Multifunctional operating room environment control system based on Internet of Things technology

Abstract

The invention relates to the technical field of environment control, in particular to an operating room multifunctional environment control system based on the Internet of Things technology, which comprises an environment control unit, an automatic control unit, a light automatic adjusting unit, a mode matching unit, an air monitoring unit and an air purifying unit, and further comprises a voice acquisition unit, a voice processing unit and a control unit, the voice acquisition unit carries out voice acquisition on an operating room administrator through setting audio acquisition equipment in a target area in an operating room so as to obtain environment control voice, carries out preprocessing on the environment control voice so as to obtain standard environment control voice, and transmits the standard environment control voice to the voice recognition unit. According to the invention, through voice acquisition and recognition, instructions and demands of an operating room administrator can be responded in real time, and environmental parameters such as temperature, humidity and illumination are automatically adjusted, so that comfort and safety in the operating room are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental control, and in particular to a multifunctional environmental control system for an operating room based on the Internet of Things technology. Background Art

[0002] An operating room is a facility within a hospital that is specifically used for performing surgical operations and other invasive medical procedures. It usually has a highly clean and sterile environment to ensure that patients are not infected during surgery, and provides medical staff with the equipment and tools needed to perform surgery. The design and equipment configuration of the operating room must meet strict medical and health standards and safety requirements, such as air filtration, ultraviolet sterilization, disinfection equipment, etc., to ensure the safety and success rate of surgical operations.

[0003] Internet of Things technology refers to a technical system that connects various physical devices (such as sensors, actuators, electronic devices, software, etc.) through the Internet, enabling them to exchange data with each other and perform intelligent control and operation.

[0004] Traditional systems usually rely on manual adjustment of environmental equipment, such as manual control of air conditioning, lighting and air purifiers, which makes the response to environmental changes relatively slow, and traditional systems may lack effective energy management strategies. For example, in the absence of real-time environmental data and intelligent control, air conditioning and lighting systems may operate in a fixed mode, resulting in energy waste. In traditional systems, operating room administrators may need to adjust the environment through multiple control panels or manual switches. This operation method may not only be complicated, but also consume valuable time. In addition, traditional systems usually lack the ability to collect and analyze real-time environmental data, making it difficult to accurately monitor parameters such as temperature, humidity and air quality in the operating room and make immediate adjustments accordingly. Summary of the invention

[0005] The purpose of the present invention is to provide a multifunctional operating room environmental control system based on Internet of Things technology, which solves the technical problems in the prior art that the operating room operation mode is complicated, consumes valuable time, lacks the ability to collect and analyze real-time environmental data, and is difficult to accurately monitor parameters such as temperature, humidity and air quality in the operating room.

[0006] A multifunctional operating room environment control system based on Internet of Things technology, including an environment control unit, an automatic control unit, a light automatic adjustment unit, a pattern matching unit, an air monitoring unit and an air purification unit, and also includes: a voice collection unit, a voice recognition unit and an environment data collection unit;

[0007] The voice collection unit collects the voice of the operating room administrator by setting an audio collection device in the target area of ​​the operating room to obtain the environment control voice, and pre-processes the environment control voice to obtain the standard environment control voice, and transmits the standard environment control voice to the voice recognition unit;

[0008] The speech recognition unit receives the standard environment control speech transmitted by the speech acquisition unit, and performs speech recognition on the standard environment control speech through a trained speech recognition model to obtain environment control keywords, matches the environment control keywords with an environment control table pre-stored in a database to obtain environment control information corresponding to the environment control keywords, and transmits the environment control information to the environment control unit and the pattern matching unit;

[0009] The environmental data acquisition unit collects the environmental data of the target area by setting a sensor group in the target area in the operating room to obtain the environmental data of the target area, the sensor group includes a temperature sensor and a humidity sensor, the environmental data includes temperature and humidity, and the environmental data of the target area is transmitted to the automatic control unit.

[0010] Preferably, the automatic control unit receives the environmental data of the target area transmitted by the environmental data acquisition unit, and constructs an environmental control model based on the environmental data of the target area, wherein the environmental control model includes a state space, an action space and a reward function, and solves the environmental control model based on a reinforcement learning algorithm to obtain controllable variables of the HVAC system, and transmits the controllable variables to the environmental control unit.

[0011] Preferably, the automatic light adjustment unit is used to perform adaptive light adjustment on the lighting area in the operating room through an automatic light adjustment method to obtain adaptive light adjustment information and transmit the information to the environment control unit.

[0012] Preferably, the pattern matching unit receives the environmental control information transmitted by the voice recognition unit and records the quantity to obtain multiple commonly used environmental control information, sequentially number the multiple commonly used environmental control information, match and map the sequential numbers with the control terminal, and display the multiple commonly used environmental control information on the control terminal according to the sequential numbers. The operating room administrator selects the commonly used environmental control information through the control terminal and transmits the selected commonly used environmental control information to the environmental control unit.

[0013] Preferably, the environmental control unit receives the environmental control information transmitted by the voice recognition unit, the controllable variables transmitted by the automatic control unit, the light adaptive adjustment information transmitted by the automatic light adjustment unit, and the common environmental control information transmitted by the pattern matching unit, and controls the environmental status in the operating room through an environmental control method.

[0014] Preferably, the air monitoring unit is used to monitor the concentrations of various pollutants in the operating room through air quality sensors to obtain real-time concentrations of various pollutants, and calculate real-time air quality sub-indices of various pollutants based on the real-time concentrations of various pollutants, and calculate real-time air quality index based on the real-time air quality sub-indices of various pollutants, and transmit the real-time air quality index to the air purification unit.

[0015] Preferably, the air purification unit receives the real-time air quality index transmitted by the air monitoring unit, and maps the air quality index with the air purifier operating time to obtain a mapping table, matches the real-time air quality index with the mapping table to obtain the air purifier operating time corresponding to the real-time air quality index, and controls the operation of the air purifier based on the air purifier operating time.

[0016] Preferably, the calculation formula of the real-time air quality index of various pollutants is as follows:

[0017]

[0018] Among them, R represents a single pollutant, IAQI R Represents the air quality index of a single pollutant R, IAQI Lo and IAQI Hi Respectively represent and BR Lo and BR Hi The corresponding air quality index, BR Lo and BR Hi They represent the lower and upper values ​​of the pollutant concentration limit values ​​close to the concentration value of a single pollutant R, respectively. R Represents the mass concentration value of a single pollutant R;

[0019] The calculation formula of the real-time air quality index is as follows:

[0020] AQI=max{IAQI1,IAQI2,...,IAQI k ,...,IAQI n};

[0021] Among them, AQI represents the real-time air quality index, n represents the number of pollutant types, and IAQIk represents the kth pollutant.

[0022] Preferably, constructing an environmental control model based on the environmental data of the target area comprises the following steps:

[0023] A1. The environmental data at the same time is converted by a conversion formula to obtain a state space. The conversion formula includes a temperature conversion formula and a humidity conversion formula. The temperature conversion formula is as follows:

[0024]

[0025] Among them, t e ' m represents the temperature after conversion, t em Indicates the temperature before conversion, T low,bo Indicates the lower limit of temperature setting, T up,bo Indicates the upper limit of temperature setting;

[0026] The temperature conversion formula is as follows:

[0027]

[0028] Among them, R′ H Represents the converted humidity, R H Represents the humidity before conversion, R low,bo Indicates the lower limit of humidity setting, R up,bo Indicates the upper limit of humidity setting;

[0029] A2. Based on the state space, a temperature penalty term and a humidity penalty term are defined, and a reward function is defined based on the temperature penalty term and the humidity penalty term. The reward function is as follows:

[0030] R eward =-k1p tem -k2p RH ;

[0031] Among them, R eward represents the reward, k1 and k2 represent the temperature penalty coefficient and humidity penalty coefficient, p tem and p RH represents the temperature penalty term and the humidity penalty term, and and

[0032] A3. The air supply volume of the HVAC system is used as the action space, and the action space is as follows:

[0033] A=[a0,a1,a2,a3]=[0,50%,75%,100%];

[0034] Among them, A represents the action space, and a0, a1, a2, and a3 represent the control actions in the action space.

[0035] Preferably, the automatic lighting adjustment method comprises the following steps:

[0036] B1. Divide the lighting area in the operating room into multiple defined areas, and collect boundary conditions of the defined areas through a convolutional neural network to obtain initial values ​​of the boundary conditions of the defined areas. The calculation formula of the boundary conditions is as follows:

[0037]

[0038] Among them, t x ,t y ,t g and t k represents the corresponding coordinate values ​​of each bounding box on each limited area predicted by the convolutional neural network, x and y represent the values ​​of x and y in the rectangular coordinate system, g and k represent the height and width of the bounding box, and n x and n y Indicates the degree of deviation of the target from the set center position, p g and p k Represents the predicted bounding box corresponding to the height and width, m x and m y represents the boundary condition, m g and m k Indicates the height and width position of the corresponding point;

[0039] B2. Set a data acquisition cycle to regularly acquire the location of the indoor personnel in the operating room, define the connected area of ​​the indoor personnel as a closed body, simplify the circle domain of the closed body radius with the lighting point as the center, and define an error compensation function to perform error compensation on the closed body to obtain a closed body compensation value. The closed body definition formula is as follows:

[0040] U={u||uP j ||≤R b ,u∈A};

[0041] Among them, U represents the definition of the closed space, u represents any point in the closed space, and P j represents the number of grid intersections of the normalized input space partition, R b represents the radius of the closed body, and A represents the normalized input space;

[0042] The error compensation function is as follows:

[0043] y k =S k[b1,b2,...,b L ][q1,q2,...,q L ] T ;

[0044] Among them, y k Indicates the error compensation value, S k represents the weight coefficient, b L represents the Gaussian function value, q L represents the weight coefficient vector;

[0045] B3. Calculate the distribution of the illumination intensity field in the closed body according to the current illumination value in the closed body to obtain the total illumination intensity in the closed body. The distribution formula of the illumination intensity field is as follows:

[0046]

[0047] Among them, I total (x, y) represents the total light intensity, N represents the sum of illumination, i represents the number of sampling times, u represents the wave field, and t represents time;

[0048] B4. Iteratively judge all the indoor occupants. When the total light intensity in the enclosure is within the preset optimal lighting range, no light adjustment is performed. When the total light intensity in the enclosure is greater than the preset upper limit of the optimal lighting range, the lighting intensity of the lighting area corresponding to the enclosure is reduced. When the total light intensity in the enclosure is less than the lower limit of the optimal lighting range, the lighting intensity of the lighting area corresponding to the enclosure is increased, thereby obtaining light adaptive adjustment information.

[0049] Preferably, the environmental control method comprises the following steps:

[0050] C1, determining whether the operating room administrator actively controls the environmental status in the operating room, if in an active control state, performing environmental control according to the environmental control information and the common environmental control information, otherwise, executing step C2;

[0051] C2. Controlling the air supply volume of the HVAC system according to the controllable variables, and controlling the lighting area in the operating room according to the adaptive lighting adjustment information.

[0052] Preferably, determining whether the operating room administrator actively controls the environmental state in the operating room comprises the following steps:

[0053] D1, judging whether the environmental control information is received, if the environmental control information is received, it is in the active control state, otherwise, executing step D2;

[0054] D2. Determine whether the commonly used environment control information is received. If the commonly used environment control information is received, the system is in an active control state.

[0055] Beneficial effects of the present invention:

[0056] 1. The present invention can respond to the instructions and needs of the operating room administrator in real time through voice collection and recognition, and automatically adjust environmental parameters such as temperature, humidity and lighting to ensure comfort and safety in the operating room. Through the environmental data collection unit and the automatic control unit, an environmental control model can be established according to the environmental data collected by the sensor, and the environmental control can be optimized through the reinforcement learning algorithm, so as to achieve more efficient HVAC system management and improve energy utilization efficiency. The lighting in the operating room is automatically adjusted according to environmental needs through the automatic lighting adjustment unit to ensure that the lighting quality and brightness during the operation are appropriate, which is beneficial to the doctor's operation and the patient's sense of security.

[0057] 2. The present invention can record and manage commonly used environmental control information through the pattern matching unit, so that operating room administrators can easily and quickly select and apply common environmental control modes, improve work efficiency and operational convenience, and through the air monitoring unit and the air purification unit, the system can monitor the concentration of various pollutants in the operating room in real time, and automatically adjust the operation of the air purification equipment according to the real-time air quality index, to ensure the cleanliness and safety of the air in the operating room, and help reduce the risk of cross infection. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the contents of the embodiments of the present invention and these drawings without paying any creative work.

[0059] Figure 1 This is a structural block diagram of an operating room multifunctional environmental control system based on Internet of Things technology of the present invention.

[0060] In the figure: 1. Voice collection unit; 2. Environmental control unit; 3. Voice recognition unit; 4. Environmental data collection unit; 5. Automatic control unit; 6. Automatic lighting adjustment unit; 7. Pattern matching unit; 8. Air monitoring unit; 9. Air purification unit. DETAILED DESCRIPTION

[0061] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0062] In the description of the present invention, unless otherwise clearly specified and limited, the terms "connected", "connected", and "fixed" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0064] In the description of this embodiment, the terms "upper", "lower", "left", "right" and other directions or positional relationships are based on the directions or positional relationships shown in the drawings, and are only for the convenience of description and simplification of operation, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operate in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used to distinguish in the description and have no special meaning.

[0065] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0066] Embodiment 1, as Figure 1 As shown, the present invention proposes a multifunctional operating room environment control system based on the Internet of Things technology, including an environment control unit 2, an automatic control unit 5, an automatic lighting adjustment unit 6, a pattern matching unit 7, an air monitoring unit 8 and an air purification unit 9, and also includes:

[0067] The voice collection unit 1 collects the voice of the operating room administrator by setting an audio collection device in a target area in the operating room to obtain the environment control voice, and pre-processes the environment control voice to obtain the standard environment control voice, and transmits the standard environment control voice to the voice recognition unit 3;

[0068] The speech recognition unit 3 receives the standard environment control speech transmitted by the speech acquisition unit 1, and performs speech recognition on the standard environment control speech through the trained speech recognition model to obtain environment control keywords, matches the environment control keywords with the environment control table pre-stored in the database to obtain environment control information corresponding to the environment control keywords, and transmits the environment control information to the environment control unit 2 and the pattern matching unit 7;

[0069] The environmental data acquisition unit 4 is used to collect environmental data of the target area by setting a sensor group in the target area in the operating room to obtain the environmental data of the target area. The sensor group includes a temperature sensor and a humidity sensor. The environmental data includes temperature and humidity, and the environmental data of the target area is transmitted to the automatic control unit 5.

[0070] In the present invention, the audio acquisition device is usually a high-quality microphone or microphone device specially designed for use in a medical environment. The main function of these devices is to accurately capture voice signals in the operating room, including the speech or control instructions of doctors or operating room administrators; the speech recognition model usually refers to a trained machine learning model for converting voice signals into text or keywords. These models are usually based on deep learning technology, especially recurrent neural networks or their variants, such as long short-term memory networks or gated recurrent units and transcription autoencoders.

[0071] In an optional embodiment, the automatic control unit 5 receives the environmental data of the target area transmitted by the environmental data acquisition unit 4, and constructs an environmental control model based on the environmental data of the target area. The environmental control model includes a state space, an action space, and a reward function. The environmental control model is solved based on a reinforcement learning algorithm to obtain controllable variables of the HVAC system, and the controllable variables are transmitted to the environmental control unit 2.

[0072] It should be noted that reinforcement learning algorithms are a type of machine learning method that aims to optimize a certain goal through interactive learning with the environment; HVAC systems refer to systems that integrate heating, ventilation, and air conditioning functions, and are designed to regulate the temperature, humidity, and fluidity of indoor air to create a comfortable indoor environment. These systems are usually composed of multiple components and devices.

[0073] In an optional embodiment, the automatic light adjustment unit 6 is used to perform adaptive light adjustment on the lighting area in the operating room by an automatic light adjustment method to obtain adaptive light adjustment information and transmit the information to the environment control unit 2 .

[0074] It should be noted that automatic lighting adjustment is a technology that automatically adjusts the brightness and color temperature of lighting equipment through sensors, control systems and execution mechanisms to adapt to different environments and needs.

[0075] In an optional embodiment, the pattern matching unit 7 receives the environmental control information transmitted by the voice recognition unit 3, and records the quantity of the environmental control information to obtain multiple commonly used environmental control information, sequentially number the multiple commonly used environmental control information, and match and map the sequential numbers with the control terminal, and display the multiple commonly used environmental control information on the control terminal according to the sequential numbers. The operating room administrator selects the commonly used environmental control information through the control terminal and transmits the selected commonly used environmental control information to the environmental control unit 2.

[0076] In an optional embodiment, the environmental control unit 2 receives the environmental control information transmitted by the voice recognition unit 3, the controllable variables transmitted by the automatic control unit 5, the light adaptive adjustment information transmitted by the automatic light adjustment unit 6, and the common environmental control information transmitted by the pattern matching unit 7, and controls the environmental status in the operating room through the environmental control method.

[0077] In an optional embodiment, the air monitoring unit 8 is used to monitor the concentrations of various pollutants in the operating room through air quality sensors to obtain real-time concentrations of various pollutants, and calculate the real-time air quality sub-indices of various pollutants based on the real-time concentrations of various pollutants, and calculate the real-time air quality index based on the real-time air quality sub-indices of various pollutants, and transmit the real-time air quality index to the air purification unit 9.

[0078] In an optional embodiment, the air purification unit 9 receives the real-time air quality index transmitted by the air monitoring unit 8, and maps the air quality index with the air purifier operating time to obtain a mapping table, matches the real-time air quality index with the mapping table to obtain the air purifier operating time corresponding to the real-time air quality index, and controls the operation of the air purifier based on the air purifier operating time.

[0079] It should be noted that a mapping table is a data structure used to map the real-time air quality index to the corresponding air purifier operating time. This mapping table is usually a pre-set table or function, which contains different air quality index ranges and corresponding air purifier operating times.

[0080] Embodiment 2, the present invention proposes a multifunctional operating room environment control system based on the Internet of Things technology. Compared with embodiment 1, this embodiment also includes: the calculation formula of the real-time air quality index of various pollutants is as follows:

[0081]

[0082] Among them, R represents a single pollutant, IAQI R Represents the air quality index of a single pollutant R, IAQI Lo and IAQI Hi Respectively represent and BR Lo and BR Hi The corresponding air quality index, BR Lo and BR Hi They represent the lower and upper values ​​of the pollutant concentration limit values ​​close to the concentration value of a single pollutant R, respectively. R Represents the mass concentration value of a single pollutant R;

[0083] The calculation formula of real-time air quality index is as follows:

[0084] AQI=max{IAQI1,IAQI2,...,IAQI k ,...,IAQI n};

[0085] Among them, AQI represents the real-time air quality index, n represents the number of pollutant types, and IAQI k represents the kth pollutant.

[0086] In an optional embodiment, constructing an environmental control model based on environmental data of a target area includes the following steps:

[0087] A1. The environmental data at the same time is converted through a conversion formula to obtain a state space. The conversion formula includes a temperature conversion formula and a humidity conversion formula. The temperature conversion formula is as follows:

[0088]

[0089] Among them, t e ' m represents the temperature after conversion, t em Indicates the temperature before conversion, T low,bo Indicates the lower limit of temperature setting, T up,bo Indicates the upper limit of temperature setting;

[0090] The temperature conversion formula is as follows:

[0091]

[0092] Among them, R′ H Represents the converted humidity, R H Represents the humidity before conversion, R low,bo Indicates the lower limit of humidity setting, R up,bo Indicates the upper limit of humidity setting;

[0093] A2. Define temperature penalty term and humidity penalty term based on the state space, and define reward function based on temperature penalty term and humidity penalty term. The reward function is as follows:

[0094] R eward =-k1p tem -k2p RH ;

[0095] Among them, R eward represents the reward, k1 and k2 represent the temperature penalty coefficient and humidity penalty coefficient, p tem and p RH represents the temperature penalty term and the humidity penalty term, and and

[0096] A3. The air supply volume of the HVAC system is used as the action space. The action space is as follows:

[0097] A=[a0,a1,a2,a3]=[0,50%,75%,100%];

[0098] Among them, A represents the action space, and a0, a1, a2, and a3 represent the control actions in the action space.

[0099] In an optional embodiment, the automatic lighting adjustment method includes the following steps:

[0100] B1. Divide the lighting area in the operating room into multiple defined areas, and collect the boundary conditions of the defined areas through a convolutional neural network to obtain the initial values ​​of the boundary conditions of the defined areas. The calculation formula of the boundary conditions is as follows:

[0101]

[0102] Among them, t x ,t y ,t g and t k represents the corresponding coordinate values ​​of each bounding box on each limited area predicted by the convolutional neural network, x and y represent the values ​​of x and y in the rectangular coordinate system, g and k represent the height and width of the bounding box, and n x and n y Indicates the degree of deviation of the target from the set center position, p g and pk Represents the predicted bounding box corresponding to the height and width, m x and m y represents the boundary condition, m g and m k Indicates the height and width position of the corresponding point;

[0103] B2. Set a data acquisition cycle to regularly acquire the location of the indoor personnel in the operating room, define the connected area of ​​the indoor personnel as a closed body, and simplify the circle domain of the closed body radius with the lighting point as the center of the circle, and define an error compensation function to compensate the error of the closed body to obtain the closed body compensation value. The closed body definition formula is as follows:

[0104] U={u||uP j ||≤R b ,u∈A};

[0105] Among them, U represents the definition of the closed space, u represents any point in the closed space, and P j represents the number of grid intersections of the normalized input space partition, R b represents the radius of the closed body, and A represents the normalized input space;

[0106] The error compensation function is as follows:

[0107] y k =S k[ b1,b2,...,b L ][q1,q2,...,q L ] T ;

[0108] Among them, y k Indicates the error compensation value, S k represents the weight coefficient, b L represents the Gaussian function value, q L represents the weight coefficient vector;

[0109] B3. Calculate the distribution of the lighting intensity field in the closed body according to the current illuminance value in the closed body to obtain the total light intensity in the closed body. The distribution formula of the lighting intensity field is as follows:

[0110]

[0111] Among them, I total (x, y) represents the total light intensity, N represents the sum of illumination, i represents the number of sampling times, u represents the wave field, and t represents time;

[0112] B4. Perform iterative judgment on all indoor personnel. When the total light intensity in the enclosure is within the preset optimal lighting range, no light adjustment is performed. When the total light intensity in the enclosure is greater than the preset upper limit of the optimal lighting range, the lighting intensity of the lighting area corresponding to the enclosure is reduced. When the total light intensity in the enclosure is less than the lower limit of the optimal lighting range, the lighting intensity of the lighting area corresponding to the enclosure is increased, thereby obtaining light adaptive adjustment information.

[0113] In an optional embodiment, the environmental control method comprises the following steps:

[0114] C1, judging whether the operating room administrator actively controls the environmental status in the operating room, if it is in the active control state, then performing environmental control according to the environmental control information and the common environmental control information, otherwise, executing step C2;

[0115] C2. Control the air supply volume of the HVAC system according to the controllable variables, and control the lighting area in the operating room according to the adaptive lighting adjustment information.

[0116] In an optional embodiment, determining whether the operating room administrator actively controls the environmental state in the operating room includes the following steps:

[0117] D1, determine whether the environmental control information is received, if the environmental control information is received, it is in the active control state, otherwise, execute step D2;

[0118] D2. Determine whether common environment control information is received. If common environment control information is received, it is in active control state.

[0119] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, various obvious changes, readjustments and substitutions can be made without departing from the protection scope of the present invention. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A multifunctional operating room environment control system based on Internet of Things technology, comprising an environment control unit, an automatic control unit, a lighting automatic adjustment unit, a pattern matching unit, an air monitoring unit and an air purification unit, characterized in that: It also includes: a voice collection unit, a voice recognition unit and an environmental data collection unit; The voice collection unit collects the voice of the operating room administrator by setting an audio collection device in the target area of ​​the operating room to obtain the environment control voice, and pre-processes the environment control voice to obtain the standard environment control voice, and transmits the standard environment control voice to the voice recognition unit; The speech recognition unit receives the standard environment control speech transmitted by the speech acquisition unit, and performs speech recognition on the standard environment control speech through a trained speech recognition model to obtain environment control keywords, matches the environment control keywords with an environment control table pre-stored in a database to obtain environment control information corresponding to the environment control keywords, and transmits the environment control information to the environment control unit and the pattern matching unit; The environmental data acquisition unit collects the environmental data of the target area by setting a sensor group in the target area in the operating room to obtain the environmental data of the target area, the sensor group includes a temperature sensor and a humidity sensor, the environmental data includes temperature and humidity, and the environmental data of the target area is transmitted to the automatic control unit.

2. According to claim 1, a multifunctional operating room environment control system based on Internet of Things technology is characterized in that: The automatic control unit receives the environmental data of the target area transmitted by the environmental data acquisition unit, and constructs an environmental control model based on the environmental data of the target area, wherein the environmental control model includes a state space, an action space and a reward function, and solves the environmental control model based on a reinforcement learning algorithm to obtain controllable variables of a HVAC system, and transmits the controllable variables to the environmental control unit.

3. According to claim 1, a multifunctional operating room environment control system based on Internet of Things technology is characterized in that: The automatic light adjustment unit is used to perform adaptive light adjustment on the lighting area in the operating room through an automatic light adjustment method to obtain adaptive light adjustment information and transmit the information to the environment control unit.

4. The multifunctional operating room environment control system based on Internet of Things technology according to claim 1 is characterized in that: The pattern matching unit receives the environmental control information transmitted by the voice recognition unit and records the quantity to obtain multiple commonly used environmental control information, sequentially number the multiple commonly used environmental control information, match and map the sequential numbers with the control terminal, and display multiple commonly used environmental control information on the control terminal according to the sequential numbers. The operating room administrator selects the commonly used environmental control information through the control terminal and transmits the selected commonly used environmental control information to the environmental control unit.

5. According to claim 1, the multifunctional operating room environment control system based on Internet of Things technology is characterized in that: The environmental control unit receives the environmental control information transmitted by the voice recognition unit, the controllable variables transmitted by the automatic control unit, the light adaptive adjustment information transmitted by the automatic light adjustment unit, and the common environmental control information transmitted by the pattern matching unit, and controls the environmental status in the operating room through the environmental control method.

6. The multifunctional operating room environment control system based on Internet of Things technology according to claim 1 is characterized in that: The air monitoring unit is used to monitor the concentrations of various pollutants in the operating room through air quality sensors to obtain real-time concentrations of various pollutants, calculate real-time air quality sub-indices of various pollutants based on the real-time concentrations of various pollutants, calculate real-time air quality index based on the real-time air quality sub-indices of various pollutants, and transmit the real-time air quality index to the air purification unit.

7. The multifunctional operating room environment control system based on Internet of Things technology according to claim 6 is characterized in that: The air purification unit receives the real-time air quality index transmitted by the air monitoring unit, and maps the air quality index with the air purifier operating time to obtain a mapping table, matches the real-time air quality index with the mapping table to obtain the air purifier operating time corresponding to the real-time air quality index, and controls the operation of the air purifier based on the air purifier operating time.

8. The multifunctional operating room environment control system based on Internet of Things technology according to claim 6 is characterized in that: The calculation formulas for the real-time air quality sub-indexes of various pollutants are as follows: Among them, R represents a single pollutant, IAQI R Represents the air quality index of a single pollutant R, IAQI Lo and IAQI Hi Respectively represent and BR Lo and BR Hi The corresponding air quality index, BR Lo and BR Hi They represent the lower and upper values ​​of the pollutant concentration limit values ​​close to the concentration value of a single pollutant R, respectively. R Represents the mass concentration value of a single pollutant R; The calculation formula of the real-time air quality index is as follows: AQI=max{IAQI1,IAQI2,...,IAQI k ,...,IAQI n }; Among them, AQI represents the real-time air quality index, n represents the number of pollutant types, and IAQI k represents the kth pollutant.

9. The multifunctional operating room environment control system based on Internet of Things technology according to claim 2 is characterized in that: Building an environmental control model based on the environmental data of the target area includes the following steps: A1. The environmental data at the same time is converted by a conversion formula to obtain a state space. The conversion formula includes a temperature conversion formula and a humidity conversion formula. The temperature conversion formula is as follows: Among them, t e ' m represents the temperature after conversion, t em Indicates the temperature before conversion, T low,bo Indicates the lower limit of temperature setting, T up,bo Indicates the upper limit of temperature setting; The temperature conversion formula is as follows: Among them, R′ H Represents the converted humidity, R H Represents the humidity before conversion, R low,bo Indicates the lower limit of humidity setting, R up,bo Indicates the upper limit of humidity setting; A2. Based on the state space, a temperature penalty term and a humidity penalty term are defined, and a reward function is defined based on the temperature penalty term and the humidity penalty term. The reward function is as follows: R eward =-k1p tem -k2p RH ; Among them, R eward represents the reward, k1 and k2 represent the temperature penalty coefficient and humidity penalty coefficient, p tem and p RH represents the temperature penalty term and the humidity penalty term, and and A3. The air supply volume of the HVAC system is used as the action space, and the action space is as follows: A=[a0,a1,a2,a3]=[0,50%,75%,100%]; Among them, A represents the action space, and a0, a1, a2, and a3 represent the control actions in the action space.

10. The multifunctional operating room environment control system based on Internet of Things technology according to claim 3 is characterized in that: The automatic lighting adjustment method comprises the following steps: B1. Divide the lighting area in the operating room into multiple defined areas, and collect boundary conditions of the defined areas through a convolutional neural network to obtain initial values ​​of the boundary conditions of the defined areas. The calculation formula of the boundary conditions is as follows: Among them, t x ,t y ,t g and t k represents the corresponding coordinate values ​​of each bounding box on each limited area predicted by the convolutional neural network, x and y represent the values ​​of x and y in the rectangular coordinate system, g and k represent the height and width of the bounding box, and n x and n y Indicates the degree of deviation of the target from the set center position, p g and p k Represents the predicted bounding box corresponding to the height and width, m x and m y represents the boundary condition, m g and m k Indicates the height and width position of the corresponding point; B2. Set a data acquisition cycle to regularly acquire the location of the indoor personnel in the operating room, define the connected area of ​​the indoor personnel as a closed body, simplify the circle domain of the closed body radius with the lighting point as the center, and define an error compensation function to perform error compensation on the closed body to obtain a closed body compensation value. The closed body definition formula is as follows: U={u||uP j ||≤R b ,u∈A}; Among them, U represents the definition of the closed space, u represents any point in the closed space, and P j represents the number of grid intersections of the normalized input space partition, R b represents the radius of the closed body, and A represents the normalized input space; The error compensation function is as follows: y k =S k [b1,b2,...,b L ][q1,q2,...,q L ] T ; Among them, y k Indicates the error compensation value, S k represents the weight coefficient, b L represents the Gaussian function value, q L represents the weight coefficient vector; B3. Calculate the distribution of the illumination intensity field in the closed body according to the current illumination value in the closed body to obtain the total illumination intensity in the closed body. The distribution formula of the illumination intensity field is as follows: Among them, I total (x, y) represents the total light intensity, N represents the sum of illumination, i represents the number of sampling times, u represents the wave field, and t represents time; B4. Iteratively judge all the indoor occupants. When the total light intensity in the enclosure is within the preset optimal lighting range, no light adjustment is performed. When the total light intensity in the enclosure is greater than the preset upper limit of the optimal lighting range, the lighting intensity of the lighting area corresponding to the enclosure is reduced. When the total light intensity in the enclosure is less than the lower limit of the optimal lighting range, the lighting intensity of the lighting area corresponding to the enclosure is increased, thereby obtaining light adaptive adjustment information.

11. The multifunctional operating room environment control system based on Internet of Things technology according to claim 5, characterized in that: The environmental control method comprises the following steps: C1, determining whether the operating room administrator actively controls the environmental status in the operating room, if in an active control state, performing environmental control according to the environmental control information and the common environmental control information, otherwise, executing step C2; C2. Controlling the air supply volume of the HVAC system according to the controllable variables, and controlling the lighting area in the operating room according to the adaptive lighting adjustment information.

12. The multifunctional operating room environment control system based on Internet of Things technology according to claim 11, characterized in that: Determining whether the operating room administrator actively controls the environmental state in the operating room includes the following steps: D1, judging whether the environmental control information is received, if the environmental control information is received, it is in the active control state, otherwise, executing step D2; D2. Determine whether the commonly used environment control information is received. If the commonly used environment control information is received, the system is in an active control state.

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