Gas detection method and device based on multiple sensors and medium

Abstract

The invention relates to a gas detection method and device based on multiple sensors and a medium, the multiple sensors comprise multiple gas sensors and one or more environment sensors, and the method comprises the following steps: acquiring real-time concentration information of multiple gases through the gas sensors; acquiring real-time environment information through an environment sensor; for the real-time concentration information collected by each gas sensor, the real-time credibility of the gas sensor is determined according to the historical accuracy and the real-time environment information of the gas sensor; if the real-time credibility is smaller than or equal to a credibility threshold value, determining a first target weight about a historical mean value of the gas sensor according to the real-time credibility; and adjusting the real-time concentration information according to the real-time concentration information, the historical mean value and the first target weight so as to obtain the adjusted real-time concentration information. And in a multi-gas environment, the detection precision of the gas sensor is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of gas detection, and in particular to a multi-sensor based gas detection method, equipment and medium. Background Art

[0002] With technological advancements, the need for gas detection is increasing in both civilian and industrial settings. The civilian market has relatively low performance requirements and offers low prices, but detection accuracy and reliability are low. The industrial market, on the other hand, places higher demands on product quality and performance. Currently, most civilian and industrial gas detectors can only detect a single gas. However, gas detection is often required in scenarios involving more than just one gas. When multiple gases are present, or when detecting multiple gases simultaneously, improving gas detection accuracy has become a pressing technical challenge in existing technologies. Summary of the Invention

[0003] The first object of the present invention is to provide a gas detection method, device and medium based on multiple sensors.

[0004] According to one aspect of the present application, a multi-sensor based gas detection method is provided, wherein the multi-sensor includes multiple gas sensors and one or more environmental sensors, and the method includes: Obtain real-time concentration information of various gases through gas sensors; obtain real-time environmental information through environmental sensors; For the real-time concentration information collected by each gas sensor, the real-time credibility of the gas sensor is determined based on the historical accuracy of the gas sensor and the real-time environmental information; If the real-time credibility is less than or equal to the credibility threshold, determining a first target weight for the historical mean value of the gas sensor according to the real-time credibility; The real-time concentration information is adjusted according to the real-time concentration information, the historical mean, and the first target weight to obtain adjusted real-time concentration information.

[0005] According to another aspect of the present application, a computer device for gas detection is provided, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the above-mentioned method.

[0006] According to another aspect of the present application, a computer-readable storage medium is provided, storing a computer program that can be loaded by a processor and execute the above method.

[0007] Compared with the prior art, the present application adjusts the real-time concentration information obtained by the corresponding gas sensors by setting up multiple gas sensors and one or more environmental sensors to ensure the accuracy of the gas sensor. Specifically, the historical accuracy of the gas sensor is adjusted according to the real-time environmental information to obtain the real-time credibility of the gas sensor. If the real-time credibility is less than or equal to the credibility threshold, the historical mean and real-time concentration information of the gas sensor are weighted according to the real-time credibility to determine the first target weight for the historical mean. The real-time concentration information is adjusted according to the real-time concentration information, the historical mean, and the first target weight to obtain the adjusted real-time concentration information. In a multi-gas environment, the detection accuracy of the gas sensor is ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flow chart of a method for gas detection based on multiple sensors according to an embodiment of the present application is shown; Figure 2 A schematic structural diagram of a multi-sensor gas detection device according to an embodiment of the present application is shown; Figure 3 FIGURES illustrate exemplary systems that can be used to implement the various embodiments described herein. DETAILED DESCRIPTION

[0009] The present application is described in further detail below with reference to the accompanying drawings.

[0010] In a typical configuration of the present application, the terminal, the device of the service network, and the trusted party each include one or more processors (eg, a central processing unit (CPU)), an input / output interface, a network interface, and a memory.

[0011] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory. Memory is an example of a computer-readable medium.

[0012] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PCM), programmable random access memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0013] The devices referred to in this application include, but are not limited to, terminals, network devices, or devices formed by integrating terminals and network devices via a network. The terminals include, but are not limited to, any mobile electronic product that can interact with a user (e.g., through a touchpad), such as a smartphone, a tablet computer, etc. The mobile electronic product can use any operating system, such as the Android operating system, the iOS operating system, etc. The network device includes an electronic device that can automatically perform numerical calculations and information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, a microprocessor, an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc. The network device includes, but is not limited to, a computer, a network host, a single network server, a set of multiple network servers, or a cloud consisting of multiple servers; herein, a cloud is composed of a large number of computers or network servers based on cloud computing. Cloud computing is a type of distributed computing, a virtual supercomputer composed of a group of loosely coupled computers. The network includes but is not limited to the Internet, a wide area network, a metropolitan area network, a local area network, a VPN network, a wireless self-organizing network (Ad Hoc network), etc. Preferably, the device may also be a program running on the terminal, the network device, or a device formed by integrating the terminal and the network device, the network device, the touch terminal, or the network device and the touch terminal via a network.

[0014] Of course, those skilled in the art should understand that the above-mentioned devices are only examples, and other existing or future devices that are applicable to this application should also be included in the scope of protection of this application and are included here by reference.

[0015] In the description of the present application, “plurality” means two or more, unless otherwise clearly defined.

[0016] refer to Figure 1An embodiment of the present invention provides a flow chart of a multi-sensor-based gas detection method. The multi-sensor includes multiple gas sensors and one or more environmental sensors. The method includes steps S11, S12, and S13. In step S11, real-time concentration information of multiple gases is acquired through gas sensors; real-time environmental information is acquired through environmental sensors. In step S12, for the real-time concentration information collected by each gas sensor, the real-time credibility of the gas sensor is determined based on the gas sensor's historical accuracy and real-time environmental information. In step S13, if the real-time credibility is less than or equal to a credibility threshold, a first target weight for the historical average of the gas sensor is determined based on the real-time credibility. In step S14, the real-time concentration information is adjusted based on the real-time concentration information, the historical average, and the first target weight to obtain adjusted real-time concentration information. In some embodiments, gas sensors include but are not limited to CO sensors, CH4 sensors, CO2 sensors, etc. In some embodiments, the environmental sensors and gas sensors are a combination of sensors for a specific scenario. For example, a combination of a CO sensor, a CH4 sensor (e.g., MOS), a CO2 sensor (e.g., NDIR), and a temperature sensor for combustion scenarios. Another example is a combination of an HCHO sensor (e.g., an electrochemical sensor), a TVOC sensor, a CO2 sensor, a humidity sensor, and a temperature sensor for indoor formaldehyde detection. Another example is a combination of a CH4 sensor, a CO2 sensor, an H2S sensor, and a temperature sensor for biogas fermentation. Environmental sensors include, but are not limited to, temperature sensors and humidity sensors. In some embodiments, multiple sensors can be integrated into a single portable device, which performs gas detection. Multiple sensors are electrically connected to a computing device, which performs gas detection. In some embodiments, the computing device includes, but is not limited to, a computer, a tablet computer, a control module, and the like.

[0017] Specifically, in step S11, real-time concentration information of multiple gases is acquired through gas sensors. Real-time environmental information is acquired through environmental sensors. For example, real-time concentration information (e.g., ppm) of CO, CH4, and CO2 is acquired through a CO sensor, a CH4 sensor, and a CO2 sensor, respectively. Real-time temperature information is acquired through a temperature sensor.

[0018] In step S12, for the real-time concentration information collected by each gas sensor, the real-time credibility of the gas sensor is determined based on the historical accuracy of the gas sensor and the real-time environmental information. In some embodiments, each gas sensor has a corresponding historical accuracy. The historical accuracy can be obtained in advance through experiments or determined based on the maximum error of the sensor provided by the manufacturer. For example, . In some embodiments, the historical accuracy of each gas sensor can be pre-recorded in a database. For example, the database records the correlation between the sensor identification of the gas sensor and the historical accuracy of the gas sensor, so that the historical accuracy of the gas sensor can be obtained from the database based on the sensor identification of the gas sensor. In some embodiments, the impact of the environment on the detection accuracy of the gas sensor cannot be ignored. For example, a high temperature environment will cause the CH4 sensor to drift, thereby affecting the CH4 sensor's misdetection of real-time concentration information. The real-time credibility of the gas sensor is determined by judging whether the real-time environmental information meets the penalty conditions. For the specific description of this part, please refer to the corresponding embodiment below, which will not be repeated here.

[0019] In step S13, if the real-time credibility is less than or equal to the credibility threshold, a first target weight for the historical mean of the gas sensor is determined based on the real-time credibility. In some embodiments, the real-time credibility of the gas sensor includes the historical accuracy of the gas sensor adjusted based on the real-time environmental information. For example, the real-time credibility of the gas sensor is monitored in real time, and whether the real-time credibility is less than or equal to the credibility threshold is monitored in real time. When the real-time credibility is less than or equal to the credibility threshold, it is determined to adjust the real-time concentration information obtained by the gas sensor in combination with the historical mean of the gas sensor. Based on the real-time credibility, the weight distribution of the historical mean and the real-time concentration information of the gas sensor is determined. Specifically, the credibility interval into which the real-time credibility falls is determined, and the credibility interval is used as the target credibility interval. The first target weight of the historical mean of the concentration information obtained by the gas sensor is determined based on the target credibility interval. In some embodiments, the historical mean of the concentration information obtained by the gas sensor includes but is not limited to the average value of the concentration information obtained by the gas sensor within the most recent target time. For example, the system records the concentration information obtained by each gas sensor. When the real-time credibility of a gas sensor is less than or equal to the credibility threshold, the system obtains the average of the concentration information obtained by the gas sensor within the most recent target time (for example, within 1 minute, 2 minutes, etc.) based on the records and uses this average as the historical mean. The first target weight corresponding to the historical mean is determined based on the target credibility interval. The second target weight corresponding to the real-time concentration information is 1 minus the first target weight.

[0020] In step S14, the real-time concentration information is adjusted according to the real-time concentration information, the historical mean, and the first target weight to obtain the adjusted real-time concentration information. For example, the adjusted real-time concentration information , where A includes the adjusted real-time concentration information, Including the second target weight, B includes real-time concentration information, The first target weight is included, and C includes real-time concentration information. In this embodiment, the historical accuracy of the gas sensor is adjusted based on real-time environmental information to dynamically determine the real-time reliability of the gas sensor. When the real-time reliability is less than or equal to the reliability threshold, it is determined that the real-time concentration information acquired by the gas sensor needs to be adjusted based on the historical average value of the gas sensor. A weight is then assigned based on the real-time reliability. Finally, the real-time concentration information is adjusted based on the assigned weight to reduce the impact of the environment on the accuracy of the gas sensor.

[0021] In some embodiments, determining the real-time credibility of a gas sensor based on the gas sensor's historical accuracy and real-time environmental information includes: querying a database for a target environmental sensor and a target penalty condition corresponding to the gas sensor based on the gas sensor's sensor identifier, wherein the database includes multiple mapping relationships, each mapping relationship being used to associate a gas sensor with the environmental sensor corresponding to the gas sensor and a penalty condition; if the real-time environmental information acquired by the target environmental sensor meets the target penalty condition, adjusting the gas sensor's historical accuracy based on a first target penalty coefficient corresponding to the target penalty condition to determine the real-time credibility of the gas sensor. For example, different gases are affected by the environment to varying degrees. For example, a CH4 sensor is more affected by temperature, and high temperatures can cause the CH4 sensor's detection results to drift. However, CO and CO2 sensors are less affected by temperature. Therefore, the temperature sensor is used as the target environmental sensor for the CH4 sensor. The database pre-records a mapping relationship between the CH4 sensor's sensor identifier and the temperature sensor's sensor identifier, so that the target environmental sensor can be determined based on the CH4 sensor's sensor identifier. In some embodiments, the penalty condition includes, but is not limited to, an environmental threshold or range associated with the environmental information. For example, the mapping relationship in the database is also used to associate the gas sensor's sensor identifier with the penalty condition corresponding to the gas sensor. For example, the target environmental sensor includes a temperature sensor, and the target penalty condition corresponding to the temperature sensor can be a temperature threshold or a temperature interval. For the gas sensor, if the real-time environmental information obtained by the target environmental sensor meets the target penalty condition, the historical accuracy of the gas sensor is adjusted according to the first target penalty coefficient corresponding to the target penalty condition to obtain the real-time credibility of the gas sensor. For example, the penalty condition includes an environmental threshold, and the environmental threshold corresponds to a first penalty coefficient. When the environmental threshold is reached, the real-time credibility is equal to the historical accuracy multiplied by the first penalty coefficient. For another example, the penalty condition includes one or more interval ranges, and each interval range corresponds to a first penalty coefficient. Determine the target interval range in which the real-time environmental information obtained by the target environmental sensor falls, and determine the first penalty coefficient corresponding to the target interval range as the first target penalty coefficient. The real-time credibility is equal to the historical accuracy multiplied by the first target penalty coefficient.

[0022] In some embodiments, the target penalty condition includes one or more interval ranges, each interval range corresponds to a first penalty coefficient. If the real-time environmental information obtained by the target environmental sensor meets the target penalty condition, the historical accuracy of the gas sensor is adjusted according to the first target penalty coefficient corresponding to the target penalty condition, including: determining the target interval range that the real-time environmental information meets based on the real-time environmental information obtained by the target environmental sensor, and determining the first penalty coefficient corresponding to the target interval range as the first target penalty coefficient; adjusting the historical accuracy of the gas sensor according to the first target penalty coefficient corresponding to the target interval range. For example, the target penalty condition includes one or more interval ranges, each interval range corresponds to a first penalty coefficient. Determine the target interval range within which the real-time environmental information obtained by the target environmental sensor falls, and determine the first penalty coefficient corresponding to the target interval range as the first target penalty coefficient. The real-time credibility is equal to the historical accuracy multiplied by the first target penalty coefficient.

[0023] In some embodiments, the method further includes step S15 (not shown). In step S15, current scene information is obtained; a reference gas sensor and an adjustment gas sensor are determined from multiple gas sensors based on the current scene information, wherein a database includes multiple scene information and corresponding reference gas sensors, adjustment gas sensors, and scene coefficients for each scene information. For the adjustment gas sensor, whether there is a conflict between the real-time concentration information of the adjustment gas obtained by the adjustment gas sensor and the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor is detected based on the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor, the scene coefficient of the current scene, and the error range corresponding to the adjustment gas sensor. If a conflict exists, a real-time error of the adjustment gas sensor is determined based on the real-time concentration information and the current theoretical concentration; a penalty coefficient corresponding to the adjustment gas sensor is determined based on the real-time error; and the real-time credibility of the adjustment gas sensor is adjusted based on the penalty coefficient. In some embodiments, the scene information includes, but is not limited to, combustion scenes (e.g., kitchen or industrial combustion monitoring) and biogas fermentation scenes. In some embodiments, obtaining the current scene information includes at least one of the following: obtaining the current scene information by user input. For example, the system provides an input interface for the user to directly set the current scene information through the input interface. The current scene information is obtained by inputting the real-time concentration information into the scene model. For example, real-time concentration information acquired by multiple gas sensors is input into a scenario model, and the scenario model directly outputs current scenario information. For example, the scenario model may include a model trained using a machine learning algorithm. For example, during training, the machine learning model is trained using a large amount of historical concentration information acquired by multiple sensors in different scenarios to generate the scenario model. When the real-time concentration information acquired by multiple gas sensors is input into the scenario model, the scenario model outputs the current scenario information corresponding to the real-time concentration information. In some embodiments, the baseline gas sensor comprises a gas sensor that is less affected by the environment in the current scenario. For example, in a combustion scenario, a CO2 sensor is less affected by temperature, and thus the CO2 sensor is the baseline gas sensor. In some embodiments, the adjustment gas sensor comprises a gas sensor that is more affected by the environment in the current scenario and requires adjustment. For example, in a combustion scenario, a CH4 sensor is more affected by temperature, and thus the CH4 sensor is designated as the adjustment gas sensor. In some embodiments, scenario coefficients include, but are not limited to, combustion efficiency, postpartum methanogen activity coefficient, and the like. In some embodiments, the database pre-associates and maps the baseline gas sensor, adjustment gas sensor, and scenario coefficient corresponding to each of the multiple scenario information. In order to determine the reference gas sensor, adjustment gas sensor, and scene coefficient corresponding to the current scene information based on the current scene information.Because the adjustment gas sensor is significantly affected by the environment, it is necessary to detect whether there is a conflict between the real-time concentration information of the adjustment gas obtained by the adjustment gas sensor and the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor based on the real-time concentration information of the reference gas, the scenario coefficient, and the error range of the adjustment gas sensor. In other words, because the adjustment gas sensor is significantly affected by the environment, the chemical reaction relationship between the gases can be used to determine whether there is a conflict between the adjustment gas and the reference gas. For example, in a methane combustion scenario, the complete combustion of one volume of methane (e.g., the adjustment gas) produces one volume of carbon dioxide (e.g., the reference gas). If the real-time concentration information of carbon dioxide is detected, the current theoretical concentration information of methane can be inferred based on this real-time concentration information. The determination of whether there is a conflict is then determined based on the current real-time concentration information of methane. The specific process for determining a conflict is described in the corresponding embodiments below and is not detailed here. If there is a conflict, the real-time error of the adjustment gas sensor is determined based on the real-time concentration information and the current theoretical concentration information. For example, the real-time error is equal to the absolute value of the difference between the real-time concentration information and the current theoretical concentration information. Furthermore, a second target penalty coefficient corresponding to the adjustment gas sensor is determined based on the real-time error. For example, an error interval or error threshold is set. A second target penalty coefficient is determined based on the error interval or error threshold. For example, an error threshold and a fixed second target penalty coefficient are set. When the real-time error reaches the error threshold, the fixed second target penalty coefficient is determined. For another example, an error interval and a second penalty coefficient corresponding to each error interval are set. The target error interval within which the real-time error falls is determined, and the second penalty coefficient corresponding to the target error interval is determined as the second target penalty coefficient. Furthermore, the real-time credibility of the gas sensor is adjusted based on the second target penalty coefficient. For example, the adjusted real-time credibility is equal to the second target penalty coefficient multiplied by the real-time credibility before adjustment.

[0024] In some embodiments, for an adjustment gas sensor, based on the real-time concentration information of the reference gas obtained by the adjustment gas sensor, the scene coefficient of the current scene, and the error range corresponding to the adjustment gas sensor, whether there is a conflict between the real-time concentration information of the adjustment gas obtained by the adjustment gas sensor and the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor. This includes: determining the current theoretical concentration information of the adjustment gas sensor based on the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor and the scene coefficient of the current scene information; determining the current theoretical concentration range based on the current theoretical concentration information and the error range corresponding to the adjustment gas sensor; and determining a conflict between the real-time concentration information of the adjustment gas obtained by the adjustment gas sensor and the real-time concentration information of the reference gas obtained by the reference gas sensor if the real-time concentration information does not fall within the current theoretical concentration range. For example, the current theoretical concentration information of methane = the real-time concentration information of carbon dioxide / combustion efficiency. Here, the reference gas sensor includes a carbon dioxide sensor, the adjustment gas sensor includes a methane sensor, and the scene coefficient includes combustion efficiency. In some embodiments, combustion efficiency comprises the ratio of actual combustion products to theoretical complete combustion products, typically a coefficient (e.g., 0.9). In some embodiments, the error range is typically preset, such as 20%. For example, the current theoretical concentration information is 222ppm, the error range is 20%, and the current theoretical concentration range is 177~266ppm. If the real-time concentration information obtained by the methane sensor is within the current theoretical concentration range, it is determined that there is no conflict. If it is not within the current theoretical concentration range, it is determined that there is a conflict between the real-time concentration information of methane obtained by the methane sensor and the real-time concentration information of carbon dioxide obtained by the carbon dioxide sensor. When there is a conflict, it is necessary to further reduce the real-time credibility of the adjusted gas sensor. Of course, those skilled in the art will understand that the specific embodiments of conflict judgment described above are only examples. For example, in a biogas fermentation scenario, the scenario coefficient includes bacterial activity, the reference sensor includes a carbon dioxide sensor, and the adjustment sensor includes a methane sensor.

[0025] In some embodiments, determining a first target weight for the historical mean of the gas sensor based on the real-time credibility includes: determining, based on the real-time credibility, from a database a target credibility interval within which the real-time credibility falls, wherein the database includes multiple credibility intervals and a first weight with respect to the historical mean corresponding to each credibility interval; and determining the first weight corresponding to the target credibility interval as the first target weight with respect to the historical mean corresponding to the real-time credibility. For example, the database includes multiple credibility intervals (e.g., [0.5, 0.7], [0.8, 0.9], etc.), each corresponding to a first weight with respect to the historical mean. Based on the real-time credibility, determining the target credibility interval within which the real-time credibility falls (e.g., a real-time credibility of 0.6 falls within the credibility interval [0.5, 0.7]), and determining the first weight corresponding to the target credibility interval as the first target weight with respect to the historical mean.

[0026] Figure 2 A structural schematic diagram of a multi-sensor based gas detection device according to an embodiment of the present application is shown, the device includes multiple gas sensors, one or more environmental sensors, and the device also includes: an acquisition module, the acquisition module is used to obtain real-time concentration information of multiple gases through gas sensors; obtain real-time environmental information through environmental sensors; a credibility determination module, the credibility determination module is used to determine the real-time credibility of the gas sensor according to the historical accuracy and real-time environmental information of the gas sensor for the real-time concentration information collected by each gas sensor; a weight allocation module, the weight allocation module is used to determine a first target weight for the historical mean of the gas sensor according to the real-time credibility if the real-time credibility is less than or equal to the credibility threshold; a concentration adjustment module, the concentration adjustment module is used to adjust the real-time concentration information according to the real-time concentration information, the historical mean, and the first target weight to obtain adjusted real-time concentration information.

[0027] Here, the specific implementations corresponding to the acquisition module, credibility determination module, weight allocation module, and concentration adjustment module are respectively the same or similar to the specific embodiments of the above-mentioned steps S11, S12, S13, and S14, and are therefore not repeated here and are included here by reference.

[0028] In addition to the methods and devices described in the above embodiments, the present application also provides a computer-readable storage medium, which stores computer code. When the computer code is executed, the method described in any of the above items is executed.

[0029] The present application also provides a computer program product. When the computer program product is executed by a computer device, the method described in any one of the preceding items is executed.

[0030] The present application also provides a computer device, comprising: one or more processors; a memory for storing one or more computer programs; When the one or more computer programs are executed by the one or more processors, the one or more processors are caused to implement the method as described in any one of the preceding items.

[0031] Figure 3 shows an exemplary system that can be used to implement the various embodiments described in this application; like Figure 3 In some embodiments, the system 300 can function as any of the devices described in the various embodiments. In some embodiments, the system 300 can include one or more computer-readable media (e.g., system memory or NVM / storage device 320) having instructions and one or more processors (e.g., processor(s) 305) coupled to the one or more computer-readable media and configured to execute the instructions to implement the modules and thereby perform the actions described herein.

[0032] For one embodiment, system control module 310 may include any suitable interface controller to provide any suitable interface to at least one of processor(s) 305 and / or any suitable device or component in communication with system control module 310 .

[0033] The system control module 310 may include a memory controller module 330 to provide an interface to the system memory 315. The memory controller module 330 may be a hardware module, a software module, and / or a firmware module.

[0034] System memory 315 can be used, for example, to load and store data and / or instructions for system 300. For one embodiment, system memory 315 can include any suitable volatile memory, such as a suitable DRAM. In some embodiments, system memory 315 can include double data rate type four synchronous dynamic random access memory (DDR4 SDRAM).

[0035] For one embodiment, system control module 310 may include one or more input / output (I / O) controllers to provide interfaces to NVM / storage device 320 and communication interface(s) 325 .

[0036] For example, NVM / storage 320 may be used to store data and / or instructions. NVM / storage 320 may include any suitable non-volatile memory (e.g., flash memory) and / or may include any suitable non-volatile storage device(s) (e.g., one or more hard disk drives (HDDs), one or more compact disk (CD) drives, and / or one or more digital versatile disk (DVD) drives).

[0037] NVM / storage device 320 may include storage resources that are physically part of the device on which system 300 is installed, or it may be accessible to the device without being part of the device. For example, NVM / storage device 320 may be accessed over a network via communication interface(s) 325.

[0038] Communication interface(s) 325 may provide an interface for system 300 to communicate over one or more networks and / or with any other suitable devices. System 300 may wirelessly communicate with one or more components of a wireless network in accordance with any of one or more wireless network standards and / or protocols.

[0039] For one embodiment, at least one of the processor(s) 305 may be packaged together with the logic of one or more controllers of the system control module 310 (e.g., the memory controller module 330). For one embodiment, at least one of the processor(s) 305 may be packaged together with the logic of one or more controllers of the system control module 310 to form a system-in-package (SiP). For one embodiment, at least one of the processor(s) 305 may be integrated on the same die with the logic of one or more controllers of the system control module 310. For one embodiment, at least one of the processor(s) 305 may be integrated on the same die with the logic of one or more controllers of the system control module 310 to form a system-on-chip (SoC).

[0040] In various embodiments, system 300 may be, but is not limited to, a server, a workstation, a desktop computing device, or a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet computer, a netbook, etc.). In various embodiments, system 300 may have more or fewer components and / or a different architecture. For example, in some embodiments, system 300 includes one or more cameras, a keyboard, a liquid crystal display (LCD) screen (including a touchscreen display), a non-volatile memory port, multiple antennas, a graphics chip, an application-specific integrated circuit (ASIC), and a speaker.

[0041] It should be noted that the present application can be implemented in software and / or a combination of software and hardware, for example, using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In one embodiment, the software program of the present application can be executed by a processor to implement the steps or functions described above. Similarly, the software program of the present application (including related data structures) can be stored in a computer-readable recording medium, such as a RAM memory, a magnetic or optical drive, a floppy disk, and the like. In addition, some steps or functions of the present application can be implemented in hardware, for example, as a circuit that cooperates with a processor to perform the various steps or functions.

[0042] In addition, a part of the present application may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present application through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes but is not limited to a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0043] Communication media include media by which communication signals containing, for example, computer-readable instructions, data structures, program modules, or other data are transmitted from one system to another. Communication media may include guided transmission media such as cables and wires (e.g., fiber optic, coaxial, etc.) and wireless (unguided transmission) media capable of propagating energy waves, such as acoustic, electromagnetic, RF, microwave, and infrared. Computer-readable instructions, data structures, program modules, or other data may be embodied as, for example, a modulated data signal in a wireless medium such as a carrier wave or similar mechanism such as that embodied as part of spread spectrum technology. The term "modulated data signal" refers to a signal that has one or more of its characteristics changed or set in such a manner as to encode information in the signal. Modulation may be analog, digital, or a hybrid modulation technique.

[0044] By way of example and not limitation, computer-readable storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. For example, computer-readable storage media include, but are not limited to, volatile memory such as random access memory (RAM, DRAM, SRAM); and non-volatile memory such as flash memory, various read-only memories (ROM, PROM, EPROM, EEPROM), magnetic and ferromagnetic / ferroelectric memories (MRAM, FeRAM); and magnetic and optical storage devices (hard disks, magnetic tapes, CDs, DVDs); or other media now known or later developed that can store computer-readable information / data for use by a computer system.

[0045] Here, according to one embodiment of the present application, a device is included, which includes a memory for storing computer program instructions and a processor for executing the program instructions, wherein, when the computer program instructions are executed by the processor, the device is triggered to run the methods and / or technical solutions based on the aforementioned multiple embodiments of the present application.

[0046] It is obvious to those skilled in the art that the present application is not limited to the details of the above-mentioned exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the spirit or basic characteristics of the present application. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the device claim can also be implemented by one unit or device through software or hardware. Words such as first and second are used to indicate names and do not indicate any particular order.

Claims

1. A gas detection method based on multiple sensors, characterized in that: The multi-sensor comprises a plurality of gas sensors and one or more environmental sensors, and the method comprises: Acquiring real-time concentration information of multiple gases through the gas sensor; acquiring real-time environmental information through the environmental sensor; For the real-time concentration information collected by each gas sensor, determine the real-time credibility of the gas sensor based on the historical accuracy of the gas sensor and the real-time environmental information; If the real-time credibility is less than or equal to the credibility threshold, determining a first target weight for a historical average value of the gas sensor according to the real-time credibility; The real-time concentration information is adjusted according to the real-time concentration information, the historical mean, and the first target weight to obtain adjusted real-time concentration information.

2. The method according to claim 1, characterized in that The determining the real-time credibility of the gas sensor according to the historical accuracy of the gas sensor and the real-time environmental information includes: querying a database for a target environmental sensor and a target penalty condition corresponding to the gas sensor according to the sensor identifier of the gas sensor, wherein the database includes a plurality of mapping relationships, each mapping relationship being used to associate a gas sensor with an environmental sensor corresponding to the gas sensor and a penalty condition; If the real-time environmental information acquired by the target environmental sensor meets the target penalty condition, the historical accuracy of the gas sensor is adjusted according to a first target penalty coefficient corresponding to the target penalty condition to obtain the real-time credibility of the gas sensor.

3. The method according to claim 2, characterized in that The target penalty condition includes one or more interval ranges, each interval range corresponds to a first penalty coefficient, and if the real-time environmental information acquired by the target environmental sensor meets the target penalty condition, adjusting the historical accuracy of the gas sensor according to the first target penalty coefficient corresponding to the target penalty condition includes: Determining a target interval range satisfied by the real-time environmental information acquired by the target environmental sensor, and determining a first penalty coefficient corresponding to the target interval range as a first target penalty coefficient; The historical accuracy of the gas sensor is adjusted according to a first target penalty coefficient corresponding to the target interval.

4. The method according to claim 1, wherein The method further comprises: Get current scene information; Determining a reference gas sensor and an adjustment gas sensor from the plurality of gas sensors according to the current scene information, wherein a database includes a plurality of scene information and a reference gas sensor, an adjustment gas sensor, and a scene coefficient corresponding to each scene information; For the adjustment gas sensor, detecting whether there is a conflict between the real-time concentration information of the adjustment gas obtained by the adjustment gas sensor and the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor based on the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor, the scene coefficient of the current scene information, and the error range corresponding to the adjustment gas sensor; If there is a conflict, determining a real-time error of the adjustment gas sensor according to the real-time concentration information and the current theoretical concentration information; Determining a second target penalty coefficient corresponding to the adjusted gas sensor according to the real-time error; The real-time credibility of the gas sensor is adjusted according to the second target penalty coefficient.

5. The method according to claim 4, characterized in that The step of detecting, for the adjustment gas sensor, whether there is a conflict between the real-time concentration information of the adjustment gas obtained by the adjustment gas sensor and the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor based on the real-time concentration information of the reference gas obtained by the corresponding reference gas sensor, the scene coefficient of the current scene information, and the error range corresponding to the adjustment gas sensor, includes: Determine the current theoretical concentration information of the adjustment gas sensor according to the real-time concentration information of the reference gas acquired by the corresponding reference gas sensor and the scene coefficient of the current scene information; Determine the current theoretical concentration range according to the current theoretical concentration information and the error range corresponding to the adjustment gas sensor; If the real-time concentration information does not fall within the current theoretical concentration range, it is determined that there is a conflict between the real-time concentration information of the adjustment gas acquired by the adjustment gas sensor and the real-time concentration information of the reference gas acquired by the reference gas sensor.

6. The method according to claim 4, characterized in that Acquiring current scene information includes at least one of the following: Acquiring the current scene information by inputting the current scene information by the user; The current scene information is obtained by inputting the real-time concentration information into a scene model.

7. The method according to claim 1, characterized in that The determining, according to the real-time credibility, a first target weight of a historical average value of the gas sensor includes: Determining a target credibility interval within which the real-time credibility falls from a database according to the real-time credibility, wherein the database includes a plurality of credibility intervals and a first weight corresponding to each credibility interval with respect to a historical mean; The first weight corresponding to the target credibility interval is determined as the first target weight corresponding to the real-time credibility with respect to the historical mean.

8. A gas detection device based on multiple sensors, characterized in that: The device includes a plurality of gas sensors, one or more environmental sensors, and further includes: An acquisition module, configured to acquire real-time concentration information of multiple gases through the gas sensor; and acquire real-time environmental information through the environmental sensor; a credibility determination module, configured to determine the real-time credibility of each gas sensor based on the real-time concentration information collected by the gas sensor and the real-time environmental information; a weight allocation module, configured to determine a first target weight for a historical mean value of the gas sensor according to the real-time credibility if the real-time credibility is less than or equal to a credibility threshold; A concentration adjustment module is used to adjust the real-time concentration information according to the real-time concentration information, the historical mean, and the first target weight to obtain adjusted real-time concentration information.

9. A computer device for gas detection, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes any one of the methods according to claims 1 to 7.

10. A computer-readable storage medium, characterized in that A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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