiments only express several implementation manners of the present application, which are described in a more specific and detailed manner, but should not be understood as a limitation on the patent scope of the present application. It should be noted that, for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, which are all within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

[0058] The above merely describes the preferred embodiments of the present application and should not be used to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for managing fitness equipment based on the Internet of Things, characterized in that, The method includes: Define the usage scenarios of fitness equipment, set the allocation rules for Bluetooth devices, establish a one-to-one correspondence between users and Bluetooth devices, and use several signal receivers pre-deployed in the usage scenarios to collect Bluetooth beacon signals from Bluetooth devices. Then, calculate the user's real-time location using a multi-directional positioning algorithm. Edit the usage rules of the fitness equipment, divide the usage scenario into several sub-areas, where each piece of fitness equipment corresponds to a sub-area. When the real-time location enters a sub-area, use the IoT device pre-embedded in the fitness equipment to collect the usage data of the fitness equipment and send it to the user terminal corresponding to the Bluetooth device. The usage data includes at least: training behavior data, generation time and end time. Use the usage data to verify the real-time location, collect the current status of the fitness equipment, and construct a usage status table. Using the generation and end times as endpoints, a fitness event is generated, and a data block is created that corresponds one-to-one with the fitness equipment. The usage data of each piece of fitness equipment in the fitness event is written into the data block, sorted according to the generation time, and integrated to generate a data chain. Once the user's real-time Bluetooth beacon signal is detected, the data chain corresponding to the user is located, the top and bottom blocks in the data chain are popped out and defined as target blocks, the usage status table is queried to determine whether all the fitness equipment corresponding to the target block is used, if so, the data chain is further checked for the blocks after the target block, if not, the attribute data of the fitness equipment corresponding to the target block is read and written into a preset template, recommendation information is generated, sent to the user terminal, and a reservation management mechanism is built.

2. The fitness equipment management method based on the Internet of Things according to claim 1, characterized in that, The step of collecting Bluetooth beacon signals from Bluetooth devices using several signal receivers pre-deployed in the usage scenario includes: Edit the usage instructions for the Bluetooth device, locate the display device in the usage scenario, and send the usage instructions to the display device; Read the unique identifier in the Bluetooth beacon signal, collect the user's communication information, and establish a correspondence between the communication information and the unique identifier.

3. The fitness equipment management method based on the Internet of Things according to claim 1, characterized in that, The steps of editing the usage rules for fitness equipment and dividing the usage scenario into several sub-regions include: Collect multi-source data within the usage scenario, wherein the multi-source data includes at least: WIFI signal and video surveillance data, and perform cross-validation on the real-time location; Based on the fitness events, the usage frequency of each sub-region is calculated, and the deployment location of the signal receiver is adjusted.

4. The IoT-based fitness equipment management method according to claim 2, characterized in that, The step of collecting usage data from the fitness equipment and sending it to the user terminal corresponding to the Bluetooth device includes: Construct a feature set consisting of several risk features, where each piece of fitness equipment corresponds to a feature set, and determine whether there are risk features in the usage data; Configure handling rules that correspond one-to-one with risk characteristics, locate edge devices within the usage scenario, and write the risk characteristics and handling rules into the edge devices.

5. The IoT-based fitness equipment management method according to claim 1, characterized in that, The steps of writing the usage data of each piece of fitness equipment in a fitness event into several blocks, sorting them according to the time of generation, and integrating them to generate a data chain include: From the data chain, key features are extracted, wherein the key features include at least: interval duration and repetition count, training preferences are generated, and user profiles are drawn; The system receives training objectives uploaded by users and activates pre-built reminder strategies based on the key features.

6. The fitness equipment management method based on the Internet of Things according to claim 4, characterized in that, The step of querying the usage status table to determine whether all the fitness equipment corresponding to the target block is in use includes: Integrate the aforementioned appointment management mechanism into edge devices; Write feedback into the recommendation information to generate a reservation record, wherein the reservation record includes at least: a unique identifier and a reservation time, and grant control permissions to the fitness equipment to the edge device.

7. A fitness equipment management system based on the Internet of Things, characterized in that, The system includes: The calculation module is used to define the usage scenarios of fitness equipment, set the allocation rules of Bluetooth devices, establish a one-to-one correspondence between users and Bluetooth devices, and use several signal receivers pre-deployed in the usage scenarios to collect Bluetooth beacon signals of Bluetooth devices and calculate the user's real-time location through a multi-directional positioning algorithm. The editing module is used to edit the usage rules of the fitness equipment, dividing the usage scenario into several sub-regions, where each piece of fitness equipment corresponds to a sub-region. When the real-time location enters a sub-region, the IoT device pre-embedded in the fitness equipment is used to collect the usage data of the fitness equipment and send it to the user terminal corresponding to the Bluetooth device. The usage data includes at least: training behavior data, generation time and end time. The real-time location is verified using the usage data, the current status of the fitness equipment is collected, and a usage status table is constructed. The integration module is used to generate fitness events with the generation time and end time as endpoints, create data blocks that correspond one-to-one with fitness equipment, write the usage data of each piece of fitness equipment in the fitness event into the data blocks, sort them according to the generation time, and integrate them to generate a data chain. The module is used to locate the user's corresponding data chain after detecting the user's real-time Bluetooth beacon signal, pop the top and bottom blocks in the data chain and define them as target blocks, query the usage status table to determine whether all the fitness equipment corresponding to the target block is used. If so, it continues to check the blocks after the target block in the data chain. If not, it reads the attribute data of the fitness equipment corresponding to the target block and writes it into a preset template, generates recommendation information, sends it to the user terminal, and builds a reservation management mechanism.

8. The IoT-based fitness equipment management system according to claim 7, characterized in that, The computing module includes: The editing unit is used to edit the usage method of the Bluetooth device, locate the display device in the usage scenario, and send the usage method to the display device; The establishment unit is used to read the unique identifier in the Bluetooth beacon signal, collect the user's communication information, and establish the correspondence between the communication information and the unique identifier.

9. The IoT-based fitness equipment management system according to claim 8, characterized in that, The editing module includes: The verification unit is used to collect multi-source data within the usage scenario, wherein the multi-source data includes at least: WIFI signals and video surveillance data, and to cross-verify the real-time location. An adjustment unit is used to calculate the usage frequency of each sub-region based on the fitness events and to adjust the deployment location of the signal receiver. The judgment unit is used to construct a feature set consisting of several risk features, wherein each fitness equipment corresponds to a feature set, and to determine whether there are risk features in the usage data; The configuration unit is used to configure the handling rules that correspond one-to-one with the risk characteristics, locate the edge devices in the usage scenario, and write the risk characteristics and handling rules into the edge devices.

10. The IoT-based fitness equipment management system according to claim 7, characterized in that, The integration module includes: The assembly unit is used to extract key features from the data chain, wherein the key features include at least: interval duration and repetition count, generate training preferences, and draw user profiles; The receiving unit is used to receive the training objectives uploaded by the user and activate the pre-built reminder strategy through the key features.

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