Intelligent sports equipment management and monitoring system based on Internet of Things

Abstract

The invention relates to the technical field of the Internet of Things, and discloses an intelligent sports equipment management and monitoring system based on the Internet of Things, which comprises a state sensing tag, a self-adaptive event field generator, a state interaction terminal and a cloud cooperative control engine, the state sensing tag is installed on the equipment, receives the loss calculation protocol broadcasted by the generator, and calculates and accumulates a loss value in combination with the physical attribute of the state sensing tag and the on-site time; after the equipment is used, the terminal reads the newest loss value in the tag and uploads the newest loss value to the cloud; the cloud engine analyzes the overall equipment load of the specific area; when the load exceeds a threshold value, the engine generates and issues a new loss calculation protocol with a relatively low influence degree to the generator of the region; and the generator updates the broadcast protocol and dynamically adjusts the loss accumulation rate of the region. According to the invention, the prediction of the life cycle of the equipment and the adaptive balance of the regional use intensity are realized, and the management efficiency and safety are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to an intelligent sports equipment management and monitoring system based on the Internet of Things. Background Art

[0002] In gyms, stadiums, training centers, and other places, sports equipment like barbell plates, dumbbells, and weight racks are subjected to frequent and intensive use. The physical condition of these equipment, such as material fatigue, toughness loss, and structural wear, is directly related to user safety. Therefore, timely and effective maintenance, evaluation, and replacement of these equipment is a core and arduous task in operations management.

[0003] Currently, sports equipment management primarily relies on manual inspections and batch replacement strategies based on fixed time periods. Managers visually inspect equipment for visible physical damage like cracks and deformation, or they retire equipment after reaching a preset service life based on the purchase date. This management model has inherent and profound flaws. First, its assessment method is crude and outdated. Manual visual inspections are completely unable to detect metal fatigue or material loss accumulated within the equipment due to repeated load bearing and impact. Problems often only become apparent after the damage has become quite severe, or even after a safety incident has occurred.

[0004] Secondly, a fixed-cycle replacement strategy ignores the significant differences in equipment usage intensity. Within a venue, equipment deployed in popular strength training areas experiences significantly greater loads than similar equipment in less frequently used areas. However, a static, one-size-fits-all replacement strategy that treats all equipment equally results in some equipment being discarded long before reaching its physical lifespan, resulting in significant economic waste. Meanwhile, heavily used equipment may become a safety hazard before reaching its replacement cycle, creating a management blind spot. While existing technologies like radio frequency identification (RFID) enable rapid inventory of equipment, addressing the question of "whether it exists," they still lack an effective technical answer to the core question of "what condition" the equipment is in. Therefore, the industry urgently needs a management technology that can penetrate the surface of equipment, quantify its inherent wear and tear, and dynamically adapt to its usage environment, enabling a shift from passive, extensive management to proactive, precise, and predictive maintenance. Summary of the Invention

[0005] The technical problem to be solved by the present invention is that the existing technology usually relies on fixed maintenance cycles or passive responses after failures when managing sports equipment. It lacks an automated and quantitative loss assessment mechanism that can combine the physical properties of the equipment itself with the impact of the actual use environment. It is particularly difficult to effectively monitor the full life cycle status of a large number of passive equipment.

[0006] To solve the above technical problems, the present invention provides an intelligent sports equipment management and monitoring system based on the Internet of Things, the system comprising: At least one state-sensing tag is used to be installed on sports equipment, and its internal storage unit stores preset physical attribute parameters that characterize the inherent physical characteristics of the sports equipment, as well as a cumulative loss value for recording the degree of wear of the equipment.

[0007] At least one adaptive event field generator is deployed in a physical space, and its signal transmission module is used to periodically broadcast the loss calculation rules including the environmental impact rules to its coverage area.

[0008] The state sensing tag further includes a microprocessor, which is configured as follows: The device receives the loss calculation protocol broadcast by the adaptive event field generator via its signal receiving module, and calculates the loss increment of the sports equipment within the coverage range based on the received loss calculation protocol and the physical property parameters in its own storage unit, and updates the accumulated loss value in the storage unit according to the calculated loss increment.

[0009] In one embodiment, the physical property parameters specifically include: Material coefficient used to quantify the material's ability to resist wear and tear , and the initial toughness threshold that represents the upper limit of the initial health of the equipment .

[0010] The loss calculation protocol specifically includes: a calculation model identifier for specifying a specific algorithm for loss increment; , and one or more environmental influencing parameters that provide external variables for the algorithm .

[0011] The specific method for the microprocessor in the state perception tag to perform the loss increment calculation is: according to the calculation model identifier The specified nonlinear aging model performs the following operations: ; in, is the calculated loss increment; The duration of time the sports equipment is within the coverage area; is the accumulated loss value before the update; and is the environmental impact parameter obtained from the loss calculation protocol; is the initial toughness threshold; is the material coefficient.

[0012] In another embodiment, the system further comprises: At least one status interaction terminal is deployed at a key node of sports equipment circulation, and is configured to read the updated cumulative loss value and the physical attribute parameter in the status perception tag; The cloud-based collaborative control engine is connected to the state interaction terminal through a network.

[0013] The cloud-based collaborative control engine includes an analysis module and a control module.

[0014] The analysis module is configured as follows: Receive the accumulated loss value and initial toughness threshold of one or more equipment uploaded by the state interaction terminal, and calculate the regional load within the coverage range of the adaptive event field generator based on the accumulated loss value and initial toughness threshold.

[0015] The control module is configured as follows: The regional load calculated by the analysis module is compared with the preset adjustment strategy. When the regional load triggers the adjustment strategy, a new loss calculation protocol is generated and sent to the corresponding adaptive event field generator for updating the broadcast content.

[0016] The analysis module calculates the regional load The specific method is: ; in, is the total number of equipment within the coverage area, For the The cumulative loss value of each device, For the The initial toughness threshold of each equipment.

[0017] The technical solution provided by the present invention realizes personalized and real-time updating of the loss status of each individual device by performing loss increment calculation that integrates the physical properties of the device itself and the external environment regulations on the edge device side of the state perception tag.

[0018] Furthermore, the macro-regional load is analyzed through the cloud-based collaborative control engine, and the adaptive event field generator of the environmental definition layer is feedback-adjusted, building a closed-loop system from data collection, edge computing to cloud analysis and reverse control.

[0019] This solution can achieve dynamic and quantitative assessment of equipment loss and make adaptive adjustments based on the overall status of the system, providing technical support for predictive maintenance and refined asset management of sports equipment.

[0020] The present invention provides an intelligent sports equipment management and monitoring system based on the Internet of Things. It has the following beneficial effects: 1. This invention uses edge-side state-aware tags to independently calculate wear increments by combining their own stored physical attribute parameters representing inherent physical characteristics with wear calculation protocols acquired from the external environment. This enables precise and personalized assessment of the wear status of individual sports equipment. This approach overcomes the inability of traditional methods to distinguish between individual equipment differences and environmental influences, resulting in wear assessment results that are more closely aligned with the equipment's actual physical condition. 2. This invention utilizes a cloud-based collaborative control engine to analyze regional loads based on collected status data from multiple devices. Based on this analysis, it dynamically adjusts the loss calculation protocol broadcast by the adaptive event field generator. This design establishes a closed management loop from status monitoring to environmental control, enabling the system to transition from passive recording to active intervention, achieving adaptive and proactive management of the overall loss rate of the device resource pool. 3. This invention deploys status interaction terminals at key points in the equipment flow, collecting and uploading complete equipment status data after each use cycle. The cloud-based collaborative control engine then records this data in a lifecycle ledger established for each equipment. This ensures that data from the equipment's commissioning to its retirement is fully and systematically recorded, providing comprehensive and quantified data support for subsequent asset valuation, procurement decision optimization, and user accountability tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic structural diagram of an intelligent sports equipment management and monitoring system based on the Internet of Things according to an embodiment of the present invention; Figure 2 A schematic diagram of the internal structure of a state-aware tag according to an embodiment of the present invention; Figure 3 A schematic diagram of the internal structure of an adaptive event field generator according to an embodiment of the present invention; Figure 4 A schematic diagram of the internal structure of a status interaction terminal according to an embodiment of the present invention; Figure 5This is a schematic diagram of the functional modules of a cloud-based collaborative control engine according to an embodiment of the present invention; Figure 6 A flowchart of a method for managing and monitoring intelligent sports equipment according to an embodiment of the present invention is shown; Figure 7 The figure is a schematic diagram of the system information interaction timing according to an embodiment of the present invention.

[0022] Among them, 10. State perception tag; 11. Microprocessor; 12. Non-volatile storage unit; 13. Signal transceiver unit; 14. Power supply unit; 20. Adaptive event field generator; 21. First main control unit; 22. Signal broadcast unit; 23. Network interface unit; 24. Power supply module; 30. State interaction terminal; 31. Second main control unit; 32. Data reading module; 33. Network communication module; 34. User interaction interface; 40. Cloud collaborative control engine; 41. Data receiving and parsing module; 42. Analysis module; 43. Control module; 44. Database module. DETAILED DESCRIPTION

[0023] To make the objectives, technical solutions, and advantages of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It is apparent that the described embodiments are only some of the embodiments of the present invention, and not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0024] Refer to the attached Figure 1 , Figure 1 FIG2 is a schematic diagram of the structure of an IoT-based intelligent sports equipment management and monitoring system according to one embodiment of the present invention. The present invention provides an IoT-based intelligent sports equipment management and monitoring system, which may include: a state-sensing tag 10, an adaptive event field generator 20, a state interaction terminal 30, and a cloud-based collaborative control engine 40.

[0025] The status sensing tag 10 is designed to be physically mounted or integrated onto a piece of sports equipment. In a specific embodiment, the tag 10 comprises a microprocessor, a non-volatile memory unit, a signal transceiver unit, and a power supply unit. The memory unit pre-stores two types of core data: physical attribute parameters representing the inherent physical characteristics of the sports equipment; and cumulative wear values ​​used to record the current wear and tear of the equipment in real time.

[0026] An adaptive event field generator 20 is deployed within a specific physical space, such as a strength training area or aerobics area within a stadium. This generator 20 includes a main control unit and a signal broadcast unit. The signal broadcast unit is configured to periodically broadcast a data packet containing environmental impact rules (referred to as a loss calculation protocol in this disclosure) to its signal coverage area at a preset frequency.

[0027] In one embodiment of the present invention, the state awareness tag 10 exchanges information with the adaptive event field generator 20 .

[0028] Specifically, the signal transceiver unit of the state-aware tag 10 is used to receive the loss calculation protocol broadcast by the adaptive event field generator 20. Subsequently, the microprocessor inside the tag 10 performs a core calculation task: Based on the received loss calculation protocol and the physical property parameters stored in its own memory unit, it calculates a quantitative loss increment. After the calculation is completed, the microprocessor uses this loss increment to accumulate and update the accumulated loss value in the memory unit.

[0029] In a specific computational embodiment, the microprocessor performs a loss increment The calculation can follow the nonlinear aging model as follows: ; in: Indicates the loss increment obtained from this calculation; Indicates the duration that the state awareness tag 10 is within the signal coverage of the adaptive event field generator 20; Indicates the accumulated loss value stored in the state sensing tag 10 before executing this calculation; Represents the initial toughness threshold stored in the physical property parameters, which represents the upper limit of the initial health of the equipment; Represents the material coefficient stored in the physical property parameters, which is used to quantify the wear resistance of the core material of the equipment; 、 Represents the environmental impact parameter parsed from the loss calculation protocol, and its value is determined by the physical characteristics of the current environment.

[0030] The status interaction terminal 30 is deployed at key physical nodes where sports equipment circulates, such as entrances and exits of a sports venue or equipment storage areas. This terminal 30 is equipped with a data reading module. When sports equipment with a status sensing tag 10 passes through its effective range, the data reading module is triggered to read the complete data stored in the status sensing tag 10's internal storage unit. This data includes at least the updated cumulative wear value and physical attribute parameters.

[0031] In addition, the status interaction terminal 30 also includes a network communication module for uploading the read data to the cloud collaborative control engine 40.

[0032] The cloud-based collaborative control engine 40 is composed of software modules deployed on a remote server, and establishes communication connections with the state interaction terminal 30 and the adaptive event field generator 20 via a network. The cloud-based collaborative control engine 40 includes an analysis module and a control module.

[0033] The analysis module receives and processes data uploaded from one or more status interaction terminals 30. Based on these data, the analysis module evaluates the system status within the coverage area of ​​a specific adaptive event field generator 20, specifically calculating the regional load within the coverage area.

[0034] In one embodiment, the area load is calculated as follows: ; in, is the total number of equipment in the area, For the region The cumulative loss value of each device, For the The initial toughness threshold of each equipment.

[0035] The control module compares the regional load calculated by the analysis module with a preset regulation strategy. If the comparison triggers the regulation strategy (for example, if the regional load exceeds a preset threshold), the control module generates a new loss calculation protocol. This new loss calculation protocol is then transmitted via the network to the corresponding adaptive event field generator 20. Upon receipt, the adaptive event field generator 20 adopts the new loss calculation protocol for subsequent broadcasts. Through this path, the system forms a complete closed loop from data collection, edge computing, cloud-based analysis, to environmental feedback control.

[0036] Refer to the attached Figure 2 , Figure 2FIG. 1 is a schematic diagram of the internal structure of a state sensing tag 10 according to an embodiment of the present invention. In a specific embodiment, the hardware structure of the state sensing tag 10 may include a microprocessor 11 , a non-volatile storage unit 12 , a signal transceiver unit 13 , and a power supply unit 14 .

[0037] The microprocessor 11 is the computing and control core of the state sensing tag 10 , which is used to execute preset instruction programs, manage the work of other hardware units inside the tag, and perform the core loss increment calculation task.

[0038] The non-volatile storage unit 12 is electrically connected to the microprocessor 11 and is used to persistently store data without external power. In one embodiment, the storage unit 12 can be implemented using flash memory, ferroelectric random access memory (FRAM), or electrically erasable programmable read-only memory (EEPROM) to meet application requirements for low power consumption and multiple erase and write cycles. The data structure stored in the storage unit 12 specifically includes physical property parameters and accumulated loss values.

[0039] Physical attribute parameters are a set of data written when the tag is initialized, which are used to uniquely describe the inherent characteristics of the sports equipment it is attached to. This parameter set may include: Globally unique identifier , an identity code assigned to each sports equipment that is not repeated in the system; Equipment physical category , used to identify the type of equipment, for example, the code corresponds to a barbell, dumbbell or yoga mat; Material coefficient This is a dimensionless value that is calibrated based on the material mechanical properties of the core components of the equipment (such as metal, rubber, composite fiber, etc.) and pre-stored. It is used to quantify the anti-aging and anti-wear capabilities of different materials in loss calculations; Initial toughness threshold , which is a preset value that defines the total amount of cumulative wear and tear that the device is designed to withstand, and serves as a baseline for judging the health status and relative degree of aging of the device; Manufacturing timestamp , records the production or activation date of the equipment.

[0040] Accumulated loss value It is a dynamically updated value stored in the non-volatile storage unit 12, and its initial value is zero. Whenever the microprocessor 11 completes a loss increment calculation, it will perform a local update operation: The microprocessor 11 reads the current accumulated loss value from the storage unit 12, performs an addition operation on the newly calculated loss increment, and then writes the operation result back to the same address in the storage unit 12 to overwrite the old value.

[0041] Signal transceiver unit 13 is electrically connected to microprocessor 11 and is used to implement wireless communication between status awareness tag 10 and external devices. In one embodiment, unit 13 can be a Bluetooth Low Energy (BLE) module configured to operate in listening mode to receive the loss calculation protocol broadcast by adaptive event field generator 20 and pass the received data to microprocessor 11 for processing.

[0042] Power supply unit 14 provides the necessary power for all electronic components within status sensing tag 10. In one embodiment, power supply unit 14 can be a long-life button cell or thin-film battery. In another embodiment, it can also integrate an energy harvesting module, such as one that harvests energy from ambient vibration or light, to extend the tag's overall operating life.

[0043] Refer to the attached Figure 3 , Figure 3 FIG2 is a schematic diagram of the internal structure of an adaptive event field generator 20 according to an embodiment of the present invention. In a specific embodiment, the adaptive event field generator 20 is fixedly deployed in a specific physical area, and its hardware structure may include a first main control unit 21, a signal broadcast unit 22, a network interface unit 23, and a power supply module 24.

[0044] The first main control unit 21, which can be, for example, a microcontroller (MCU) or an embedded system core board, is electrically connected to the signal broadcast unit 22 and the network interface unit 23. The first main control unit 21 is used to manage and control the operation of the entire generator 20. Its core function is to generate or update the loss calculation protocol based on instructions received from the network interface unit 23 or according to its internal preset configuration, and to provide this protocol data to the signal broadcast unit 22 for broadcast.

[0045] Signal broadcast unit 22, under the control of first main control unit 21, continuously broadcasts wireless signals to the surrounding area at a preset power and time interval. In one embodiment, unit 22 can be a Bluetooth Low Energy (BLE) radio frequency front-end, and the signals it broadcasts are BLE advertising packets. The loss calculation protocol is based on the core data carried in these advertising packets.

[0046] The data structure of the loss calculation protocol is organized into a standardized format to facilitate parsing by the state awareness tag 10. The data structure may specifically include: Protocol Identifier , a unique code assigned to the currently broadcast protocol, used for version control or to distinguish different protocols; Computational model identification , which is a specific value or code corresponding to one or more loss calculation algorithms preset in the status sensing tag 10. For example, the code "0x01" may correspond to the aforementioned nonlinear aging model, while the code "0x02" may correspond to a simplified linear accumulation model; Environmental Impact Parameter Set , which is an ordered set of one or more values, identified by the computational model The specified calculation formula provides external variables. For example, in the aforementioned nonlinear aging model, the parameter set includes the environmental impact parameters and Specific value of .

[0047] In a specific embodiment of the present invention, the environmental impact parameter set Parameters in and With detailed physical meaning: parameter It is defined as the basic environmental loss coefficient, and its value is associated with the static properties of the physical area where the adaptive event field generator 20 is deployed. For example, at the initial stage of system deployment, the cloud collaborative control engine 40 will assign an initial Value: Generators deployed in free weight areas (where barbells and dumbbells are frequently used and equipment is at risk of falling) The value is set to a higher value (such as 0.8); while the generator deployed in, for example, a yoga stretching area (where equipment is used gently) The value is set to a low value (such as 0.2).

[0048] parameter It is defined as a dynamic intensity adjustment factor, and its value is calculated and updated in real time or quasi-real time by the cloud collaborative control engine 40 based on dynamic data. The value of is positively correlated with the equipment turnover rate in the area. The cloud collaborative control engine 40 calculates the equipment turnover rate by analyzing the number of data entries uploaded by the status interaction terminals 30 in the area within a specific time window (for example, the past hour). The higher the turnover rate, the greater the usage intensity of the area, and the cloud collaborative control engine 40 will calculate and issue a higher value. , so when calculating the loss increment, the existing loss The amplification effect is stronger, which is in line with the physical law that high-intensity use will accelerate the loss of aging parts.

[0049] In a specific implementation, the above data structure is encoded and placed in the Manufacturer Specific Data field of the BLE advertising packet. For example, the first few bytes can be used to define the manufacturer ID and data type, and the following byte is used to store the calculation model identifier. The next few bytes store the environmental impact parameter set in order. In this way, any state-aware tag 10 within the coverage area can efficiently obtain and parse the complete loss calculation protocol by scanning the BLE broadcast channel.

[0050] The network interface unit 23 provides the adaptive event field generator 20 with the ability to remotely communicate with the cloud-based collaborative control engine 40. In one embodiment, the unit 23 may be a Wi-Fi module or an Ethernet interface controller. The network interface unit 23 continuously maintains a network connection with the cloud-based collaborative control engine 40 and receives control instructions from the latter.

[0051] The adaptive characteristics of the adaptive event field generator 20 are achieved through the collaborative work of the network interface unit 23 and the first main control unit 21. When the cloud-based collaborative control engine 40 decides based on its analysis results that the environmental impact of a certain area needs to be adjusted, it will send a control instruction containing a new loss calculation protocol to the adaptive event field generator 20 deployed in the area through the network. After receiving the instruction, the network interface unit 23 passes it to the first main control unit 21. The first main control unit 21 then updates its internally stored loss calculation protocol and instructs the signal broadcast unit 22 to use this new protocol data for broadcasting in subsequent broadcast cycles, thereby achieving dynamic and remote adjustment of the definition of physical environmental impact.

[0052] The power supply module 24 provides a stable working power supply for the adaptive event field generator 20. Since it is fixedly deployed, in one embodiment, the power supply module 24 can be directly connected to the mains and power each internal unit through a power adapter.

[0053] Refer to the attached Figure 4 , Figure 4 Figure 3 is a schematic diagram of the internal structure of a state interaction terminal 30 according to one embodiment of the present invention. In one specific embodiment, the state interaction terminal 30 is fixedly deployed at a key location where sports equipment undergoes state transitions, such as at the equipment storage check-in / check-out window or at the entrance or exit of a training area. Its hardware architecture includes a second main control unit 31, a data reading module 32, a network communication module 33, and a user interface 34.

[0054] The second main control unit 31 , which may be a microcontroller or an embedded microcomputer, serves as the control core of the status interaction terminal 30 , is responsible for scheduling and managing the coordination of other modules, and performing preliminary processing and packaging of data.

[0055] The data reading module 32 is electrically connected to the second main control unit 31 and is used to establish a communication link with the state awareness tags 10 within its near-field communication range and extract data. In one embodiment, this module 32 may be a Bluetooth Low Energy (BLE) transceiver. Unlike the one-way broadcast of the adaptive event field generator 20, the data reading module 32 is configured to actively scan and identify nearby state awareness tags 10. When it detects that the signal strength (RSSI) of a state awareness tag 10 exceeds a preset near-field threshold, the data reading module 32 will send a data read request to the state awareness tag 10.

[0056] In response to the data read request, the state-aware tag 10 sends the complete state data packet in its storage unit 12 to the data reading module 32. The data packet includes but is not limited to the global unique identifier of the tag. , its complete set of physical property parameters, and its latest accumulated loss value that has been updated locally multiple times After receiving the data packet, the data reading module 32 forwards it to the second main control unit 31 .

[0057] Under the control of the second main control unit 31, the network communication module 33 establishes a secure data connection between the status interaction terminal 30 and the remote cloud-based collaborative control engine 40. In one embodiment, the module 33 can be an Ethernet interface, a Wi-Fi module, or a cellular network module (such as 4G / LTE).

[0058] After receiving the tag's status data packet from the data reading module 32, the second master control unit 31 performs a data encapsulation operation. This operation specifically involves appending a millisecond-accurate timestamp generated by the terminal itself, as well as a terminal ID identifying the terminal's physical location, to the main data packet. The second master control unit 31 then uploads this encapsulated synchronization data packet, containing complete information, to the designated data interface of the cloud-based collaborative control engine 40 via the network communication module 33.

[0059] The user interface 34 is connected to the second main control unit 31 and is used to provide immediate feedback to users on-site. In one embodiment, the user interface 34 may include an LED status indicator and a buzzer. For example, when data is successfully read and uploaded, the second main control unit 31 may control the green LED to light up and trigger a short buzzer to emit a beep, confirming to the user that the equipment borrowing or returning operation has been successfully recorded.

[0060] Refer to the attached Figure 5 , Figure 5 Figure 4 is a functional module diagram of a cloud-based collaborative control engine 40 according to one embodiment of the present invention. In one specific embodiment, the cloud-based collaborative control engine 40 comprises a set of collaborative software modules deployed on one or more remote servers. These modules may include a data receiving and parsing module 41, an analysis module 42, a control module 43, and a database module 44.

[0061] The data receiving and parsing module 41 is the external data interface of the cloud collaborative control engine 40. The data receiving and parsing module 41 continuously monitors the designated network port to receive synchronization data packets uploaded via the network from one or more state interaction terminals 30. After receiving the data packet, the data receiving and parsing module 41 first verifies its validity, such as checking the data format and integrity, and then performs parsing operations to accurately extract each data field from the data packet, such as the globally unique identifier of the state perception tag 10. , its physical property parameter set, the latest accumulated loss value After the parsing is completed, the data receiving and parsing module 41 forwards the structured data to the database module 44.

[0062] The database module 44 provides persistent data storage and management capabilities for the system. In one embodiment, the database module 44 can be a relational database or a time series database. One of its core functions is to identify each sports equipment in the system based on its globally unique identifier. , establish and maintain an independent lifecycle ledger. This ledger records all state changes of the equipment since it was put into use in chronological order.

[0063] Specifically, every time the database module 44 receives a new structured data from the data receiving and parsing module 41, it will Locate the corresponding lifecycle ledger and append the data as a new entry. Each entry contains the cumulative loss value of the synchronization , a snapshot of physical attribute parameters, as well as the timestamp and physical location of the synchronization (reflected by the terminal ID). In this way, a traceable record of the status of each device throughout its life cycle is achieved.

[0064] The analysis module 42 is used to perform system-level status assessment tasks. This analysis module 42 is configured to run according to a preset time period (e.g., once every hour) or when triggered by a specific event (e.g., a sudden increase in the frequency of equipment borrowing and returning in a certain area). During operation, the analysis module 42 initiates a data query request to the database module 44 to obtain the latest status data of all sports equipment within a specific physical area (i.e., the area covered by a specific adaptive event field generator 20), primarily their cumulative wear and tear values. and initial toughness threshold .

[0065] After obtaining the required data, the analysis module 42 performs regional load The calculation method is detailed in the above formula, which takes the current relative loss of all equipment in the area as After the calculation is completed, the analysis module 42 will obtain the regional load value. Output to the control module 43.

[0066] Control module 43 is the decision-making and execution unit that implements the system's adaptive closed-loop regulation. It stores one or more preset regulation strategies. Each strategy defines one or more regional load thresholds and the corresponding actions to be taken when the regional load reaches these thresholds.

[0067] The control module 43 receives the regional load value output by the analysis module 42 Then, compare it with the preset adjustment strategy. If a certain threshold is exceeded, the corresponding adjustment action is triggered. The action is specifically: the control module 43 generates a new loss calculation protocol. In one embodiment, the generation process can be: while maintaining the calculation model identifier Under the same conditions, the environmental impact parameter set is reduced according to the preset rules Parameter values ​​in (for example, and After generating the new loss calculation protocol, the control module 43 encapsulates it into a control instruction and sends it to the adaptive event field generator 20 corresponding to the regional load through the network to instruct it to update the broadcast content.

[0068] In a specific embodiment, the regulation strategy stored in the control module 43 is a set of multi-level threshold response mechanisms. This mechanism is based on the regional load calculated by the analysis module 42. Values ​​define different response levels: Safety zone: When When , the control module 43 determines that the overall health status of the equipment in the current area is good and does not perform any adjustment operation.

[0069] Warning and moderate adjustment range: When , the control module 43 is triggered. It will generate a new loss calculation rule, the dynamic strength adjustment factor in the rule The value of is adjusted down by 20% (for example, from 1.0 to 0.8). The control module 43 then sends this new protocol to the corresponding adaptive event field generator 20. This operation is intended to proactively slow the average aging rate of equipment across the entire region by reducing the acceleration of loss accumulation.

[0070] High load and strong regulation range: when When the control module 43 performs a stronger adjustment action, the new loss calculation protocol it generates not only includes the dynamic strength adjustment factor Reduce by 40%, and also reduce the basic environmental loss coefficient When issuing this new regulation, the control module 43 will also send a high-level alert to the system management backend, suggesting that the management personnel conduct a physical inspection or rotation maintenance of the sports equipment in the area.

[0071] Refer to the attached Figure 6 and Figure 7 , Figure 6 is a flow chart of a method for managing and monitoring intelligent sports equipment according to an embodiment of the present invention. Figure 7 1 is a schematic diagram of the system information interaction sequence according to an embodiment of the present invention. The method is accomplished through the collaborative work of the state perception tag 10, the adaptive event field generator 20, the state interaction terminal 30, and the cloud collaborative control engine 40. In a specific application scenario, the method may include the following steps: S100: Calculation and accumulation of edge-side loss status.

[0072] This step is performed at the physical location of the state awareness tag 10. When a piece of sports equipment equipped with the state awareness tag 10 enters the physical area defined by the adaptive event field generator 20, the microprocessor 11 inside the state awareness tag 10 starts to execute a series of operations.

[0073] First, during its operation, the signal transceiver unit 13 of the state sensing tag 10 continuously receives the loss calculation protocol broadcast by the adaptive event field generator 20. The microprocessor 11 parses the received protocol data and extracts the calculation model identifier. and environmental impact parameter sets At the same time, the microprocessor 11 maintains an internal timer to record the duration of the tag 10 staying in the area. .

[0074] Next, the microprocessor 11 reads the pre-stored physical property parameters of the device from the non-volatile storage unit 12, including the material coefficient and initial toughness threshold , and read the currently stored accumulated loss value .

[0075] Then, the microprocessor 11 identifies the calculated model according to the analysis , call the corresponding calculation formula, and all the parameters obtained above, including duration , Current accumulated loss value , material coefficient , initial toughness threshold and environmental impact parameters As input variable, perform a loss increment This operation process is completely completed locally on the tag 10.

[0076] Finally, after calculating the loss increment After that, the microprocessor 11 immediately performs a local data update, and adds the increment to the current accumulated loss value read. The accumulated loss value is added and written back to the non-volatile storage unit 12. This series of operations (receiving, calculating, updating) can be performed periodically while the equipment is in the area, thereby achieving real-time and dynamic accumulation of the equipment loss status.

[0077] S200: Execute synchronization and upload of status data.

[0078] This step is performed at the status interaction terminal 30. When the sports equipment is moved into the effective communication range of the status interaction terminal 30 after use, for example, returned to the equipment rack or taken out of the training area exit, this step is triggered.

[0079] After the data reading module 32 of the state interaction terminal 30 detects the state perception tag 10, it actively initiates a data reading communication. After receiving the request, the state perception tag 10 stores the complete data stored in its internal non-volatile storage unit 12, including its globally unique identifier. , a complete set of physical property parameters and the latest accumulated loss value after the S100 step update , packaged and sent to the status interaction terminal 30.

[0080] After receiving the data packet, the second main control unit 31 of the status interaction terminal 30 appends additional information to it, including the precise timestamp of the data synchronization and the terminal's own geographic location identifier. The second main control unit 31 then instructs its network communication module 33 to upload this fully encapsulated synchronization data packet to the cloud-based collaborative control engine 40 via the network.

[0081] S300: Execute cloud-based analysis and adaptive feedback control.

[0082] This step is performed in the cloud collaborative control engine 40. The data receiving and parsing module 41 of the cloud collaborative control engine 40 receives and parses the synchronization data packet uploaded in step S200, and stores the parsed structured data in the corresponding equipment lifecycle account book in the database module 44.

[0083] The analysis module 42 of the cloud-based collaborative control engine 40 is activated according to a preset strategy (e.g., at regular intervals). Upon activation, the analysis module 42 queries the database module 44 for the latest status data of all equipment within a specific physical area and calculates the overall load value of the area based on the aforementioned regional load calculation formula. .

[0084] Then, the analysis module 42 calculates the regional load value The value is passed to the control module 43. The control module 43 compares the value with the internally stored adjustment strategy threshold. If the value does not exceed the threshold, no action is taken. If the value exceeds the threshold, it indicates that the overall equipment loss rate in the area is too high and intervention is required.

[0085] If intervention is required, the control module 43 will generate a new loss calculation rule. For example, it can generate an environmental impact parameter Finally, control module 43 sends this new loss calculation protocol over the network to the adaptive event field generator 20 deployed in the physical area. Upon receiving the new protocol, the generator 20 immediately begins broadcasting it, thereby reducing the cumulative loss rate for equipment subsequently entering the area. This completes a complete closed-loop collaborative control process from the edge to the cloud and back to the edge.

[0086] The following describes a specific application example to illustrate the actual application process of the technical solution disclosed in the present invention. This example describes the deployment and operation process of the system of the present invention in a barbell plate management scenario in a university gymnasium.

[0087] Example: Phase 1: System initialization and deployment The gymnasium manager initializes and configures a batch of new, 20-kilogram barbell plates. Using a dedicated programming device, the manager writes the initial physical property parameters to the state-sensing tag 10 attached to each barbell plate. For example, for one barbell plate (numbered B-20KG-077), the data written into its non-volatile storage unit 12 includes: a globally unique identifier (ID) of "B-20KG-077"; a material coefficient of is 1.5 (this is a pre-calibrated value based on its high-density rubber material); initial toughness threshold is 80000. At the same time, its cumulative loss value The initial value is set to 0. After the writing is completed, the state sensing tag 10 is embedded into the inner side of the center hole of the barbell plate.

[0088] In the strength training area of ​​the gymnasium, the management deployed an adaptive event field generator 20 and connected its network interface unit 23 to the gymnasium's wired network. The initial broadcast content of the generator 20, namely the loss calculation protocol, is set to a default value by the cloud collaborative control engine 40, where the calculation model identifier "0x01", environmental impact parameter set Medium parameters is 0.8, parameter is 1.1.

[0089] At the entrance to the strength training area, the administrator installs a status interaction terminal 30, which is also connected to the gymnasium network.

[0090] Phase 2: Single use and data update process A student takes a barbell plate numbered "B-20KG-077" from storage and enters the strength training area. The state-aware tag 10 on the barbell plate then enters the signal coverage of the adaptive event field generator 20 and begins receiving the loss calculation protocol broadcast by it.

[0091] The student trained in this area for 45 minutes (2700 seconds). During this period, the microprocessor 11 of the state perception tag 10 performed a loss increment calculation. It read the data from its own storage unit 12. 、 、 , and combined with parameters received from the outside , and the duration of this stay , perform the operation. After the operation is completed, the loss increment will be calculated The updated new accumulated loss value is added to the original accumulated loss value 0, and the updated new accumulated loss value is written back to its non-volatile storage unit 12.

[0092] After training, the student leaves the strength training area carrying the weights and passes through the state interaction terminal 30 at the entrance. As the weights pass by, the data reading module 32 of the state interaction terminal 30 initiates a data read request to the weights' state sensing tag 10 and retrieves complete state data, including its latest accumulated wear value. The state interaction terminal 30 appends this data with the current timestamp and the terminal ID "Door-Terminal-02," and then uploads it to the cloud-based collaborative control engine 40 via the network.

[0093] Phase 3: Cloud-based analysis and adaptive adjustment process After receiving the data, the cloud-based collaborative control engine 40 records it in the lifecycle ledger of the barbell plate numbered "B-20KG-077". After running for a period of time, the analysis module 42 of the cloud-based collaborative control engine 40 is triggered to start analyzing the overall status of the strength training area.

[0094] The analysis module 42 queries the database and obtains the latest status of all barbell plates with usage records in the area. The calculation formula is calculated and the result is 0.72. The control module 43 compares this result with the preset adjustment strategy, which stipulates that when When it exceeds 0.7, the environmental impact level needs to be lowered.

[0095] The condition is triggered. The control module 43 immediately generates a new loss calculation protocol, in which the calculation model identifier Keep "0x01" unchanged, but the environment affects the parameter set The parameters in are adjusted to and Subsequently, the control module 43 sends the instruction containing the new protocol to the adaptive event field generator 20 deployed in the strength training area through the network.

[0096] Upon receiving the command, the adaptive event field generator 20 immediately updates its broadcast wear calculation protocol to the newly received version. Thereafter, any additional wear calculations for any equipment entering the strength training area will be based on this adjusted, less impactful protocol. This process fully embodies the closed-loop mechanism of the present invention, from individual status monitoring to macro-environmental feedback regulation.

[0097] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. The intelligent sports equipment management and monitoring system based on the Internet of Things is characterized by: include: At least one state-sensing tag, the state-sensing tag being used to be mounted on sports equipment and storing therein preset physical attribute parameters characterizing inherent physical characteristics of the sports equipment, as well as a cumulative wear value for recording the degree of wear of the equipment; At least one adaptive event field generator is deployed in the physical space and is used to periodically broadcast the loss calculation rules including the environmental impact rules to its coverage area; The state awareness tag is further configured as follows: Receive the loss calculation protocol broadcast by the adaptive event field generator, and based on the received loss calculation protocol and the physical property parameters stored in itself, calculate the loss increment of the sports equipment within the coverage range, and update the accumulated loss value stored internally according to the loss increment.

2. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 1 is characterized in that: The physical property parameters include: The material coefficient used to quantify the material's ability to resist wear and tear, and the initial toughness threshold that represents the upper limit of the equipment's initial health.

3. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 2 is characterized in that: The loss calculation protocol includes: A calculation model identifier for specifying a specific algorithm for loss increment, and a set of environmental impact parameters that provide external variables for the algorithm.

4. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 3 is characterized in that: The state-aware tag is specifically configured to calculate the loss increment using the following nonlinear aging model: ； in, is the loss increment, is the duration of time the sports equipment is within the coverage area, and is a parameter in the environmental impact parameter set, is the accumulated loss value before updating, is the initial toughness threshold, is the material coefficient.

5. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 1 is characterized in that: The system further comprises: At least one status interaction terminal, deployed at a key node in the circulation of sports equipment, for reading the updated cumulative loss value in the status perception tag; The cloud-based collaborative control engine is connected to the state interaction terminal for receiving the accumulated loss value uploaded by the state interaction terminal.

6. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 5 is characterized in that: The state interaction terminal is specifically configured as follows: Read the complete set of physical property parameters stored in the state perception tag, and upload the complete set to the cloud collaborative control engine.

7. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 5 is characterized in that: The cloud-based collaborative control engine is further configured to: Calculating the regional load of all equipment within the coverage area of ​​the adaptive event field generator based on the accumulated loss values ​​received from one or more status interaction terminals; When the regional load triggers a preset adjustment strategy, a new loss calculation protocol is generated and sent to the corresponding adaptive event field generator for updating broadcast content.

8. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 7 is characterized in that: The cloud-based collaborative control engine is specifically configured to calculate the regional load using the following formula: ； in, is the total number of equipment in the area, For the The cumulative loss value of each device, For the The initial toughness threshold of each equipment.

9. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 7, characterized in that: The cloud-based collaborative control engine generates the new loss calculation protocol, specifically including: While maintaining the calculation model identifier in the loss calculation protocol unchanged, the parameter values ​​in the environmental impact parameter set are adjusted.

10. The intelligent sports equipment management and monitoring system based on the Internet of Things according to claim 5 is characterized in that: The cloud-based collaborative control engine is further configured to: A life cycle account book is established for each sports equipment, and the accumulated loss value and related information received from the status interaction terminal each time are recorded in the corresponding life cycle account book.

Images