Intelligent ventilation control method and system for biological laboratory

Abstract

The invention provides an intelligent ventilation control method and system for a biological laboratory. The method comprises the steps that if it is monitored that the operation state of an air exhaust system is changed into a shutdown state, first working parameters of a ventilation system of the biological laboratory are determined according to shutdown parameters of the air exhaust system, and the ventilation system is controlled to execute weak air exhaust operation according to the first working parameters; shooting high-definition image data of an operation area of the biological safety cabinet, extracting biological experiment data from the high-definition image data, predicting the generation amount of harmful gas residues according to the biological experiment data, and determining a second working parameter of the ventilation system according to the generation amount of the harmful gas residues, and the ventilation system is controlled to execute strong exhaust operation according to the second working parameter. According to the scheme, after the air exhaust system of the biological safety cabinet is shut down, harmful gas in the biological laboratory can be exhausted by regulating and controlling the ventilation system in the biological laboratory, and it is ensured that a healthy air environment is kept in the biological laboratory all the time.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent biological laboratories, and in particular to an intelligent ventilation control method and system for biological laboratories. Background Art

[0002] Biological laboratories are places where biological research and experiments are carried out. They are usually equipped with advanced equipment and instruments to support research in various biological fields.

[0003] Certain biological experiments will produce harmful gases, which will have adverse effects on experimenters or equipment in biological laboratories. Therefore, the good operation of the ventilation system is a basic requirement for biological laboratories. In order to reduce the impact of harmful gases, biological laboratories generally use biological safety cabinets. The biological safety cabinets suck the air out of the cabinet to maintain a negative pressure state inside the cabinet, thus ensuring that the harmful gases generated by biological experiments conducted in the biological safety cabinet do not spread into the biological laboratory.

[0004] However, after the exhaust system of the biosafety cabinet is turned off, the negative pressure in the biosafety cabinet gradually becomes unstable and eventually remains the same as the atmospheric pressure in the biological laboratory. Therefore, the protective treatment effect of harmful gases for a period of time after the exhaust system is turned off will be greatly reduced; or, if biological experiments are still being carried out in the biosafety cabinet after the exhaust system is turned off, it is impossible to protect the harmful gases that continue to be generated. The existing technology has not yet effectively solved this technical problem. Summary of the invention

[0005] In order to at least solve the technical problems existing in the above-mentioned background technology, the present invention provides a biological laboratory intelligent ventilation control method, system, electronic equipment and computer storage medium.

[0006] The present invention provides a biological laboratory intelligent ventilation control method, comprising the following steps: Monitor the operating state of the exhaust system of the biological safety cabinet. If it is monitored that the operating state of the exhaust system changes to a shutdown state, determine the first working parameter of the ventilation system of the biological laboratory according to the shutdown parameter of the exhaust system, and control the ventilation system to perform a weak exhaust operation according to the first working parameter; Capture high-definition image data of the operating area of ​​the biological safety cabinet, extract biological experiment data from the high-definition image data, predict the amount of harmful gas residue generated based on the biological experiment data, determine the second operating parameter of the ventilation system based on the amount of harmful gas residue generated, and control the ventilation system to perform a strong exhaust operation according to the second operating parameter.

[0007] Furthermore, the monitoring of the operating state of the exhaust system of the biological safety cabinet includes: Communicate to obtain the operation plan data and / or stop button status data of the biosafety cabinet; Monitoring the operating state of the exhaust system of the biological safety cabinet according to the operating plan data and the current time to obtain the continued operating state or shutdown state of the exhaust system; And / or, judging whether the exhaust system is manually shut down according to the stop button status data, if so, judging that the exhaust system is in the shutdown state, otherwise judging that the exhaust system is in the continuous operation state.

[0008] Further, the first operating parameter of the ventilation system of the biological laboratory is determined according to the shutdown parameter of the exhaust system, including: Extracting the shutdown duration from the shutdown parameters of the exhaust system, and determining the external exhaust air velocity curve in the biosafety cabinet according to the shutdown duration; Acquire a third operating parameter currently being executed by the ventilation system, wherein the third operating parameter includes a first external exhaust flow velocity, and predict a second external exhaust flow velocity in the area where the biosafety cabinet is located based on the first external exhaust flow velocity; The external exhaust gas flow velocity curve and the second external exhaust gas flow velocity are input into a depth prediction model, and the depth prediction model outputs the first operating parameter.

[0009] Further, the predicting of a second external exhaust flow rate in the area where the biosafety cabinet is located according to the first external exhaust flow rate includes: Acquire the overall internal structure data of the biological laboratory and the regional structure data of the area where the biological safety cabinet is located, and construct a physical model of the biological laboratory based on the overall internal structure data and the regional structure data; The airflow condition is simulated based on the first external exhaust air flow velocity, the physical model and the regional structure data to obtain the second external exhaust air flow velocity in the area where the biosafety cabinet is located.

[0010] Furthermore, the prediction of the harmful gas residual generation amount based on the biological experimental data includes: Determine the type of biological experiment, the amount of experimental materials, and the experimental stage of the biological experiment according to the biological experiment data; The amount of harmful gas residue generated is predicted based on the type of biological experiment, the amount of experimental materials and the experimental stage.

[0011] Furthermore, the second operating parameter of the ventilation system is determined according to the amount of residual harmful gas generated, including: Determine a fourth operating parameter of the ventilation system according to the harmful gas residual generation amount and a preset comparison table; and extracting personnel presence data from the high-definition image data, and determining a correction coefficient based on the personnel presence data; The fourth operating parameter is adjusted to the second operating parameter using the correction coefficient, wherein the second operating parameter includes the third external exhaust air flow rate of the ventilation system.

[0012] The present invention also provides a biological laboratory intelligent ventilation control system, including a monitoring module, a shooting module, a weak processing module, and a strong processing module; wherein, The monitoring module is used to monitor the operating status of the exhaust system of the biosafety cabinet; The weak processing module is used to determine the first working parameter of the ventilation system of the biological laboratory according to the shutdown parameter of the exhaust system if it is monitored that the operating state of the exhaust system has changed to a shutdown state, and control the ventilation system to perform a weak exhaust operation according to the first working parameter; The shooting module is used to shoot high-definition image data of the operating area of ​​the biosafety cabinet; The strong processing module is used to extract biological experimental data from the high-definition image data, predict the amount of harmful gas residue generated based on the biological experimental data, determine the second working parameter of the ventilation system based on the amount of harmful gas residue generated, and control the ventilation system to perform strong exhaust operation according to the second working parameter.

[0013] The present invention also provides an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the method as described in any of the preceding items.

[0014] The present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, any of the above methods is executed.

[0015] The present invention also provides a computer program product, wherein a computer program in the computer program product is executed by a processor of an electronic device to implement any of the methods described above.

[0016] The solution of the present invention can exhaust harmful gases in the biological laboratory by regulating the ventilation system in the biological laboratory after the exhaust system of the biological safety cabinet is shut down, thereby ensuring that a healthy air environment is always maintained in the biological laboratory. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a flow chart of a biological laboratory intelligent ventilation control method disclosed in an embodiment of the present invention; Figure 2 It is a structural schematic diagram of an intelligent ventilation control system for a biological laboratory disclosed in an embodiment of the present invention; Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0020] like Figure 1 As shown, an embodiment of the present invention provides an intelligent ventilation control method for a biological laboratory, comprising the following steps: monitoring the operating state of an exhaust system of a biological safety cabinet, and if it is monitored that the operating state of the exhaust system changes to a shutdown state, determining a first working parameter of the ventilation system of the biological laboratory according to the shutdown parameter of the exhaust system, and controlling the ventilation system to perform a weak exhaust operation according to the first working parameter; Capture high-definition image data of the operating area of ​​the biological safety cabinet, extract biological experiment data from the high-definition image data, predict the amount of harmful gas residue generated based on the biological experiment data, determine the second operating parameter of the ventilation system based on the amount of harmful gas residue generated, and control the ventilation system to perform a strong exhaust operation according to the second operating parameter.

[0021] The present invention configures a ventilation system in the biological laboratory, and the biological safety cabinet in the biological laboratory is also configured with its own exhaust system. Under normal circumstances, the ventilation system and the exhaust system are both working normally. The exhaust system keeps the biological safety cabinet in a negative pressure state to prevent the harmful gases in the biological safety cabinet from diffusing into the biological laboratory; the ventilation system is used to keep the air in the biological laboratory updated and to discharge a small amount of harmful gases leaked from the biological safety cabinet. On this basis, the biological laboratory is also equipped with a monitoring device, which monitors the operating state of the exhaust system of the biological safety cabinet. If it is monitored that the operating state of the exhaust system changes to a shutdown state, the first working parameter of the ventilation system of the biological laboratory is determined according to the shutdown parameter of the exhaust system, and the ventilation system is controlled to be cut out from the conventional ventilation mode, and a weak ventilation operation is performed according to the first working parameter, that is, the exhaust air flow rate is controlled to be lower than the exhaust air flow rate in the conventional mode. Such a setting is conducive to maintaining the outward flow of air in the biological safety cabinet after the exhaust system is shut down.

[0022] At the same time, high-definition image data of the operation area of ​​the biosafety cabinet is also captured, and biological experiment data is extracted from the high-definition image data. Based on this, it can be determined whether there are any unfinished biological experiments in the operation area of ​​the biosafety cabinet, and the amount of harmful gas residue generated can be predicted. Then, the second working parameter of the ventilation system is determined based on the amount of harmful gas residue generated, and the ventilation system is controlled to switch from the first working parameter to the second working parameter to perform strong ventilation operation, that is, the exhaust air flow rate is controlled to be higher than the exhaust air flow rate in the normal mode. This setting ensures that after the exhaust system of the biosafety cabinet is shut down, the harmful gases generated by the unfinished biological experiments can still be discharged from the biological laboratory through the ventilation system.

[0023] Therefore, the solution of the present invention can exhaust harmful gases in the biological laboratory by regulating the ventilation system in the biological laboratory after the exhaust system of the biological safety cabinet is shut down, thereby ensuring that a healthy air environment is always maintained in the biological laboratory.

[0024] Furthermore, the monitoring of the operating state of the exhaust system of the biological safety cabinet includes: Communicate to obtain the operation plan data and / or stop button status data of the biosafety cabinet; Monitoring the operating state of the exhaust system of the biological safety cabinet according to the operating plan data and the current time to obtain the continued operating state or shutdown state of the exhaust system; And / or, judging whether the exhaust system is manually shut down according to the stop button status data, if so, judging that the exhaust system is in the shutdown state, otherwise judging that the exhaust system is in the continuous operation state.

[0025] In the embodiment of the present invention, the monitoring device monitors the operating state of the exhaust system of the biological safety cabinet in the above two ways. The monitoring device maintains a communication connection with the biological safety cabinet to obtain the pre-set operation plan data of the biological safety cabinet, and the operation plan data includes the shutdown time of the exhaust system. By comparing and analyzing the shutdown time with the current time, it can be determined whether the exhaust system of the biological safety cabinet is in a continuous operation state or a shutdown state.

[0026] The monitoring device can also obtain the stop button status data of the stop button of the exhaust system of the biological safety cabinet. When the stop button status data indicates that the stop button is pressed, it can be determined that the exhaust system of the biological safety cabinet is switched to the stop state, otherwise it continues to operate.

[0027] Further, the first operating parameter of the ventilation system of the biological laboratory is determined according to the shutdown parameter of the exhaust system, including: Extracting the shutdown duration from the shutdown parameters of the exhaust system, and determining the external exhaust air velocity curve in the biosafety cabinet according to the shutdown duration; Acquire a third operating parameter currently being executed by the ventilation system, wherein the third operating parameter includes a first external exhaust flow velocity, and predict a second external exhaust flow velocity in the area where the biosafety cabinet is located based on the first external exhaust flow velocity; The external exhaust gas flow velocity curve and the second external exhaust gas flow velocity are input into a depth prediction model, and the depth prediction model outputs the first operating parameter.

[0028] In an embodiment of the present invention, after the exhaust system is shut down, the ventilation system in the biological laboratory is configured to weaken its own external exhaust intensity to adapt to the gradual weakening of the exhaust flow inside and outside the biological safety cabinet, so as to extend the maintenance time of the outward circulation of the air flow in the biological safety cabinet as much as possible.

[0029] In this regard, the present invention first extracts the shutdown duration from the shutdown parameters of the exhaust system. The shutdown duration is the duration of the rotation speed of the exhaust system decreasing until it stops rotating after the shutdown command is executed. During this period, the flow rate of the external exhaust airflow in the biological safety cabinet gradually weakens. According to the shutdown duration, the external exhaust airflow velocity curve in the biological safety cabinet can be determined. The determination of the external exhaust airflow velocity curve can be obtained through a pre-determined control relationship. The control relationship is the external exhaust airflow velocity curve corresponding to different shutdown durations determined in advance. Of course, the control relationship can also be determined separately on the basis of the exhaust gear of the exhaust system. When comparing and comparing, it is also necessary to be based on the real-time exhaust gear, which will not be described in detail.

[0030] Then, the third working parameter currently being executed by the ventilation system is obtained, and the third working parameter includes a first external exhaust flow velocity, which is the external exhaust flow velocity at the exhaust port of the ventilation system. However, the external exhaust flow velocity at the exhaust port is not equal to the external exhaust flow velocity of the area where the biosafety cabinet is located. In this regard, the present invention further provides a method for predicting a second external exhaust flow velocity in the area where the biosafety cabinet is located based on the first external exhaust flow velocity obtained above.

[0031] Finally, the aforementioned external exhaust air velocity curve and the second external exhaust air velocity are input into the deep prediction model, and the deep prediction model outputs the first working parameter of the ventilation system. Therefore, the ventilation system performs ventilation operation on the biological laboratory according to the first working parameter, thereby achieving the technical purpose of extending the maintenance time of the airflow outward circulation in the biological safety cabinet as much as possible.

[0032] Among them, the deep prediction model is preferably constructed based on the Transformer model, which mainly includes an encoder, a self-attention mechanism, multi-head self-attention, a feedforward fully connected layer, a residual connection, a decoder, etc. Pre-collect multiple sets of data corresponding to the external exhaust airflow velocity curves and the second external exhaust airflow velocity, and measure the corresponding maintenance time of the situation of the airflow in the biosafety cabinet flowing outward, and use the maintenance time as the label data to construct a training data set to train the deep prediction model.

[0033] Further, the predicting of a second external exhaust flow rate in the area where the biosafety cabinet is located according to the first external exhaust flow rate includes: Acquire the overall internal structure data of the biological laboratory and the regional structure data of the area where the biological safety cabinet is located, and construct a physical model of the biological laboratory based on the overall internal structure data and the regional structure data; The airflow condition is simulated based on the first external exhaust air flow velocity, the physical model and the regional structure data to obtain the second external exhaust air flow velocity in the area where the biosafety cabinet is located.

[0034] In the embodiment of the present invention, the overall internal structure data of the biological laboratory and the regional structure data of the area where the biological safety cabinet is located can be obtained in advance. For example, the monitoring device can extract the structural data of each area in the biological laboratory through image recognition technology, and the physical model of the biological laboratory can be constructed based on this. Then, the air flow condition is simulated based on the first external exhaust air flow velocity, the physical model and the regional structure data, and then the second external exhaust air flow velocity in the area where the biological safety cabinet is located is obtained.

[0035] Among them, the above simulation process can use turbulence models such as k-ε two-equation model and RANS model to describe the turbulent characteristics of indoor airflow. In addition, in recent years, data-driven models have been more and more widely used in indoor airflow simulation. These models can improve the prediction accuracy of indoor anisotropic flow by using a large amount of experimental data or simulation data for training. Therefore, the above simulation process of the present invention can also be implemented by using data-driven models such as RANS models driven by artificial neural network data.

[0036] Furthermore, the prediction of the harmful gas residual generation amount based on the biological experimental data includes: Determine the type of biological experiment, the amount of experimental materials, and the experimental stage of the biological experiment according to the biological experiment data; The amount of harmful gas residue generated is predicted based on the type of biological experiment, the amount of experimental materials and the experimental stage.

[0037] In an embodiment of the present invention, the monitoring device can capture high-definition image data of the operating area of ​​the biosafety cabinet, and directly extract the type of biological experiment and the amount of experimental materials from it through image recognition technology. The biological experiment types include the cultivation of pathogenic microorganisms, PCR (polymerase chain reaction) and DNA sequencing experiments, etc. These biological experiments themselves or the reagents used may release harmful gases to the outside. At the same time, it is also possible to obtain the current experimental stage of the biological experiment by communicating with the biosafety cabinet, and the amount of harmful gas released in different experimental stages is different. Therefore, based on the type of biological experiment, the amount of experimental materials and the experimental stage, it is possible to predict the amount of harmful gas residue generated after the exhaust system is actually shut down (that is, the exhaust fan stops rotating, and the external exhaust flow rate of the biosafety cabinet is less than the preset value). Among them, the prediction of the amount of harmful gas residue generated in this embodiment can also be achieved based on a model, for example, based on a Transformer model, which will not be described in detail.

[0038] Furthermore, the second operating parameter of the ventilation system is determined according to the amount of residual harmful gas generated, including: Determine a fourth operating parameter of the ventilation system according to the harmful gas residual generation amount and a preset comparison table; and extracting personnel presence data from the high-definition image data, and determining a correction coefficient based on the personnel presence data; The fourth operating parameter is adjusted to the second operating parameter using the correction coefficient, wherein the second operating parameter includes the third external exhaust air flow rate of the ventilation system.

[0039] In an embodiment of the present invention, a comparison table of the fourth working parameter of the ventilation system and the amount of residual harmful gas generated is pre-established. The fourth working parameter corresponding to the amount of residual harmful gas generated in the comparison table can ensure that the harmful gas is discharged from the biological laboratory within a preset time (for example, half a minute). At the same time, whether there are relevant personnel in the biological laboratory will also affect the exhaust time of the harmful gas. Generally speaking, when there are relevant personnel in the biological laboratory, it is necessary to speed up the exhaust of harmful gases, and the more people are present, the faster the harmful gas needs to be discharged. In this regard, the present invention is further configured to extract the presence of personnel data from the high-definition image data, and the presence of personnel data includes whether there are personnel and the number of personnel. According to the presence of personnel data, a correction coefficient is determined, and the fourth working parameter is adjusted to the second working parameter using the correction coefficient. Among them, when there is no personnel present, the correction coefficient is 1, that is, the fourth working parameter mentioned above is not corrected; when there is a person present, the correction coefficient is set to be positively correlated with the number of people present. However, the present invention does not limit the expression form of the positive correlation calculation formula between the correction coefficient and the number of people present.

[0040] like Figure 2 As shown, the embodiment of the present invention also discloses a biological laboratory intelligent ventilation control system, including a monitoring module, a shooting module, a weak processing module, and a strong processing module; wherein, The monitoring module is used to monitor the operating status of the exhaust system of the biosafety cabinet; The weak processing module is used to determine the first working parameter of the ventilation system of the biological laboratory according to the shutdown parameter of the exhaust system if it is monitored that the operating state of the exhaust system has changed to a shutdown state, and control the ventilation system to perform a weak exhaust operation according to the first working parameter; The shooting module is used to shoot high-definition image data of the operating area of ​​the biosafety cabinet; The strong processing module is used to extract biological experimental data from the high-definition image data, predict the amount of harmful gas residue generated based on the biological experimental data, determine the second working parameter of the ventilation system based on the amount of harmful gas residue generated, and control the ventilation system to perform strong exhaust operation according to the second working parameter.

[0041] like Figure 3 As shown, an embodiment of the present invention further discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the method described in any of the preceding items.

[0042] An embodiment of the present invention further discloses a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, any of the above methods is executed.

[0043] An embodiment of the present invention further discloses a computer program product, in which a computer program in the computer program product is executed by a processor of an electronic device to implement any of the above methods.

[0044] The processor in the electronic device of the present invention can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) or a computer program loaded from a memory into a random access memory (RAM). In the RAM, various programs and data required for memory operation can also be stored. The processor, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0045] Many components in an electronic device are connected to the I / O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of displays, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, such as network cards, modems, wireless communication transceivers, etc. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks.

[0046] The processor may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of processors include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor performs the various methods and processes described above, such as the response perception method. For example, in some embodiments, the response perception method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a memory. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via a ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the processor, one or more steps of the response perception method described above may be performed. Alternatively, in other embodiments, the processor may be configured to perform the response perception method in any other appropriate manner (e.g., by means of firmware).

[0047] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0048] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0049] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0050] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0051] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0052] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0053] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0054] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A biological laboratory intelligent ventilation control method, characterized in that: The steps include: Monitor the operating state of the exhaust system of the biological safety cabinet. If it is monitored that the operating state of the exhaust system changes to a shutdown state, determine the first working parameter of the ventilation system of the biological laboratory according to the shutdown parameter of the exhaust system, and control the ventilation system to perform a weak exhaust operation according to the first working parameter; Capture high-definition image data of the operating area of ​​the biological safety cabinet, extract biological experiment data from the high-definition image data, predict the amount of harmful gas residue generated based on the biological experiment data, determine the second operating parameter of the ventilation system based on the amount of harmful gas residue generated, and control the ventilation system to perform a strong exhaust operation according to the second operating parameter.

2. According to claim 1, a biological laboratory intelligent ventilation control method is characterized by: The monitoring of the operating state of the exhaust system of the biological safety cabinet includes: Communicate to obtain the operation plan data and / or stop button status data of the biosafety cabinet; Monitoring the operating state of the exhaust system of the biological safety cabinet according to the operating plan data and the current time to obtain the continued operating state or shutdown state of the exhaust system; And / or, judging whether the exhaust system is manually shut down according to the stop button status data, if so, judging that the exhaust system is in the shutdown state, otherwise judging that the exhaust system is in the continuous operation state.

3. A biological laboratory intelligent ventilation control method according to claim 2, characterized in that: Determining the first operating parameter of the ventilation system of the biological laboratory according to the shutdown parameter of the exhaust system includes: Extracting the shutdown duration from the shutdown parameters of the exhaust system, and determining the external exhaust air velocity curve in the biosafety cabinet according to the shutdown duration; Acquire a third operating parameter currently being executed by the ventilation system, wherein the third operating parameter includes a first external exhaust flow velocity, and predict a second external exhaust flow velocity in the area where the biosafety cabinet is located based on the first external exhaust flow velocity; The external exhaust gas flow velocity curve and the second external exhaust gas flow velocity are input into a depth prediction model, and the depth prediction model outputs the first operating parameter.

4. A biological laboratory intelligent ventilation control method according to claim 3, characterized in that: The step of predicting a second external exhaust flow rate in the area where the biosafety cabinet is located based on the first external exhaust flow rate comprises: Acquire the overall internal structure data of the biological laboratory and the regional structure data of the area where the biological safety cabinet is located, and construct a physical model of the biological laboratory based on the overall internal structure data and the regional structure data; The airflow condition is simulated based on the first external exhaust air flow velocity, the physical model and the regional structure data to obtain the second external exhaust air flow velocity in the area where the biosafety cabinet is located.

5. A biological laboratory intelligent ventilation control method according to claim 4, characterized in that: The prediction of the harmful gas residual generation amount based on the biological experimental data includes: Determine the type of biological experiment, the amount of experimental materials, and the experimental stage of the biological experiment according to the biological experiment data; The amount of harmful gas residue generated is predicted based on the type of biological experiment, the amount of experimental materials and the experimental stage.

6. A biological laboratory intelligent ventilation control method according to claim 5, characterized in that: The determining of the second operating parameter of the ventilation system according to the amount of harmful gas residue generated comprises: Determine a fourth operating parameter of the ventilation system according to the harmful gas residual generation amount and a preset comparison table; and extracting personnel presence data from the high-definition image data, and determining a correction coefficient based on the personnel presence data; The fourth operating parameter is adjusted to the second operating parameter using the correction coefficient, wherein the second operating parameter includes the third external exhaust air flow rate of the ventilation system.

7. An intelligent ventilation control system for a biological laboratory, characterized by: It includes monitoring module, shooting module, weak processing module and strong processing module; among them, The monitoring module is used to monitor the operating status of the exhaust system of the biosafety cabinet; The weak processing module is used to determine the first working parameter of the ventilation system of the biological laboratory according to the shutdown parameter of the exhaust system if it is monitored that the operating state of the exhaust system has changed to a shutdown state, and control the ventilation system to perform a weak exhaust operation according to the first working parameter; The shooting module is used to shoot high-definition image data of the operating area of ​​the biosafety cabinet; The strong processing module is used to extract biological experimental data from the high-definition image data, predict the amount of harmful gas residue generated based on the biological experimental data, determine the second working parameter of the ventilation system based on the amount of harmful gas residue generated, and control the ventilation system to perform strong exhaust operation according to the second working parameter.

8. An electronic device, comprising: A memory storing executable program code; A processor coupled to the memory; characterized in that: the processor calls the executable program code stored in the memory to execute the method according to any one of claims 1-6.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is executed.

10. A computer program product, characterized in that: The computer program in the computer program product is executed by a processor of an electronic device to implement the method according to any one of claims 1 to 6.

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