Refrigerated medicine Internet of Things temperature and humidity monitoring and control system

Abstract

The invention belongs to the field of Internet of Things, and particularly discloses a refrigerated medicine Internet of Things temperature and humidity monitoring and control system which comprises a sensor deployment module, a data transmission module, a control module, an intelligent early warning module and a data backup and storage module. According to the method, a secret key encapsulation mechanism based on an LDEP encoder-decoder (Low-Density Parity-Check) is used for encapsulating the encrypted temperature and humidity data as a secret key, and meanwhile, a new self-defined rotation engine is introduced, so that the de-encapsulation speed is increased, and data leakage and tampering are effectively prevented; a real-time control method based on fuzzy reasoning is used, the valve opening percentage is determined according to humidity and temperature data collected by a sensor network, a membership function is introduced to carry out approximate expression on the temperature and humidity data, data processing is simplified, the continuity of the actual situation is better met, and the real-time performance is improved. A control signal is calculated through a proportional-integral-differential algorithm to realize automatic control of the valve, so that the labor cost is reduced, the response is quick, and the control effect and quality are improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things, and in particular to an Internet of Things temperature and humidity monitoring and control system for refrigerated medicines. Background Art

[0002] The IoT humidity and temperature monitoring is a process of using IoT technology to monitor and collect data on the humidity and temperature in the environment in real time. It has the advantages of strong real-time performance, high accuracy, and remote monitoring, and provides strong data support for scientific management and decision-making in various industries. However, when transmitting IoT data, there may be threats of data theft, tampering, or network attacks, which may lead to system failures, affect the subsequent precise control of refrigeration equipment, dehumidification equipment, and humidification equipment, reduce or invalidate the efficacy of drugs, and increase medical risks. At present, the control of refrigeration equipment, dehumidification equipment, and humidification equipment is mainly carried out manually, which is prone to errors due to fatigue and negligence. Compared with the automated system, the manual response speed is slow and cannot respond to certain rapidly changing situations in time. Summary of the invention

[0003] In view of the above situation, in order to overcome the defects of the prior art, the present invention provides a refrigerated medicine Internet of Things temperature and humidity monitoring and control system. In view of the technical problems that the traditional technology may face the threat of data theft, tampering or network attack during Internet of Things data transmission, resulting in system failure, affecting the subsequent precise control of refrigeration equipment, dehumidification equipment and humidification equipment, reducing or invalidating the efficacy of medicines, and increasing medical risks, the present invention uses a LDEP encoder-decoder (Low-Density The invention adopts a key encapsulation mechanism of Parity-Check to encapsulate the key of encrypted temperature and humidity data to resist external interference, and introduces a new custom rotation engine to improve the unpacking speed and effectively prevent data leakage and tampering; the current control of refrigeration equipment, dehumidification equipment and humidification equipment is mainly carried out manually, which is easy to cause errors due to fatigue and negligence, and compared with the automation system, the manual reaction speed is slower and cannot respond to certain rapidly changing situations in time. The present invention uses a real-time control method based on fuzzy reasoning, determines the valve opening percentage according to the wet temperature data collected by the sensor network, introduces a membership function to approximate the temperature and humidity data, simplifies data processing, is more in line with the continuity of the actual situation, and realizes decision-making that is more in line with the human way of thinking. The control signal is calculated by the proportional-integral-differential algorithm to realize automatic control of the valve, reduce labor costs, respond quickly, and improve the control effect and quality.

[0004] The technical solution adopted by the present invention is as follows: The present invention provides a refrigerated medicine Internet of Things temperature and humidity monitoring and control system, the refrigerated medicine Internet of Things temperature and humidity monitoring and control system comprises a sensor deployment module, a data transmission module, a control module, an intelligent early warning module and a data backup and storage module;

[0005] The sensor deployment module distributes high-precision temperature and humidity sensors in the cold storage area to accurately collect real-time temperature and humidity data at each location;

[0006] The data transmission module and the temperature and humidity sensor form a wireless sensor network, which transmits the temperature and humidity data to the control module and the data backup and storage module wirelessly;

[0007] The control module processes and analyzes the temperature and humidity data and automatically controls the operating status of the refrigeration equipment, including adjusting the refrigeration power and starting the dehumidification and humidification equipment;

[0008] The intelligent early warning module sets the upper and lower thresholds of temperature and humidity. When the temperature and humidity data exceed the upper and lower thresholds, the system automatically triggers an alarm and notifies the staff via SMS and email;

[0009] The data backup and storage module establishes a database to store temperature and humidity data and performs data backup regularly.

[0010] The data transmission module ensures the secure transmission of temperature and humidity data through a key encapsulation-decapsulation method, and the key encapsulation-decapsulation method specifically includes the following steps:

[0011] Step A1: define two different CSHAKE functions. The absorption structure of the CSHAKE function includes two parts: byte board absorption and input absorption. Assume that the absorption phase of the CSHAKE function has 76 clock cycles, each clock cycle is 64 bits, and there are 17 hash channels. The output of the CSHAKE function consists of a key confirmation hash and a symmetric key, with a size of 512 bits, of which the first 256 bits on the left are the key confirmation hash, and the next 256 bits on the right are the symmetric key.

[0012] Step A2: Before the temperature and humidity data are transmitted, two CSHAKE functions are used to calculate the symmetric key in parallel with the key confirmation hash and the weight, and the symmetric key with the key confirmation hash is input into the error vector generator to generate an error pattern;

[0013] Step A3: randomly generate a 64-bit key seed, split the key seed and input it into two CSHAKE functions, and use the key seed and the symmetric key to encrypt the temperature and humidity data to obtain encrypted data;

[0014] Step A4: Send the error pattern to one of the CSHAKE functions to calculate the mask, perform an XOR operation on the key seed and the mask to obtain an XOR key, and input the XOR key into the LDEP encoder to generate a wrapping key;

[0015] Step A5: define a rotation engine, integrate the rotation engine with the LDEP encoder, the rotation engine includes a two-layer multiplexer, each layer of the multiplexer includes a rotation counter, the encapsulation key is passed to the first layer of the multiplexer, the multiplexer rotates the encapsulation key, the rotation counter counts from 0 to 13, resets to zero, and transmits the encapsulation key to the second layer, the multiplexer of the second layer is determined by the shift amount, and the calculation formula of the shift amount is as follows: ;

[0016] In the formula, is the displacement amount, It is a rotation counter that tracks the rotation of the encapsulation key. When the rotation counter reaches 4810, it is reset and enters the next absorption stage. At each clock cycle, the shift amount is fed back to the input. When the counter reaches 13, the multiplexer in the second layer outputs the rotation result according to the shift amount.

[0017] Step A6: The encapsulation key and the encrypted data are transmitted. After receiving the encapsulation key and the encrypted data, the control module and the data backup and storage module unseal the encapsulation key. The LDEP decoder integrated in the rotation engine decrypts the encapsulation key to obtain an error pattern and an XOR key. The error pattern inputs a CM 64 bits per cycle to generate a mask. The mask and the XOR key are XORed to obtain a recovery seed. The recovery seed is fed to the CSHAKE function in parallel to obtain a recovery key. The recovery key is input to the error vector generator to obtain a recovery error.

[0018] Step A7: If the recovery error is equal to the error pattern obtained by decrypting the LDEP decoder, the encapsulation key is equal to the recovery key generated by the recovery seed, the recovery seed and the recovery key are used to decrypt the encrypted data. Otherwise, the staff is notified of the data leak via SMS and email.

[0019] After the control module obtains the temperature and humidity data, the fuzzy control method is used to control the valve opening of the refrigeration equipment, the humidification equipment and the dehumidification equipment. The valves of the refrigeration equipment, the humidification equipment and the dehumidification equipment are controlled by electric actuators. The fuzzy control method specifically includes the following steps:

[0020] Step B1: Define the membership function to map the clear value of temperature and humidity data to a fuzzy membership value between 0 and 1. The formula used is as follows: ; ;

[0021] In the formula, is a triangular membership function with three parameters Description, where is the lower limit of the triangular membership function, is the upper limit of the triangular membership function, are the vertices of the triangle, and , It is the temperature and humidity data. is a trapezoidal membership function consisting of four parameters Description, where is the lower limit of the trapezoidal membership function, is the upper limit of the trapezoidal membership function, is the lower support limit, is the upper support limit, and ;

[0022] Step B2: Design a rule base, use the fuzzy rule base with conditional statements if-then in the fuzzy reasoning engine, and deploy the fuzzy reasoning engine on a graphical programming platform;

[0023] Step B3: Through the centroid technology, after inputting the fuzzy membership value of the temperature and humidity data, the percentage value of the valve opening of the refrigeration equipment, humidification equipment and dehumidification equipment is output, which is recorded as the control percentage value;

[0024] Step B4: Use the proportional-integral-differential algorithm to calculate the deviation between the current percentage value of the valve opening and the control percentage value, and generate a control signal. The electric actuators of the refrigeration equipment, humidification equipment and dehumidification equipment adjust the valve opening according to the control signal. After the adjustment is completed, the refrigeration equipment, humidification equipment and dehumidification equipment will work for 15 minutes and then check the temperature and humidity data again to start a new adjustment cycle. The new adjustment cycle is 1 hour. Each time an adjustment is made, the temperature and humidity data and the control percentage value are sent to the staff via SMS.

[0025] The beneficial effects achieved by the present invention using the above scheme are as follows:

[0026] (1) In view of the technical problems existing in traditional technologies, when IoT data is transmitted, data may be stolen, tampered with or attacked by a network, resulting in system failure, affecting the subsequent precise control of refrigeration equipment, dehumidification equipment and humidification equipment, reducing or rendering the efficacy of drugs ineffective, and increasing medical risks, the present invention uses a key encapsulation mechanism based on LDEP encoder-decoder (Low-Density Parity-Check) to encapsulate the key of encrypted temperature and humidity data to resist external interference. At the same time, a new custom rotation engine is introduced to improve the decryption speed and effectively prevent data leakage and tampering.

[0027] (2) In view of the technical problems that the current control of refrigeration equipment, dehumidification equipment and humidification equipment is mainly carried out manually, which is prone to errors due to fatigue and negligence, and compared with the automated system, the manual reaction speed is slow and cannot respond to certain rapidly changing situations in time, the present invention uses a real-time control method based on fuzzy reasoning, determines the valve opening percentage according to the humidity and temperature data collected by the sensor network, introduces a membership function to approximate the temperature and humidity data, simplifies data processing, is more in line with the continuity of the actual situation, and realizes decisions that are more in line with the human way of thinking, through proportional-integral-differential. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A module connection diagram of a refrigerated medicine Internet of Things temperature and humidity monitoring and control system provided by the present invention;

[0029] Figure 2 This is the membership function image of the temperature and humidity data provided by the present invention.

[0030] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0032] Example 1: See Figure 1 , this embodiment provides a refrigerated medicine Internet of Things temperature and humidity monitoring and control system, the refrigerated medicine Internet of Things temperature and humidity monitoring and control system includes a sensor deployment module, a data transmission module, a control module, an intelligent early warning module and a data backup and storage module;

[0033] The sensor deployment module distributes high-precision temperature and humidity sensors in the cold storage area to accurately collect real-time temperature and humidity data at each location;

[0034] The data transmission module and the temperature and humidity sensor form a wireless sensor network, which transmits the temperature and humidity data to the control module and the data backup and storage module wirelessly;

[0035] The control module processes and analyzes the temperature and humidity data and automatically controls the operating status of the refrigeration equipment, including adjusting the refrigeration power and starting the dehumidification and humidification equipment;

[0036] The intelligent early warning module sets the upper and lower thresholds of temperature and humidity. When the temperature and humidity data exceed the upper and lower thresholds, the system automatically triggers an alarm and notifies the staff via SMS and email;

[0037] The data backup and storage module establishes a database to store temperature and humidity data and performs data backup regularly.

[0038] Example 2: See Figure 1 This embodiment is based on the above embodiment. The data transmission module ensures the secure transmission of temperature and humidity data through a key encapsulation-decapsulation method. The key encapsulation-decapsulation method specifically includes the following steps:

[0039] Step A1: define two different CSHAKE functions. The absorption structure of the CSHAKE function includes two parts: byte board absorption and input absorption. Assume that the absorption phase of the CSHAKE function has 76 clock cycles, each clock cycle is 64 bits, and there are 17 hash channels. The output of the CSHAKE function consists of a key confirmation hash and a symmetric key, with a size of 512 bits, of which the first 256 bits on the left are the key confirmation hash, and the next 256 bits on the right are the symmetric key.

[0040] Step A2: Before the temperature and humidity data are transmitted, two CSHAKE functions are used to calculate the symmetric key in parallel with the key confirmation hash and the weight, and the symmetric key with the key confirmation hash is input into the error vector generator to generate an error pattern;

[0041] Step A3: randomly generate a 64-bit key seed, split the key seed and input it into two CSHAKE functions, and use the key seed and the symmetric key to encrypt the temperature and humidity data to obtain encrypted data;

[0042] Step A4: Send the error pattern to one of the CSHAKE functions to calculate the mask, perform an XOR operation on the key seed and the mask to obtain an XOR key, and input the XOR key into the LDEP encoder to generate a wrapping key;

[0043] Step A5: define a rotation engine, integrate the rotation engine with the LDEP encoder, the rotation engine includes a two-layer multiplexer, each layer of the multiplexer includes a rotation counter, the encapsulation key is passed to the first layer of the multiplexer, the multiplexer rotates the encapsulation key, the rotation counter counts from 0 to 13, resets to zero, and transmits the encapsulation key to the second layer, the multiplexer of the second layer is determined by the shift amount, and the calculation formula of the shift amount is as follows: ;

[0044] In the formula, is the displacement amount, It is a rotation counter that tracks the rotation of the encapsulation key. When the rotation counter reaches 4810, it is reset and enters the next absorption stage. At each clock cycle, the shift amount is fed back to the input. When the counter reaches 13, the multiplexer in the second layer outputs the rotation result according to the shift amount.

[0045] Step A6: The encapsulation key and the encrypted data are transmitted. After receiving the encapsulation key and the encrypted data, the control module and the data backup and storage module unseal the encapsulation key. The LDEP decoder integrated in the rotation engine decrypts the encapsulation key to obtain an error pattern and an XOR key. The error pattern inputs a CM 64 bits per cycle to generate a mask. The mask and the XOR key are XORed to obtain a recovery seed. The recovery seed is fed to the CSHAKE function in parallel to obtain a recovery key. The recovery key is input to the error vector generator to obtain a recovery error.

[0046] Step A7: If the recovery error is equal to the error pattern obtained by decrypting the LDEP decoder, the encapsulation key is equal to the recovery key generated by the recovery seed, the recovery seed and the recovery key are used to decrypt the encrypted data. Otherwise, the staff is notified of the data leak via SMS and email.

[0047] Through the above operations, in order to solve the technical problems existing in traditional technologies, that is, during the transmission of IoT data, data may be threatened with theft, tampering or network attacks, resulting in system failure, affecting the subsequent precise control of refrigeration equipment, dehumidification equipment and humidification equipment, reducing or rendering the efficacy of drugs ineffective, and increasing medical risks, the present invention uses a key encapsulation mechanism based on LDEP encoder-decoder (Low-Density Parity-Check) to encapsulate the key of encrypted temperature and humidity data to resist external interference, and introduces a new custom rotation engine to improve the decryption speed, effectively preventing data leakage and tampering.

[0048] Example 3: See Figure 1 and Figure 2This embodiment is based on the above embodiment. After the control module obtains the temperature and humidity data, the fuzzy control method is used to control the valve opening of the refrigeration equipment, the humidification equipment and the dehumidification equipment. The valves of the refrigeration equipment, the humidification equipment and the dehumidification equipment are controlled by electric actuators. The fuzzy control method specifically includes the following steps:

[0049] Step B1: Define the membership function to map the clear value of temperature and humidity data to a fuzzy membership value between 0 and 1. The formula used is as follows: ; ;

[0050] In the formula, is a triangular membership function with three parameters Description, where is the lower limit of the triangular membership function, is the upper limit of the triangular membership function, are the vertices of the triangle, and , It is the temperature and humidity data. is a trapezoidal membership function consisting of four parameters Description, where is the lower limit of the trapezoidal membership function, is the upper limit of the trapezoidal membership function, is the lower support limit, is the upper support limit, and ;

[0051] Step B2: Design a rule base, use the fuzzy rule base with conditional statements if-then in the fuzzy reasoning engine, and deploy the fuzzy reasoning engine on a graphical programming platform;

[0052] Step B3: Through the centroid technology, after inputting the fuzzy membership value of the temperature and humidity data, the percentage value of the valve opening of the refrigeration equipment, humidification equipment and dehumidification equipment is output, which is recorded as the control percentage value;

[0053] Step B4: Use the proportional-integral-differential algorithm to calculate the deviation between the current percentage value of the valve opening and the control percentage value, and generate a control signal. The electric actuators of the refrigeration equipment, humidification equipment and dehumidification equipment adjust the valve opening according to the control signal. After the adjustment is completed, the refrigeration equipment, humidification equipment and dehumidification equipment will work for 15 minutes and then check the temperature and humidity data again to start a new adjustment cycle. The new adjustment cycle is 1 hour. Each time an adjustment is made, the temperature and humidity data and the control percentage value are sent to the staff via SMS.

[0054] Through the above operations, the current control of refrigeration equipment, dehumidification equipment and humidification equipment is mainly carried out manually, which is easy to cause errors due to fatigue and negligence. Compared with the automated system, the manual reaction speed is slow and cannot respond to certain rapidly changing situations in time. The present invention uses a real-time control method based on fuzzy reasoning, determines the valve opening percentage according to the wet temperature data collected by the sensor network, introduces a membership function to approximate the temperature and humidity data, simplifies data processing, is more in line with the continuity of actual conditions, and realizes decisions that are more in line with human thinking. The control signal is calculated by the proportional-integral-differential algorithm to realize automatic control of the valve, reduce labor costs, respond quickly, and improve the control effect and quality.

[0055] Embodiment 4: This embodiment is based on the above embodiment. The fuzzy rule base in Embodiment 3 is briefly described as follows:

[0056] Rule 1: If the temperature is high and the humidity is high, the valve is open 80%;

[0057] Rule 2: If the temperature is high and the humidity is moderate, the valve is 60% open;

[0058] Rule 3: If the temperature is high and the humidity is low, the valve is open 40%;

[0059] Rule 4: If the temperature is moderate and the humidity is high, the valve is 60% open;

[0060] Rule 5: If the temperature is moderate and the humidity is moderate, then the valve is 30% open;

[0061] Rule 6: If the temperature is moderate and the humidity is low, the valve is 20% open;

[0062] Rule 7: If the temperature is low and the humidity is high, the valve is open 40%;

[0063] Rule 8: If the temperature is low and the humidity is moderate, the valve is 20% open;

[0064] Rule 9: If the temperature is low and the humidity is low, then open the valve 10%.

[0065] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0066] Although 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 the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0067] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A refrigerated medicine Internet of Things temperature and humidity monitoring and control system, characterized in that: It includes sensor deployment module, data transmission module, control module, intelligent early warning module and data backup and storage module; The sensor deployment module distributes high-precision temperature and humidity sensors in the cold storage area to accurately collect real-time temperature and humidity data at each location; The data transmission module and the temperature and humidity sensor form a wireless sensor network, which transmits the temperature and humidity data to the control module and the data backup and storage module wirelessly; The control module processes and analyzes the temperature and humidity data and automatically controls the operating status of the refrigeration equipment, including adjusting the refrigeration power and starting the dehumidification and humidification equipment; The intelligent early warning module sets the upper and lower thresholds of temperature and humidity. When the temperature and humidity data exceed the upper and lower thresholds, the system automatically triggers an alarm and notifies the staff via SMS and email; The data backup and storage module establishes a database to store temperature and humidity data and performs data backup regularly.

2. A refrigerated medicine Internet of Things temperature and humidity monitoring and control system according to claim 1, characterized in that: The data transmission module ensures the secure transmission of temperature and humidity data through a key encapsulation-decapsulation method, and the key encapsulation-decapsulation method specifically includes the following steps: Step A1: define two different CSHAKE functions. The absorption structure of the CSHAKE function includes two parts: byte board absorption and input absorption. Assume that the absorption phase of the CSHAKE function has 76 clock cycles, each clock cycle is 64 bits, and there are 17 hash channels. The output of the CSHAKE function consists of a key confirmation hash and a symmetric key, with a size of 512 bits, of which the first 256 bits on the left are the key confirmation hash, and the next 256 bits on the right are the symmetric key. Step A2: Before the temperature and humidity data are transmitted, two CSHAKE functions are used to calculate the symmetric key in parallel with the key confirmation hash and the weight, and the symmetric key with the key confirmation hash is input into the error vector generator to generate an error pattern; Step A3: randomly generate a 64-bit key seed, split the key seed and input it into two CSHAKE functions, and use the key seed and the symmetric key to encrypt the temperature and humidity data to obtain encrypted data; Step A4: Send the error pattern to one of the CSHAKE functions to calculate the mask, perform an XOR operation on the key seed and the mask to obtain an XOR key, and input the XOR key into the LDEP encoder to generate a wrapping key; Step A5: define a rotation engine, integrate the rotation engine with the LDEP encoder, the rotation engine includes a two-layer multiplexer, each layer of the multiplexer includes a rotation counter, the encapsulation key is passed to the first layer of the multiplexer, the multiplexer rotates the encapsulation key, the rotation counter counts from 0 to 13, resets to zero, and transmits the encapsulation key to the second layer, the multiplexer of the second layer is determined by the shift amount, and the calculation formula of the shift amount is as follows: ； In the formula, is the displacement amount, It is a rotation counter that tracks the rotation of the encapsulation key. When the rotation counter reaches 4810, it is reset and enters the next absorption stage. At each clock cycle, the shift amount is fed back to the input. When the counter reaches 13, the multiplexer in the second layer outputs the rotation result according to the shift amount. Step A6: The encapsulation key and the encrypted data are transmitted. After receiving the encapsulation key and the encrypted data, the control module and the data backup and storage module unseal the encapsulation key. The LDEP decoder integrated in the rotation engine decrypts the encapsulation key to obtain an error pattern and an XOR key. The error pattern inputs a CM 64 bits per cycle to generate a mask. The mask and the XOR key are XORed to obtain a recovery seed. The recovery seed is fed to the CSHAKE function in parallel to obtain a recovery key. The recovery key is input to the error vector generator to obtain a recovery error. Step A7: If the recovery error is equal to the error pattern obtained by decrypting the LDEP decoder, the encapsulation key is equal to the recovery key generated by the recovery seed, the recovery seed and the recovery key are used to decrypt the encrypted data. Otherwise, the staff is notified of the data leak via SMS and email.

3. A refrigerated medicine Internet of Things temperature and humidity monitoring and control system according to claim 2, characterized in that: After the control module obtains the temperature and humidity data, the fuzzy control method is used to control the valve opening of the refrigeration equipment, the humidification equipment and the dehumidification equipment. The valves of the refrigeration equipment, the humidification equipment and the dehumidification equipment are controlled by electric actuators. The fuzzy control method specifically includes the following steps: Step B1: define a membership function to map the clear values ​​of temperature and humidity data to fuzzy membership values ​​between 0 and 1; Step B2: Design a rule base, use the fuzzy rule base with conditional statements if-then in the fuzzy reasoning engine, and deploy the fuzzy reasoning engine on a graphical programming platform; Step B3: Through the centroid technology, after inputting the fuzzy membership value of the temperature and humidity data, the percentage value of the valve opening of the refrigeration equipment, humidification equipment and dehumidification equipment is output, which is recorded as the control percentage value; Step B4: Use the proportional-integral-differential algorithm to calculate the deviation between the current percentage value of the valve opening and the control percentage value, and generate a control signal. The electric actuators of the refrigeration equipment, humidification equipment and dehumidification equipment adjust the valve opening according to the control signal. After the adjustment is completed, the refrigeration equipment, humidification equipment and dehumidification equipment will work for 15 minutes and then check the temperature and humidity data again to start a new adjustment cycle. The new adjustment cycle is 1 hour. Each time an adjustment is made, the temperature and humidity data and the control percentage value are sent to the staff via SMS.

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