Guitar humidity automatic detection and adjustment system, method and device and storage medium

Abstract

The embodiment of the invention provides a guitar humidity automatic detection and adjustment system, method and device and a storage medium, and the system comprises a detection module which is configured to detect humidity data in a guitar; the transmission setting module is configured to communicate with a user terminal, receive a humidity threshold value set by a user and transmit humidity data; the execution module comprises a humidifying bin, a drying agent bin and a driving mechanism, and the driving mechanism is configured to control opening and closing of the humidifying bin and the drying agent bin; and the control module is configured to control the humidifying bin and / or the drying agent bin through the driving mechanism according to the humidity data and the humidity threshold value so as to adjust the humidity in the guitar to be within a target range limited by the humidity threshold value.

Description

Technical Field

[0001] This specification relates to the field of environmental control, and in particular to an automatic humidity detection and regulation system, method, apparatus and storage medium for guitars. Background Technology

[0002] With the rapid growth in the ownership of high-end wooden musical instruments, users are paying increasing attention to the stability of tone and service life. Wooden stringed instruments such as guitars are extremely sensitive to the humidity of the storage environment: excessive humidity can easily cause the soundboard to swell and the glue joints to crack; excessive humidity will cause the wood to shrink, the fingerboard to deform, and the pitch to drift.

[0003] Traditional maintenance methods mainly rely on a "passive + manual" approach: an individual humidifier or desiccant is placed in the instrument case, and the user periodically (usually 1-2 times a week) takes out the instrument, observes the humidity indicator reading based on experience, and then manually adds or removes consumables or adjusts the ambient air conditioning. This process is fragmented, slow to respond, and easily misses the optimal intervention window; moreover, the diffusion rate varies greatly between different types of wood (veneer / plywood) and different brands of consumables, making it impossible for humans to quantify "when to replace" or "how much to use," often resulting in double waste of "prematurely discarding" or "using expired consumables"; frequent unpacking itself disrupts the microclimate stability and increases the user's time cost, leading to low actual implementation rates, with the instrument remaining in an overly humid or overly dry state for a long time.

[0004] Therefore, it is desirable to provide a guitar humidity automatic detection and adjustment system, method, device and storage medium that can automate humidity detection, lifespan prediction, humidification / dehumidification execution and consumable degradation calibration in a closed loop: to achieve precise lifespan management that "makes the most of its capabilities" and "does not fail", and to solve the problems of relying on experience, lack of quantification and delayed response. Summary of the Invention

[0005] This specification provides one or more embodiments of an automatic humidity detection and adjustment system for guitars. The system includes: a detection module configured to detect humidity data inside the guitar; a transmission setting module configured to communicate with a user terminal, receive a humidity threshold set by the user, and transmit the humidity data; an execution module including a humidification chamber, a desiccant chamber, and a drive mechanism, the drive mechanism being configured to control the opening and closing of the humidification chamber and the desiccant chamber; and a control module configured to control the humidification chamber and / or the desiccant chamber through the drive mechanism based on the humidity data and the humidity threshold, so as to adjust the humidity inside the guitar to a target range defined by the humidity threshold.

[0006] This specification provides one or more embodiments of an automatic humidity detection and adjustment method for a guitar. The method includes: detecting humidity data inside the guitar; communicating with a user terminal to receive a humidity threshold set by the user and transmitting the humidity data; and controlling a humidification chamber and / or a desiccant chamber via a drive mechanism based on the humidity data and the humidity threshold to adjust the humidity inside the guitar to a target range defined by the humidity threshold.

[0007] This specification provides one or more embodiments of an automatic guitar humidity detection and adjustment device, the device including at least one processor and at least one memory; the at least one memory is used to store computer instructions; the at least one processor is used to execute at least a portion of the computer instructions to implement the automatic guitar humidity detection and adjustment method.

[0008] This specification provides one or more embodiments of a computer-readable storage medium that stores computer instructions that, when executed by a processor, implement a method for automatically detecting and adjusting the humidity of a guitar. Attached Figure Description

[0009] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein: Figure 1 This is a schematic diagram illustrating an application scenario of an automatic humidity detection and adjustment system for guitars, based on some embodiments of this specification. Figure 2 This is an exemplary schematic diagram of an automatic humidity detection and adjustment system for guitars, as shown in some embodiments of this specification; Figure 3 This is an exemplary flowchart of a method for automatically detecting and adjusting guitar humidity according to some embodiments of this specification; Figure 4 These are exemplary schematic diagrams illustrating preventative adjustments according to some embodiments of this specification; Figure 5 This is an exemplary schematic diagram illustrating the determination of preventative adjustment parameters according to some embodiments of this specification. Detailed Implementation

[0010] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0011] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0012] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0013] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0014] Figure 1 This is a schematic diagram illustrating an application scenario of an automatic humidity detection and adjustment system for guitars, based on some embodiments of this specification.

[0015] In some embodiments, such as Figure 1 As shown, the application scenario 100 of the guitar humidity automatic detection and adjustment system (hereinafter referred to as application scenario) may include a guitar 110, a user terminal 120, an adjustment device 130, a network 140, a processor 150, and a storage device 160.

[0016] In some embodiments, the application scenario 100 of the guitar humidity automatic detection and adjustment system may include scenarios where a guitar is needed, such as music festivals, live performances, and personal instrument practice.

[0017] One or more components of application scenario 100 can transmit data to other components of application scenario 100 via network 140. For example, processor 150 can obtain data from guitar 110, user terminal 120, adjustment device 130 and storage device 160 via network 140, or send data to user terminal 120, adjustment device 130 and storage device 160 via network 140.

[0018] In some embodiments, the processor 150 can acquire humidity data from the regulating device 130 via the network 140, as well as information on consumable consumption in the regulating device 130 via the network 140. It can also acquire environmental data, guitar data, etc., from the user terminal 120 via the network 140. The processor 150 can send the generated preventative adjustment parameters to the regulating device via the network 140.

[0019] Guitar 110 refers to a stringed instrument used for performance. In some embodiments, because the guitar 110 has a hollow internal structure, different humidity environments can affect the pitch and timbre of the guitar 110.

[0020] User terminal 120 refers to one or more terminal devices or software used by a user. In some embodiments, user terminal 120 may include one or any combination of other devices with input and / or output functions, such as mobile phone 121, tablet 122, and computer 123.

[0021] In some embodiments, the user terminal 120 can interact with other components (such as the processor 150) in the application scenario 100 of the guitar humidity automatic detection and adjustment system via the network 140. For example, the processor 150 can send consumable replacement reminders to the user terminal 120 via the network 140. The user can send guitar data, environmental data, etc., to the processor 150 via the user terminal 120. The above examples are only used to illustrate the breadth of the user terminal 120 device and are not intended to limit its scope.

[0022] In some embodiments, the user terminal 120 may include an APP for interacting with the user.

[0023] The regulating device 130 refers to a device used to regulate the humidity inside the guitar 110. In some embodiments, the regulating device 130 may include a humidification chamber, a desiccant chamber, a humidity sensor, a desiccant, humidifying materials, etc.

[0024] In some embodiments, the processor 150 can control the humidification chamber and desiccant chamber to open and close the regulating device 130, thereby regulating the humidity inside the guitar 110.

[0025] In some embodiments, the regulating device 130 may be integrated into the guitar humidity automatic detection and regulating system 200. For a description of the guitar humidity automatic detection and regulating system 200, please refer to... Figure 2 The corresponding content.

[0026] Network 140 may include any suitable network capable of facilitating information and / or data exchange. In some embodiments, at least one component of application scenario 100 (e.g., guitar 110, user terminal 120, control device 130, processor 150, storage device 160, etc.) may exchange information and / or data with at least one other component in application scenario 100 via network 140. For example, processor 150 may send a consumable replacement reminder to user terminal 120 via network 140. As another example, processor 150 may obtain data (e.g., humidity data) from control device 130 via network 140. Yet another example, a user may send a humidity threshold from user terminal 120 to processor 150 via network 140.

[0027] In some embodiments, network 140 can be any one or more of wired or wireless networks. For example, network 140 may include cable networks, fiber optic networks, telecommunications networks, the Internet, local area networks (LANs), wide area networks (WANs), wireless local area networks (WLANs), metropolitan area networks (MANs), public switched telephone networks (PSTNs), Bluetooth networks, ZigBee networks, near field communication (NFC), device internal buses, device internal wiring, cable connections, etc., or any combination thereof.

[0028] Processor 150 can process data and / or information obtained from other devices or system components. Based on this data, information, and / or processing results, the processor can execute program instructions to perform one or more functions described in this specification.

[0029] In some embodiments, the processor 150 can communicate with the user terminal 120 to receive a humidity threshold set by the user and humidity data transmitted by the adjustment device 130; based on the humidity data and humidity threshold, the processor 150 controls the adjustment device 130 (humidification chamber and / or desiccant chamber) through a drive mechanism to adjust the humidity inside the guitar to the target range defined by the humidity threshold.

[0030] In some embodiments, processor 150 may include one or more sub-processing devices (e.g., a single-core processing device or a multi-core multi-chip processing device). By way of example only, processor 140 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction processor (ASIP), a graphics processing unit (GPU), a physical processor (PPU), a digital signal processor (DSP), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, or any combination thereof.

[0031] Storage device 160 can be used to store data and / or instructions. Data refers to the digital representation of information and can include various types, such as binary data, text data, image data, video data, etc. Instructions refer to programs that control devices or components to perform specific functions. For example, storage device 160 can store humidity thresholds set by the user on user terminal 120, humidity data acquired by regulating device 130, and control instructions sent to regulating device 130 from the processor 150's history.

[0032] Storage device 160 may include one or more storage components, each of which may be a separate device or part of another device. In some embodiments, storage device 160 may include random access memory (RAM), read-only memory (ROM), mass storage, removable memory, volatile read-write memory, and any combination thereof. In some embodiments, storage device 160 may be implemented on a cloud platform.

[0033] For more information on the above components, please refer to [link / reference]. Figures 2-5 And its related descriptions.

[0034] It should be noted that the application scenario 100 of the guitar humidity automatic detection and adjustment system is provided for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can make various modifications or variations based on the description in this specification. However, such modifications and variations will not depart from the scope of this specification.

[0035] Figure 2 This is an exemplary schematic diagram of an automatic humidity detection and adjustment system for guitars, as shown in some embodiments of this specification.

[0036] In some embodiments, such as Figure 2 As shown, the guitar humidity automatic detection and adjustment system 200 (hereinafter referred to as the detection and adjustment system 200) may include a detection module 210, a transmission setting module 220, an execution module 230 and a control module 240.

[0037] In some embodiments, some or all of the transmission setting module 220 and control module 240 may be integrated into the processor and communicate with the processor.

[0038] In some embodiments, the detection module 210 can be configured to detect humidity data inside the guitar. The detection module 210 may include a high-precision humidity sensor.

[0039] The installation location of the humidity sensor can be set according to requirements. Understandably, the humidity sensor should be installed in a position that allows it to fully contact the air environment inside the guitar to ensure the accuracy of the detection data and provide a reliable basis for subsequent humidity adjustment.

[0040] In some embodiments, the transmission setting module 220 can be configured to communicate with a user terminal, receive a humidity threshold set by the user, and transmit humidity data.

[0041] Understandably, the transmission setting module 220 can be a BLE connector (i.e., Bluetooth Low Energy interface module). The BLE connector communicates with the APP in the user terminal to obtain the first humidity threshold and the second humidity threshold set by the user on the APP, and transmits the real-time humidity data to the APP for the user to view.

[0042] In some embodiments, the execution module 230 may include a humidification chamber, a desiccant chamber, and a drive mechanism.

[0043] The humidification chamber 231 refers to a separate cavity located inside the guitar and containing humidifying materials. For example, the humidifying materials may include humidifying sponges, hydrogels, etc.

[0044] In some embodiments, the humidification chamber 231 can be configured to increase the humidity inside the guitar in response to the opening of the humidification chamber 231.

[0045] The desiccant compartment 232 refers to a separate cavity located inside the guitar and containing desiccant. For example, the desiccant may include silica gel, activated carbon, etc.

[0046] In some embodiments, the desiccant compartment 232 can be configured to absorb moisture from the air inside the guitar when opened.

[0047] Both the humidification chamber and the desiccant chamber can include a chamber body and a door. The chamber body can be used to hold consumables (such as humidifying materials and desiccants), and the door can be used to control the opening or closing of the humidification chamber and the desiccant chamber.

[0048] The drive mechanism 233 refers to the motor used to provide power. For example, the drive mechanism may include a stepper motor, a servo motor, etc.

[0049] In some embodiments, the drive mechanism 233 can be configured to control the opening and closing of the doors of the humidification chamber and the desiccant chamber.

[0050] In some embodiments, the control module 240 may be configured to control the humidification chamber and / or desiccant chamber via a drive mechanism based on humidity data and a humidity threshold, so as to adjust the humidity inside the guitar to the target range defined by the humidity threshold.

[0051] In some embodiments, the control module 240 may also be configured to predict the humidity change curve inside the guitar in the future period based on guitar data, environmental data, and humidity data through a predictive model; determine preventive adjustment parameters based on the humidity change curve in the future period; and control the drive mechanism to preventively adjust the humidity data inside the guitar based on the preventive adjustment parameters.

[0052] In some embodiments, the control module 240 may also be configured to generate candidate adjustment parameters; simulate the changes in humidity inside the guitar in future time periods after the candidate adjustment parameters are executed based on a simulation model; and determine preventive adjustment parameters from the candidate adjustment parameters based on the changes in humidity and adjustment costs.

[0053] In some embodiments, the control module 240 may also be configured to record the adjustment efficiency of the execution module; and in response to the adjustment efficiency being lower than a preset efficiency threshold, send a consumable replacement reminder to the user terminal.

[0054] It should be noted that the above description of the guitar humidity automatic detection and adjustment system 200 and its modules is for ease of description only and should not be construed as limiting this specification to the scope of the illustrated embodiments. It is understood that those skilled in the art, after understanding the principle of the system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from this principle. In some embodiments, Figure 2 The detection module 210, transmission setting module 220, execution module 230, and control module 240 disclosed herein can be different modules within a single system, or a single module can implement the functions of two or more of the aforementioned modules. For example, the modules can share a single storage module, or each module can have its own separate storage module. Such variations are all within the scope of protection of this specification.

[0055] Figure 3 This is an exemplary flowchart of a method for automatically detecting and adjusting guitar humidity according to some embodiments of this specification.

[0056] In some embodiments, such as Figure 3 As shown, process 300 can be executed by a processor, and process 300 includes steps 310-330.

[0057] Step 310: Detect the humidity data inside the guitar.

[0058] Humidity data refers to data used to describe the humidity inside a guitar. For example, humidity data can include the level of moisture in the air inside the guitar.

[0059] In some embodiments, the processor may acquire humidity data via a sensor. The sensor may include a humidity sensor.

[0060] For example, a humidity sensor can be installed inside the guitar in a location where it can fully contact the air environment, and the processor can use the humidity data detected by the humidity sensor inside the guitar as humidity data.

[0061] In some embodiments, the processor may also determine the humidity data inside the guitar by other means, such as obtaining user input.

[0062] Step 320: Communicate with the user terminal, receive the humidity threshold set by the user, and transmit humidity data.

[0063] In some embodiments, the processor can communicate with the user terminal via a network.

[0064] For example, the user terminal can send the humidity threshold to the processor via the network, and the processor can send the humidity data obtained from the sensor to the user terminal via the network.

[0065] Humidity threshold refers to a parameter used to control the operation of the drive mechanism.

[0066] In some embodiments, the humidity threshold may include a first humidity threshold and a second humidity threshold.

[0067] In some embodiments, the second humidity threshold is greater than the first humidity threshold. The first humidity threshold refers to the lowest permissible humidity inside the guitar. The second humidity threshold refers to the highest permissible humidity inside the guitar.

[0068] In some embodiments, the parameter range defined by the first humidity threshold and the second humidity threshold is the parameter range within which the guitar can be played normally.

[0069] In some embodiments, in response to humidity data being within a parameter range defined by a humidity threshold (e.g., humidity data being greater than a first humidity threshold and less than a second humidity threshold), the processor remains silent in regulating the humidity inside the guitar. In response to humidity data exceeding a parameter range defined by a humidity threshold (e.g., humidity data being less than or equal to a first humidity threshold, or greater than or equal to a second humidity threshold), the processor can control the drive mechanism to open and close the door of the humidification chamber or desiccant chamber to control the humidity inside the guitar.

[0070] In some embodiments, the humidity threshold may be preset by a technician based on experience, or set by a user based on needs.

[0071] Step 330: Based on the humidity data and humidity threshold, control the humidification chamber and / or desiccant chamber through the drive mechanism to adjust the humidity inside the guitar to the target range defined by the humidity threshold.

[0072] The target range refers to the normal humidity range inside the guitar as defined by the humidity threshold. In some embodiments, the target range is also the parameter range defined by the humidity threshold.

[0073] In some embodiments, in response to the humidity sensor detecting that the humidity data inside the guitar is less than or equal to a first humidity threshold, the processor can control the drive mechanism to open the humidification chamber door, exposing the humidifying material (such as a sponge) in the humidification chamber to the air inside the guitar, and using the evaporation of moisture from the humidifying material to humidify the air inside the guitar; in response to the humidity sensor detecting that the humidity data inside the guitar is greater than or equal to a second humidity threshold, the processor can control the drive mechanism to open the desiccant chamber door, allowing the desiccant to come into contact with the air inside the guitar, absorbing moisture from the air, and thus drying the air inside the guitar.

[0074] In some embodiments, the processor may record the adjustment efficiency; and in response to the adjustment efficiency being lower than a preset efficiency threshold, send a consumable replacement reminder to the user terminal.

[0075] Regulation efficiency refers to the efficiency with which current consumables change the internal humidity of a guitar. For example, regulation efficiency can be the rate at which consumables change (including increase or decrease) the internal humidity of a guitar. Specifically, the regulation efficiency of humidifying materials refers to the rate at which they increase the internal humidity of the guitar, while the regulation efficiency of desiccant refers to the rate at which it decreases the internal humidity of the guitar.

[0076] Understandably, as the number of times consumables (such as humidifying materials and desiccants) are used increases (when the moisture evaporates or the desiccant becomes saturated with water), the regulating efficiency of the consumables will decrease (when the moisture in the humidifying material evaporates or the desiccant becomes saturated with water). The regulating efficiency can reflect the working performance of the consumables under the current condition.

[0077] In some embodiments, the processor may determine the adjustment efficiency in a variety of ways.

[0078] For example, in response to a user replacing consumables, the processor can perform performance calibration; during each automatic adjustment task, the processor records the total duration of the task and the change in humidity inside the guitar in real time, and determines the adjustment efficiency of this automatic adjustment task based on the total duration and the change in humidity.

[0079] Performance calibration refers to the operation used to determine the adjustment rate of consumables in a brand new state.

[0080] For example, the processor can determine the standard time (T) required for new consumables to cause a unit change in the humidity inside the guitar (e.g., an increase or decrease of 1% RH). base ), will standard time (T) base The baseline time (i.e., the time it takes for the guitar's internal humidity to adjust when the consumable is stored at its full performance (i.e., 100% performance). The baseline time reflects the basic rate at which the consumable achieves its adjustment effect through natural diffusion when it is in its new state.

[0081] Automatic adjustment task refers to the task of automatically adjusting the humidity inside the guitar under the control of the processor.

[0082] Total duration refers to the duration of automatic adjustment tasks, including the time from the start of the task (such as opening the door) to the end of the task (such as closing the door).

[0083] Humidity change refers to the amount of change in humidity inside the guitar before and after the automatic adjustment task.

[0084] In some embodiments, the processor can use the difference between the internal humidity of the guitar after the automatic adjustment task and the internal humidity of the guitar before the automatic adjustment task as the humidity change.

[0085] In some embodiments, in each subsequent auto-adjustment task, the processor can record the total duration (T) of the task in real time. actual ) and humidity change (ΔRH) actual ), and based on standard time (T base Total task duration (T) actual ) and humidity change (ΔRH) actual Determine the regulation efficiency. For example, a processor can determine its real-time regulation efficiency using the following formula: Where E represents the regulation efficiency.

[0086] Understandably, if the automatic adjustment task is to reduce the humidity inside the guitar, the total task duration can be the duration the desiccant compartment is open, the humidity change can be the change in humidity inside the guitar before and after the desiccant compartment is opened, and the standard time can be the time required for the new desiccant to cause a unit change in the humidity inside the guitar (e.g., a 1% decrease in RH). If the automatic adjustment task is to increase the humidity inside the guitar, the total task duration can be the duration the humidification compartment is open, the humidity change can be the change in humidity inside the guitar before and after the humidification compartment is opened, and the standard time can be the time required for the new humidification material to cause a unit change in the humidity inside the guitar (e.g., a 1% increase in RH). The processor can determine the adjustment efficiency for automatic adjustment tasks with the target of drying and automatic adjustment tasks with the target of humidification, respectively.

[0087] The preset efficiency threshold is a parameter used to determine whether consumables need to be replaced.

[0088] In some embodiments, the preset efficiency threshold can be preset by a technician based on experience. The preset efficiency thresholds for humidifying materials and desiccants can be the same or different.

[0089] Consumable replacement reminders are messages used to remind users to replace consumables.

[0090] In some embodiments, consumable replacement reminders may include text, icons, indicator lights, etc.

[0091] For example, a consumable replacement reminder could be displayed on the user terminal with a message such as "The humidifier needs to be replenished with humidifying materials," and the "humidifier" icon on the user terminal would turn red.

[0092] In some embodiments, when the adjustment efficiency of a consumable is lower than its corresponding preset efficiency threshold, the processor can send a consumable replacement reminder to the user terminal via the network.

[0093] In some embodiments of this specification, by real-time monitoring and quantification of the adjustment efficiency of consumables, the problem of users not knowing the status of consumables and the potential for adjustment failure is solved; by proactively sending replacement reminders, the reliability of the system and the convenience of maintenance are improved, ensuring that the guitar is always under effective protection.

[0094] In some embodiments of this specification, by integrating four major modules—detection, communication, bidirectional execution, and intelligent control—the problems of traditional guitar maintenance relying on manual labor, being cumbersome, and prone to negligence are solved. This achieves fully automatic and precise control of the internal humidity of the guitar, improving the convenience and reliability of guitar maintenance, effectively preventing guitar damage caused by humidity issues, and ensuring the guitar's sound quality, feel, and lifespan.

[0095] It should be noted that the above description of process 300 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to process 300 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0096] Figure 4 These are exemplary schematic diagrams illustrating preventative adjustments according to some embodiments of this specification.

[0097] In some embodiments, such as Figure 4As shown, the processor can predict the humidity change curve 450 inside the guitar in the future period based on guitar data 410, environmental data 420 and humidity data 430 through prediction model 440; determine the preventive adjustment parameter 460 based on the humidity change curve 450 in the future period; and control the drive mechanism 233 to preventively adjust the humidity data inside the guitar based on the preventive adjustment parameter 460.

[0098] Guitar data refers to data that reflects the physical characteristics and materials of a guitar.

[0099] For example, guitar data can include guitar type, guitar top wood, and guitar finish type.

[0100] Guitar types can include solid wood guitars, solid-top guitars, and laminate guitars, among others.

[0101] It is understandable that different types of guitars have different sensitivities and response speeds to changes in humidity (e.g., solid wood guitars are the most sensitive to changes in humidity).

[0102] Panel wood can include spruce, cedar, and mahogany, among others.

[0103] It is understandable that different types of panel wood have different densities, porosities, and coefficients of moisture expansion and contraction, and are therefore more sensitive to changes in humidity.

[0104] Paint types can include nitrocellulose lacquer, polyester lacquer, and UV lacquer, etc.

[0105] Understandably, the type of paint determines the degree to which the paint blocks moisture exchange, thus affecting the rate at which moisture exchange occurs between the wood panel and the surrounding environment.

[0106] In some embodiments, the processor can acquire guitar data stored by the user on the user terminal via a network, or the processor can acquire guitar data based on various methods such as image recognition.

[0107] Environmental data refers to data about the external environment in which the guitar is located. For example, environmental data may include ambient temperature, humidity, air pressure, etc.

[0108] In some embodiments, the processor can obtain environmental data stored in the user terminal via a network.

[0109] For example, the processor can obtain weather forecast data for the guitar's location from the user terminal, including ambient temperature, humidity, and air pressure for a future period (such as the next 24 or 72 hours). The geographic location can be obtained from a positioning system integrated into the user terminal (such as GPS) or manually entered by the user.

[0110] In some embodiments, the processor may also obtain environmental data of the external environment in which the guitar is located through various means such as accessing third-party weather websites.

[0111] The future time period refers to the time period after the current moment, and can be set based on needs. For example, the future time period can be the next 24 hours, the next 6 hours, etc.

[0112] A humidity change curve is a curve used to reflect the change in humidity inside a guitar over time. For example, a humidity change curve can be a curve with time on the horizontal axis and humidity on the vertical axis.

[0113] In some embodiments, the processor can use a predictive model to predict the humidity change curve inside the guitar over future periods, based on guitar data, environmental data, and humidity data.

[0114] A predictive model is a model used to determine the humidity change curve inside a guitar over a future period of time.

[0115] In some embodiments, the prediction model can be a machine learning model.

[0116] For example, the prediction model can be a convolutional neural network (CNN), etc.

[0117] In some embodiments, the input to the predictive model may include guitar data, environmental data, and humidity data, and the output may include a humidity change curve inside the guitar over a future period.

[0118] In some embodiments, the predictive model can be obtained by training a large number of first training samples with first training labels. A set of first training samples may include sample guitar data, sample environmental data, and sample humidity data at a first historical time point or a first historical period. The first training label corresponding to a set of first training samples is the sample humidity change curve of the sample guitar at a second historical period. The first historical time point or the first historical period is prior to the second historical period. The first training samples and the first training labels can be obtained based on the historical usage data of the sample guitar.

[0119] In some embodiments, the processor can perform multiple rounds of iterative training on the initial prediction model based on multiple sets of first training samples with first training labels, until the iteration termination condition is met, and the training ends to obtain a trained prediction model. At least one round of iterative training includes: selecting one or more first training samples from the training dataset; inputting the one or more first training samples into the initial prediction model to obtain model prediction outputs corresponding to the one or more first training samples; substituting the model prediction outputs corresponding to the one or more first training samples, and the first training labels corresponding to the one or more first training samples, into a predefined formula for a loss function to calculate the value of the loss function; and iteratively updating the model parameters in the initial prediction model based on the value of the loss function until the iteration termination condition is met, at which point the iteration ends to obtain a trained prediction model.

[0120] The iterative updating of the initial prediction model parameters can be performed using various methods, such as gradient descent. Iteration termination conditions can include loss function convergence, the number of iterations reaching a preset threshold, or the loss function value being less than a preset threshold.

[0121] In some embodiments, the input to the prediction model also includes pitch retention.

[0122] Pitch retention is a parameter used to measure the internal tension stability of a guitar.

[0123] In some embodiments, pitch retention is related to the number and magnitude of string adjustments on the guitar.

[0124] For example, the more strings a user adjusts on a guitar, and the greater the range of adjustment, the lower the pitch retention.

[0125] In some embodiments, the processor can determine the intonation retention rate by consulting a preset table based on the number and magnitude of string adjustments obtained within a historical time period. The preset table may include the relationship between the number and magnitude of adjustments and the intonation retention rate. In some embodiments, the preset table may be preset by a technician based on experience.

[0126] In some embodiments, the processor can directly obtain the number and magnitude of string adjustments input by the user in the user terminal. If the user uses third-party software (guitar tuning software) to adjust the strings, the processor can also obtain the number and magnitude of string adjustments made by the user through the third-party software, and then determine the guitar's intonation retention based on the number and magnitude of string adjustments made by the user.

[0127] In some embodiments, the processor may also determine the guitar's intonation retention based on methods such as directly acquiring user input.

[0128] In some embodiments, the first training sample may further include the sample pitch retention of the sample guitar at a first historical point in time or a first historical period.

[0129] In some embodiments of this specification, by quantifying user tuning behavior feedback as “pitch retention” and incorporating it into a predictive model, the problem that general tuning strategies cannot adapt to individual guitar differences is solved. This enables the tuning system to identify the sensitivity of different guitars to environmental changes, achieving personalized and precise maintenance “depending on the guitar”, thereby improving the targeting and effectiveness of the tuning.

[0130] Preventive adjustment parameters refer to the control parameters of the humidification chamber and / or desiccant chamber to be executed from the current time to the last time of a future period. For example, if the time from the current time to the last time of a future period can be represented as [t1, t2, t3, ..., tn], the preventive adjustment parameters can be (t1: humidification chamber on, t2: humidification chamber off, t3: silent, ..., tn: desiccant chamber off).

[0131] Preventive regulation refers to the operation of intervening in advance on the internal humidity of a guitar based on preventive regulation parameters.

[0132] In some embodiments, the processor can convert humidity change curves into sequence data and compare the sequence data with humidity thresholds. For times in the sequence data where the humidity is greater than a second humidity threshold, the desiccant compartment is activated; for times in the sequence data where the humidity is less than a first humidity threshold, the humidification compartment is activated; otherwise, no marker is made. Sequence data refers to a sequence that reflects the relationship between time intervals and the average humidity inside the guitar.

[0133] For example, the processor can determine the average humidity within each preset time interval (e.g., 10 minutes) and determine sequence data based on the preset time interval and the average humidity within each time interval. An exemplary sequence data can be represented as: [(s0, h0), (s1, h1), (s2, h2), ..., (s...]. n , h n ) ], where s n h represents the time relative to the initial moment, such as 0 minutes, 10 minutes, 20 minutes, etc. n This represents the average humidity. The processor can obtain the drying lead time (e.g., 90 minutes) and the humidification lead time (e.g., 120 minutes), traverse the sequence data, and perform humidification operations when the average humidity in the sequence data is less than the first humidity threshold; and perform drying operations when the average humidity in the sequence data is greater than the second humidity threshold.

[0134] A preset time interval refers to the time period used to divide the interval between each element in the sequence data. In some embodiments, the preset time interval may be preset by a technician based on experience.

[0135] Drying lead time refers to the time period used to determine when to open the desiccant compartment in advance.

[0136] Humidification lead time refers to the time period used to determine when to turn on the humidification chamber in advance.

[0137] In some embodiments, the drying advance and humidification advance can be preset by technicians based on experience.

[0138] As an example only, humidification operation may include: turning on the humidification chamber at the humidification lead time (e.g., if the humidity is less than the first humidity threshold 3 hours in the future, then the humidification chamber will be turned on 1 hour in the future); drying operation may include: turning on the desiccant chamber at the drying lead time (e.g., if the humidity is higher than the second humidity threshold 3 hours in the future, then the desiccant chamber will be turned on 1 hour and 30 minutes in the future).

[0139] The humidification advance time refers to the time when the humidification chamber is turned on ahead of schedule. In some embodiments, the processor can determine the humidification advance time as the time when the average humidity is less than a first humidity threshold, which is one humidification advance time earlier than the threshold.

[0140] The drying lead time refers to the time when the desiccant compartment is opened ahead of schedule. In some embodiments, the processor can determine the drying lead time as a time one drying lead time earlier than the time when the average humidity is greater than a second humidity threshold.

[0141] Understandably, the future time period predicted by the prediction model for the humidity change curve can be 48 hours. The prediction model can predict the humidity change curve for the future time period every prediction cycle (e.g., 6 hours). Since interventions (humidification / drying) may have been carried out in the 0-6 hour interval, the humidity change curve for the 6-48 hour interval may deviate from the prediction. Therefore, the new humidity change curve output by the prediction model at the 6-hour mark will replace the previous humidity change curve to achieve real-time updates of the humidity change curve.

[0142] In some embodiments, the prediction period may be related to the total duration of humidity below a first humidity threshold and humidity above a second humidity threshold in the previously predicted "humidity change curve for a future period," and is shorter than the duration of the future period. For example: a longer total duration means a longer or more intensive adjustment is needed, which leads to more uncertainty. Therefore, the prediction period needs to be shortened based on the preset period or the previously used prediction period, and more frequent predictions need to be made. Conversely, the prediction period can be increased based on the preset period or the previously used prediction period, but the prediction period must be shorter than the duration of the future period.

[0143] In some embodiments, the maximum value of the prediction cycle can be preset based on historical experience. For example, if historical adjustment experience shows that updating the humidity change curve every 2 hours is the most accurate and practical (such as having a good adjustment effect on guitars and not being too frequent), then the maximum value of the prediction cycle can be set. When adjusting the prediction cycle, the adjusted prediction cycle cannot exceed its maximum value.

[0144] In some embodiments, in response to a humidity change curve where the duration of humidity data exceeding the target range is greater than or equal to a preset duration, or the number of times the humidity data exceeds the target range is greater than or equal to a preset number of times, the processor may perform preventative adjustments; otherwise, preventative adjustments are not performed.

[0145] The preset duration refers to the length of time that is set in advance.

[0146] In some embodiments, the preset duration can be preset by technicians based on experience, or preset by users based on their needs.

[0147] The preset number of times refers to the number of times the humidity data is allowed to exceed the target range.

[0148] In some embodiments, the preset number of times can be preset by a technician based on experience, or preset by a user based on needs.

[0149] For example, the processor can iterate through the humidity change curve to determine a first time length t1 or a first count K1, and a second time length t2 or a second count K2. In the first time length t1, the humidity data of all time points is less than a first humidity threshold, and the first count K1 is the total number of times the humidity data is identified as being less than the first humidity threshold. In the second time length t2, the humidity data of all time points is greater than a second humidity threshold, and the second count K2 is the total number of times the humidity data is identified as being less than the second humidity threshold.

[0150] The processor can compare t1 and t2 with a preset duration. If t1 and / or t2 exceed the preset duration, preventive adjustment is performed; otherwise, no preventive adjustment is performed. It can also compare K1 and K2 with a preset number of times. If K1 and / or K2 exceed the preset number of times, preventive adjustment is performed; otherwise, no preventive adjustment is performed.

[0151] It should be noted that setting the preset duration and preset number of times is to prevent the waste of resources caused by immediately adjusting the humidity when the humidity data briefly exceeds the humidity threshold, and to prevent the guitar from frequently being in an unstable humidity environment due to the humidity fluctuating around the threshold.

[0152] In some embodiments of this specification, by setting preset duration and preset number of times, the problem of the system overreacting to small and short-term humidity fluctuations is solved, which effectively avoids unnecessary equipment start-ups and shutdowns, significantly reduces energy consumption and mechanical wear, and improves the system's operating efficiency and service life.

[0153] In some embodiments of this specification, by introducing a predictive model based on multi-source data (guitar / environment / real-time data), a leap from "passive response" to "active prevention" is achieved, thereby solving the problem that traditional solutions can only remedy the situation after the fact. By predicting in advance and intervening gently, the stability of the guitar's internal environment is greatly improved, and the impact of drastic humidity fluctuations on the guitar is avoided.

[0154] Figure 5 This is an exemplary schematic diagram illustrating the determination of preventative adjustment parameters according to some embodiments of this specification.

[0155] In some embodiments, the processor may generate candidate adjustment parameters 510; simulate the changes in humidity inside the guitar in a future period after the candidate adjustment parameters 510 are executed based on a simulation model 520; and determine preventive adjustment parameters 460 from the candidate adjustment parameters 510 based on the humidity changes 530 and the adjustment cost 540.

[0156] Candidate adjustment parameters are parameters that may be used as preventative adjustment parameters.

[0157] In some embodiments, the processor can determine candidate adjustment parameters based on guitar data, environmental data, humidity data, and humidity change curves, using a vector database. The vector database may include the relationship between guitar data, environmental data, humidity data, humidity change curves, and adjustment parameters.

[0158] In some embodiments, the processor can construct feature vectors in a vector database from guitar data, environmental data, humidity data, and humidity change curves, with each feature vector corresponding to a label. In some embodiments, the processor can use the adjustment parameter, which, under the conditions corresponding to the feature vector in historical experiments or adjustments, ensures that the humidity data will not exceed the target range in the future time period after adjustment, as the label of the feature vector.

[0159] In some embodiments, the processor can construct a target vector from the currently collected guitar data, environmental data, humidity data, and humidity change curves, determine the similarity between the target vector and the feature vector, and identify the labels corresponding to feature vectors with similarity exceeding a similarity threshold as candidate adjustment parameters. The similarity calculation method may include cosine similarity, Euclidean distance, etc. The similarity threshold can be preset by technicians based on experience.

[0160] A simulation model is a model used to simulate changes in the internal humidity of a guitar after adjustments based on candidate adjustment parameters. For example, a simulation model can be a model that integrates Newton's law of cooling (describing heat transfer), Fick's law of diffusion (describing moisture penetration), and material hygroscopic theory (e.g., the GAB hygroscopic isotherm model combined with a first-order kinetic model to describe the dynamic exchange of moisture between wood and air).

[0161] Humidity variation refers to the change in humidity data inside the guitar over time after adjustments based on candidate adjustment parameters.

[0162] In some embodiments, the processor can simulate, using a simulation model, the changes in humidity inside the guitar over a future period after the candidate adjustment parameters are executed.

[0163] For example, input the guitar data, environmental data, humidity data, humidity change curve, and at least one set of candidate adjustment parameters corresponding to the current moment. For each set of candidate adjustment parameters, simulate based on the constructed simulation model (built-in moisture diffusion equation, empirical model, etc.) to determine the internal humidity of the guitar at each future time point after executing this set of candidate adjustment parameters. Finally, output a simulated new humidity change curve after intervention by the candidate adjustment parameters, and use this new humidity change curve as the humidity change situation.

[0164] In some embodiments, the input to the simulation model may also include regulation efficiency. Regulation efficiency may include the regulation efficiency of the desiccant consumable during drying and the regulation efficiency of the humidifier consumable during humidification. More information on regulation efficiency can be found at [link to relevant documentation]. Figure 3 And its related descriptions.

[0165] In some embodiments of this specification, by combining efficiency adjustment, the simulation results of the simulation model are made to better reflect the actual situation, thereby further improving the reliability and realism of the simulation.

[0166] Adjustment costs refer to the costs incurred after an adjustment. For example, adjustment costs may include material costs and energy costs.

[0167] In some embodiments, the processor can use the weighted sum of the humidification chamber opening time, the desiccant chamber opening time, and the total number of times the humidification chamber and desiccant chamber are opened as the adjustment cost.

[0168] In some embodiments, the weights of the weighted summation can be determined by the processor based on fitting data of actual consumable consumption.

[0169] For example, the processor can determine the actual adjustment cost based on the actual operating time of the humidifier compartment, the operating time of the desiccant compartment, and the total number of times the humidifier and desiccant compartments were opened during historical adjustment processes, using linear regression and other fitting methods. The actual adjustment cost can be the amount of humidifier consumables consumed during adjustment, the amount of desiccant consumables consumed, and the economic value corresponding to the power consumption.

[0170] In some embodiments, the processor may screen candidate adjustment parameters based on preset conditions, determine the adjustment quality and adjustment cost of the screened adjustment parameters, and determine preventive adjustment parameters based on the adjustment quality and adjustment cost.

[0171] Preset conditions refer to the conditions used to screen candidate adjustment parameters. For example, preset conditions could be that candidate adjustment parameters can maintain the humidity change curve within the target range defined by a humidity threshold over a future period. Adjustment quality refers to a parameter reflecting the fluctuation of the humidity change curve (i.e., the new humidity change curve) after adjustment based on the candidate adjustment parameters. For example, adjustment quality could be the smoothness of the fluctuation of the new humidity change curve (i.e., root mean square error) or the average deviation of the new humidity change curve from the humidity threshold at various points. Higher smoothness indicates higher adjustment quality. Lower average deviation indicates higher adjustment quality.

[0172] For example, the processor can filter out candidate adjustment parameters that can maintain the humidity change curve within the target range defined by the humidity threshold in the future period, and further determine the adjustment quality corresponding to the selected candidate adjustment parameters. It can obtain the humidification chamber operation time, desiccant chamber operation time, and total number of times the humidification chamber and desiccant chamber are opened for each candidate adjustment parameter, calculate the adjustment cost (consumable cost and energy cost), and select the candidate adjustment parameter with the higher adjustment quality as the final preventive adjustment parameter when the adjustment costs are the same. Alternatively, the adjustment quality and adjustment cost can be weighted and summed, and the candidate adjustment parameter with the largest weighted sum can be selected as the final preventive adjustment parameter. The weights of adjustment quality and adjustment cost can be preset, and the weight of adjustment cost is negative.

[0173] It should be noted that when the humidity hovers around the threshold, the adjustment method can include opening the corresponding compartment door for a relatively long time to pull the humidity away from the threshold, or opening the corresponding compartment door for a short time to move the humidity away from the threshold slightly. In the first case, the opening time is longer but the number of starts is less. In the second case, the opening time may be shorter, but it may also lead to frequent opening and closing. The opening and closing process will generate a large inrush current, which may consume more power than stable operation. Therefore, the number of times the compartment door is opened and closed also needs to be considered.

[0174] In some embodiments of this specification, by simulating and evaluating the adjustment costs of multiple candidate adjustment schemes, the problem of resource waste that may be caused by simple adjustment logic is solved. Under the premise of ensuring adjustment effect, the optimal scheme with the lowest consumable and energy costs can be intelligently selected, thereby reducing the user's operating costs and extending the device's battery life.

[0175] This specification provides one or more embodiments of an automatic guitar humidity detection and adjustment device, the device including at least one processor and at least one memory; the at least one memory is used to store computer instructions; the at least one processor is used to execute at least a portion of the computer instructions to implement the automatic guitar humidity detection and adjustment method.

[0176] This specification provides one or more embodiments of a computer-readable storage medium that stores computer instructions that, when executed by a processor, implement a method for automatically detecting and adjusting the humidity of a guitar.

[0177] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0178] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0179] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0180] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0181] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0182] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, and documents referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0183] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. An automatic humidity detection and adjustment system for guitars, characterized in that, The system includes: The detection module is configured to detect humidity data inside the guitar; The transmission setting module is configured to communicate with the user terminal, receive the humidity threshold set by the user, and transmit the humidity data. The execution module includes a humidification chamber, a desiccant chamber, and a drive mechanism, wherein the drive mechanism is configured to control the opening and closing of the humidification chamber and the desiccant chamber; The control module is configured to control the humidification chamber and / or the desiccant chamber via the drive mechanism based on the humidity data and the humidity threshold, so as to adjust the humidity inside the guitar to the target range defined by the humidity threshold.

2. The system according to claim 1, characterized in that, The control module is also configured to: Based on guitar data, environmental data, and the humidity data, a prediction model is used to predict the humidity change curve inside the guitar in future time periods; the prediction model is a machine learning model. Based on the humidity change curve for the future period, determine the preventative adjustment parameters; Based on the aforementioned preventative adjustment parameters, the drive mechanism is controlled to preventatively adjust the humidity data inside the guitar.

3. The system according to claim 2, characterized in that, The control module is also configured to: Generate candidate adjustment parameters; Based on the simulation model, the humidity change inside the guitar in the future time period is simulated after the candidate adjustment parameters are executed; as well as Based on the humidity changes and adjustment costs, the preventative adjustment parameters are determined from the candidate adjustment parameters.

4. The system according to claim 1, characterized in that, The control module is also configured to: Record the adjustment efficiency of the execution module; and In response to the adjustment efficiency being lower than a preset efficiency threshold, a consumable replacement reminder is sent to the user terminal.

5. A method for automatically detecting and adjusting the humidity of a guitar, characterized in that, The method includes: Detect the humidity data inside the guitar; It communicates with the user terminal, receives the humidity threshold set by the user, and transmits the humidity data; Based on the humidity data and the humidity threshold, the humidification chamber and / or desiccant chamber are controlled by a drive mechanism to adjust the humidity inside the guitar to the target range defined by the humidity threshold.

6. The method according to claim 5, characterized in that, The step of controlling the drive mechanism to control the humidification chamber and / or desiccant chamber based on the humidity data and the humidity threshold, so as to adjust the humidity inside the guitar to the target range defined by the humidity threshold, includes: Based on guitar data, environmental data, and the humidity data, a prediction model is used to predict the humidity change curve inside the guitar in future time periods; the prediction model is a machine learning model. Based on the humidity change curve for the future period, determine the preventative adjustment parameters; Based on the aforementioned preventative adjustment parameters, the drive mechanism is controlled to preventatively adjust the humidity data inside the guitar.

7. The method according to claim 6, characterized in that, The step of determining the preventative adjustment parameters based on the humidity change curve for the future time period includes: Generate candidate adjustment parameters; Based on a simulation model, the humidity changes inside the guitar during the future time period are simulated after the candidate adjustment parameters are executed; and Based on the humidity changes and adjustment costs, the preventative adjustment parameters are determined from the candidate adjustment parameters.

8. The method according to claim 5, characterized in that, The method further includes: Record adjustment efficiency; and In response to the adjustment efficiency being lower than a preset efficiency threshold, a consumable replacement reminder is sent to the user terminal.

9. An automatic humidity detection and adjustment device for guitars, the device comprising at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is configured to execute at least a portion of the computer instructions to implement the method as described in any one of claims 5-8.

10. A computer-readable storage medium storing computer instructions that, when executed by a processor, implement the method as described in any one of claims 5-8.

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