An indoor environment quality data collection and monitoring internet of things system

Abstract

The present application relates to the internet of things and environmental monitoring technical field, specifically to a kind of indoor environmental quality data acquisition and monitoring internet of things system. Including: configuration terminal, state acquisition module, flow monitoring module, checking analysis module, compensation control module, outdoor background data acquisition node, and multiple indoor gas sensors, differential pressure sensors, temperature and humidity sensors and personnel counting equipment;Configuration terminal is used for presetting initial parameter;State acquisition module dynamically adjusts sampling period;Flow monitoring module obtains the flow parameter and gas emission parameter of air inlet and air outlet;Checking analysis module obtains flow deviation evaluation result containing moving average value;Compensation control module locates abnormal sensor and compensates concentration;Auxiliary verification module executes linkage control and local concentration zero point reference value correction when meeting conditions.The present application reduces the data processing and transmission data volume of system.

Description

Technical Field

[0001] This invention relates to the fields of Internet of Things (IoT) and environmental monitoring technology, specifically to an IoT system for indoor environmental quality data acquisition and monitoring. Background Technology

[0002] In indoor environmental quality monitoring, it is usually necessary to simultaneously collect data on the concentration of the gas to be measured, ventilation status, and human activities to determine the true concentration changes in the indoor environment and the zero-point reference drift of the sensor itself. Rooms are interconnected through ventilation ducts. Without configuring parameters such as room volume, duct structure, and connectivity, the monitoring system cannot distinguish between the actual environmental changes and sensor measurement deviations. Existing systems rely on single-point concentration data for alarms or control, or perform calculations based on data within a fixed sampling period. Under the combined effects of changes in room ventilation, fluctuations in human activities, and interference from outdoor background concentrations, there are errors in environmental status judgment, leading to false alarms, missed alarms, and deviations in linkage control. Summary of the Invention

[0003] To address the technical problems of existing indoor environmental monitoring systems, which are susceptible to errors in determining actual environmental changes and sensor offsets due to ventilation, human interference, and outdoor disturbances, this invention provides an Internet of Things (IoT) system for indoor environmental quality data acquisition and monitoring. The technical solution is as follows:

[0004] An Internet of Things (IoT) system for indoor environmental quality data acquisition and monitoring is applied to a target building with ventilation ducts and multiple rooms, wherein the ventilation ducts include air inlets and air outlets; the system includes: a configuration terminal, a status acquisition module, a flow monitoring module, a verification and analysis module, a compensation control module, as well as an outdoor background data acquisition node, an indoor gas sensor, a differential pressure sensor, a temperature and humidity sensor, and a personnel counting device;

[0005] The configuration terminal is used to preset initial parameters, which include the connection relationship between the plurality of rooms and the air inlet and air outlet of the ventilation duct;

[0006] The status acquisition module is used to acquire the original concentration measurement value of the gas to be tested in the target building through the indoor gas sensor, acquire the measured value of the dynamic and static pressure difference of the ventilation duct through the differential pressure sensor, acquire outdoor background concentration data through the outdoor background data acquisition node, acquire temperature and humidity data through the temperature and humidity sensor, and acquire the number of people through the personnel counting device.

[0007] The flow monitoring module is used to obtain the flow parameters of the air inlet and the air outlet based on the measured value of the dynamic and static pressure difference, and to obtain the gas emission parameters based on the number of people.

[0008] The verification analysis module is used to determine the gas mass flow rate deviation assessment result based on the initial parameters, the original concentration measurement value, the flow rate parameter, and the gas emission parameter;

[0009] The compensation control module is used to locate the indoor gas sensor that has experienced measurement drift based on the gas mass flow rate deviation assessment result and the connection relationship, determine the concentration correction value based on the gas mass flow rate deviation assessment result, and output the compensated concentration data.

[0010] Preferably, the initial parameters further include: the effective volume of the plurality of rooms in the target building, the cross-sectional area of ​​the ventilation duct, the zero-point reference value of the indoor gas sensor, and the zero-point drift value of the differential pressure sensor.

[0011] Preferably, the status acquisition module is further configured to output a sampling period adjustment command based on the original concentration measurement value, including: calculating the concentration change rate at adjacent sampling times based on the original concentration measurement value; if the concentration change rate is greater than a preset concentration change rate threshold, switching the current sampling period of the corresponding indoor gas sensor to a preset high-frequency sampling period; if the concentration change rate is less than or equal to the preset concentration change rate threshold, controlling the indoor gas sensor to operate with a preset basic sampling period.

[0012] Preferably, the flow monitoring module obtains the flow parameters of the air inlet and the air outlet of the ventilation duct based on the measured value of the dynamic and static pressure difference, and obtains the gas emission parameters based on the number of people, including:

[0013] The real-time volumetric flow rate of the air inlet and the air outlet is determined based on the measured dynamic and static pressure difference, the temperature and humidity data, and the cross-sectional area of ​​the ventilation duct as the flow rate parameter; the gas emission parameter is calculated based on the number of people and the preset gas emission coefficient per person.

[0014] Preferably, the verification analysis module determines the gas mass flow rate deviation assessment result, including:

[0015] Based on the original concentration measurement, the flow rate parameter, and the gas emission parameter, a gas mass balance model is constructed in conjunction with the effective volume to calculate the gas mass flow rate deviation at the current moment; and a sliding average value is calculated based on the continuous gas mass flow rate deviation within a preset time period, and the sliding average value is used as the gas mass flow rate deviation evaluation result.

[0016] Preferably, the system further includes an auxiliary verification module and a fresh air actuator; the auxiliary verification module is communicatively connected to the fresh air actuator; the auxiliary verification module is used to perform linkage control on the fresh air actuator based on the comparison result of the sliding average value and the preset deviation threshold, and to reset the zero-point reference value of the indoor gas sensor using the outdoor background concentration data when the preset verification conditions are met.

[0017] Preferably, the initial parameters further include the current sampling time interval; the compensation control module locates the indoor gas sensor experiencing measurement drift based on the connection relationship and performs concentration compensation, including:

[0018] Based on the connection relationship between the multiple rooms and the ventilation duct and the sliding average value, locate the indoor gas sensor that has experienced measurement drift;

[0019] The concentration correction value is determined based on the sliding average value, the current sampling time interval, the effective volume of the multiple rooms in the target building, and the preset compensation gain coefficient.

[0020] Concentration compensation is performed based on the preset compensation gain coefficient and the concentration correction value, and the compensated concentration data is output.

[0021] Preferably, the auxiliary verification module performs linkage control when the comparison result between the sliding average value and the preset deviation threshold meets a preset linkage control condition, and resets the zero-point reference value of the indoor gas sensor using the outdoor background concentration data when the preset verification condition is met, including:

[0022] When the original concentration measurement value is greater than the preset concentration threshold and the absolute value of the sliding average value is less than or equal to the preset deviation threshold, a linkage execution command is sent to the fresh air actuator.

[0023] When the original concentration measurement value is greater than the preset concentration threshold and the absolute value of the sliding average value is greater than the preset deviation threshold, the linkage execution command output to the fresh air actuator is blocked, and the indoor gas sensor that outputs the original concentration measurement value is controlled to adjust the sampling cycle.

[0024] When the number of people is zero for more than a preset time threshold and the gas emission parameter is less than a preset emission amount threshold, if the absolute difference between the original concentration measurement value and the outdoor background concentration data is greater than a preset bias threshold, the zero-point reference value correction of the corresponding indoor gas sensor is triggered; otherwise, the current zero-point reference value of the indoor gas sensor is maintained.

[0025] In response to the shutdown signal of the fresh air actuator, the output value of the differential pressure sensor is read as the zero-point drift value of the differential pressure sensor, and the zero-point drift value of the differential pressure sensor is deducted in the subsequent calculation of the measured dynamic and static pressure difference.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. This invention dynamically adjusts the sensor's sampling period by comparing the changes in the original concentration measurement of the gas under test with a preset concentration change rate threshold through a status acquisition module; it dynamically shortens the sampling period when the environmental concentration changes abruptly, which can promptly capture abnormal changes in indoor gas quality and improve the system's real-time response capability; at the same time, it restores the original period when the concentration is stable, reducing the amount of data processing and transmission in the system.

[0028] 2. This system utilizes a verification and analysis module to combine indoor gas concentration, airflow parameters, and gas emission parameters obtained based on personnel counts to output gas mass flow deviation assessment results; based on the connection relationship between the room and ventilation ducts, it locates indoor gas sensors that have experienced measurement drift and performs concentration compensation, thereby correcting system measurement errors and improving the reliability of long-term monitoring data.

[0029] 3. This invention uses an auxiliary verification module to determine the deviation between the concentration exceeding a preset concentration threshold and the moving average value. It only sends a linkage command to the fresh air actuator when the sensor measurement is accurate, thus avoiding equipment malfunctions caused by sensor failures. At the same time, when the number of people is continuously zero, the system can automatically reset the zero-point reference value of the indoor gas sensor using outdoor background concentration data and deduct the zero-point drift of the differential pressure sensor using the shutdown condition, thereby improving the stability and control accuracy of the system operation. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in this invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort:

[0031] Figure 1 This is a structural diagram of an Internet of Things (IoT) system for indoor environmental quality data acquisition and monitoring according to the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0033] Please see Figure 1 An Internet of Things (IoT) system for indoor environmental quality data acquisition and monitoring is applied to a target building with ventilation ducts and multiple rooms. The ventilation ducts include air inlets and exhaust outlets. The system includes: a configuration terminal, a status acquisition module, a flow monitoring module, a verification and analysis module, a compensation control module, as well as an outdoor background data acquisition node, an indoor gas sensor, a differential pressure sensor, a temperature and humidity sensor, and a personnel counting device.

[0034] The configuration terminal is used to preset initial parameters, which include the connection relationships between multiple rooms and the air inlets and outlets of the ventilation ducts.

[0035] The status acquisition module is used to acquire the original concentration measurement value of the gas to be tested in the target building through the indoor gas sensor, acquire the measured value of the dynamic and static pressure difference of the ventilation duct through the differential pressure sensor, acquire the outdoor background concentration data through the outdoor background data acquisition node, acquire the temperature and humidity data through the temperature and humidity sensor, and acquire the number of people through the personnel counting device.

[0036] The flow monitoring module is used to obtain the flow parameters of the air inlet and outlet based on the measured value of the dynamic and static pressure difference, and to obtain the gas emission parameters based on the number of people.

[0037] The verification analysis module is used to determine the gas mass flow rate deviation assessment results based on the initial parameters, original concentration measurements, flow parameters, and gas emission parameters.

[0038] The compensation control module is used to locate the indoor gas sensor that has experienced measurement drift based on the gas mass flow rate deviation assessment results and connection relationships, determine the concentration correction value based on the gas mass flow rate deviation assessment results, and output the compensated concentration data.

[0039] Obtain initial parameters, preset parameters for rooms within the monitoring range based on the existing connection relationships between multiple rooms and ventilation ducts in the building, and determine the prior conditions required for subsequent calculations;

[0040] The initial parameters refer to the basic physical parameters that are entered and kept in the configuration terminal before the system runs, including at least the effective volume of the room, the cross-sectional area of ​​the ventilation duct, and the connection relationship between the room and the air inlet and outlet.

[0041] Effective volume refers to the indoor gas volume involved in the gas exchange calculation. Its value is the remaining space ventilation volume after deducting the volume occupied by the inherent physical components of the room from the total room volume. The values ​​of the total room volume and the volume occupied by the inherent physical components of the room are pre-entered manually through the configuration terminal.

[0042] The preset deviation threshold, preset concentration threshold, preset concentration change rate threshold, preset time threshold, preset emission threshold, and preset bias threshold are all pre-calibrated by the configuration terminal based on the historical environmental monitoring dataset of the target building and combined with conventional indoor gas quality standards in this field, and stored in the system.

[0043] The preset time threshold is set based on the longest vacancy time during normal personnel turnover in the target building; the preset emission threshold is set based on the limit fluctuation range of the background emission rate of the inherent materials in the indoor environment when no personnel are present; and the preset bias threshold is based on the sensor calibration accuracy preset by the system. The preset deviation threshold is determined by comprehensively considering the variance of outdoor background concentration fluctuations. The specific formula is as follows:

[0044]

[0045] In the formula, For effective volume, This is the current sampling time interval. Real-time volumetric flow rate; All are preset weight coefficients, and the preset weight coefficients include physical conversion factors for dimension normalization, so that the dimensions of each term on the right side of the equation are consistent with the preset deviation threshold. The specific values ​​are obtained by extracting the historical environmental monitoring dataset of the target building under normal conditions for more than one natural month, and then using the sensor calibration accuracy, effective volume, current sampling time interval and real-time volume flow rate in the dataset as a multivariate independent variable matrix after standardization to eliminate dimension differences. The actual observation deviation value under the calibration environment is used as the dependent variable, and the least squares method is used to perform multivariate linear regression fitting.

[0046] The cross-sectional area of ​​a ventilation duct refers to the effective cross-sectional area through which airflow passes, including the inner cross-sectional area of ​​a circular or rectangular duct; the connection relationship refers to the airflow connectivity between different rooms and their corresponding ventilation branches, including the independent connection of a single room to an intake and exhaust branch, and the connectivity of adjacent rooms sharing an upstream supply air branch; the verification and analysis module performs collaborative calculations based on the configured unified system initial parameters, combined with ventilation coupling information of airflow source and destination, to generate a basis for determining concentration changes;

[0047] Based on the initial system parameters, perform correlation calculations between monitoring nodes and output the data verification results between nodes.

[0048] The data acquired by the status acquisition module and the flow monitoring module are monitoring parameters, which include: the original concentration measurement value of the gas to be tested, the measured value of the dynamic and static pressure difference, temperature and humidity data, the number of people, and the outdoor background concentration data.

[0049] The system acquires monitoring parameters and synchronously collects indoor environmental data based on the outputs of various sensors, generating a basic data set for subsequent judgment. Monitoring parameters refer to the raw observations acquired by the status acquisition module and flow monitoring module within the same system cycle, including at least the raw concentration measurement of the gas to be measured, the measured dynamic-static pressure difference, temperature and humidity data, the number of people, and outdoor background concentration data. The raw concentration measurement of the gas to be measured refers to the uncompensated concentration output of the indoor gas sensor for the gas to be monitored, specifically including but not limited to carbon dioxide concentration, formaldehyde concentration, or volatile organic compound concentration. The measured dynamic-static pressure difference refers to the pressure difference measured by the differential pressure sensor at the air inlet or outlet.

[0050] Temperature and humidity data are used to reflect indoor gas conditions and participate in gas density correction; the number of people is used to characterize the impact of indoor human activities on gas emissions, and is collected by personnel counting devices deployed at room entrances and exits; outdoor background data acquisition nodes are deployed at the outdoor fresh air intake of the target building or the building's outer perimeter area unaffected by indoor exhaust, and the acquired outdoor background concentration data is used to characterize the outside air concentration level before entering the system, serving as the intake air concentration or nighttime calibration reference value; the system extracts the concentration change of ambient gas and the sensor offset based on the data link of indoor concentration, flow state, human activities, and outdoor boundary conditions, and outputs the environmental state judgment result.

[0051] The status acquisition module is also used to output sampling period adjustment instructions based on the original concentration measurement value, including: calculating the concentration change rate between adjacent sampling times based on the original concentration measurement value; if the concentration change rate is greater than the preset concentration change rate threshold, switching the current sampling period of the corresponding indoor gas sensor to the preset high-frequency sampling period; if the concentration change rate is less than or equal to the preset concentration change rate threshold, controlling the indoor gas sensor to operate at the preset basic sampling period.

[0052] The system acquires the raw concentration measurements of the gas to be measured at adjacent sampling times. Based on the concentration change rate, it adjusts the sampling period of the relevant indoor gas sensors to determine the operating status of basic sampling or high-frequency sampling, and the concentration change rate. The calculation formula is:

[0053]

[0054] in, This represents the original concentration measurement of the gas to be measured at the current moment; This represents the original concentration measurement of the gas to be tested at the previous sampling time; The current sampling time interval, with units of . ;

[0055] When the concentration change rate exceeds the preset concentration change rate threshold, a control command is generated and sent to shorten the sampling period of the indoor gas sensor whose original concentration measurement value of the gas to be measured exceeds the threshold and causes measurement drift, as well as other sensors directly connected to it through the same ventilation branch, from the basic sampling period to the high-frequency sampling period, and then restore the basic sampling period after the concentration change rate falls back to the preset hysteresis range; if the concentration change rate is less than or equal to the preset concentration change rate threshold, the basic sampling period is maintained.

[0056] The status acquisition module responds to the sampling period control command generated internally by the system and performs dynamic switching between the basic sampling period and the high-frequency sampling period;

[0057] In practical implementation, the system is deployed in an indoor environment with multiple rooms and centralized ventilation ducts. The configuration terminal first records the effective volume of multiple rooms, the cross-sectional area of ​​each ventilation duct, and the connection relationship between the rooms and the ventilation branches. The status acquisition module collects the original concentration measurement value of the gas to be measured, temperature and humidity data, and the number of people in each system cycle, and receives the outdoor background concentration data provided by the outdoor background data acquisition node. When the concentration change rate of a single room is greater than the preset concentration change rate threshold, the system controls the room and other rooms connected to it through the same ventilation branch to perform a high-frequency sampling cycle, and outputs the sampling data to the flow monitoring module and the verification analysis module.

[0058] The flow monitoring module acquires the flow parameters of the air inlet and outlet of the ventilation duct based on the measured dynamic and static pressure difference, and acquires gas emission parameters based on the number of people, including:

[0059] The real-time volumetric flow rate of the air inlet and outlet is determined based on the measured dynamic and static pressure difference, temperature and humidity data, and cross-sectional area of ​​the ventilation duct as the flow rate parameter; the gas emission parameter is calculated based on the number of people and the preset gas emission coefficient per person.

[0060] The system acquires measured values ​​of dynamic and static pressure difference and temperature and humidity data. Based on the air conditions inside the duct, it calculates the flow parameters of the air inlet and outlet, and determines the gas emission parameters by combining this with the number of personnel. The measured value of dynamic and static pressure difference refers to the pressure difference measured by the differential pressure sensor inside the ventilation duct, reflecting the pressure change formed when the airflow passes through the duct. The gas density is the mass per unit volume of air, used to calculate the actual flow velocity based on the measured value of dynamic and static pressure difference.

[0061] Real-time volumetric flow rate refers to the volume of air passing through the air inlet or outlet per unit time; gas emission parameters are the amount of gas released based on human activity.

[0062] The process of obtaining flow parameters includes: the flow monitoring module obtains the flow parameters of the air inlet and outlet of the ventilation duct based on the measured value of the dynamic and static pressure difference, and obtains the gas emission parameters based on the number of people. The calculation process is expressed by the following formula:

[0063]

[0064]

[0065]

[0066] in, The gas velocity at the cross-section of the pipe has dimensions of . ; The comprehensive flow correction coefficient is dimensionless and can be obtained through pre-calibration in an on-site wind tunnel experiment, or set based on the Reynolds number and the absolute roughness of the pipe by referring to standard fluid dynamics empirical values ​​such as the Moody diagram. The measured value of the dynamic-static pressure difference output by the differential pressure sensor, with dimensions of... ; The gas density is calculated based on temperature and humidity data combined with the ideal gas law, and its dimensions are: ; The real-time volumetric flow rate at the air inlet or outlet, with dimensions of ; The cross-sectional area of ​​the ventilation duct is given by the dimension . ; Here are the gas emission parameters, with dimensions of ; The number of people is based on personnel counting equipment and is dimensionless. The standard gas emission coefficient per unit of personnel, in units of mg / (s·person), is obtained by referring to tables based on the actual use function of the target building and the current building environmental design standards.

[0067] The system synchronously calculates and generates input data based on the measured values ​​of dynamic and static pressure difference, temperature and humidity data, and the number of people, and determines the flow parameters and gas emission parameters.

[0068] The verification analysis module determines the gas mass flow rate deviation assessment results, including:

[0069] The verification and analysis module, based on the gas mass balance model, determines the gas mass flow rate deviation at the current moment, extracts the characteristics of the gas mass flow rate deviation over time, and calculates the moving average value, which is the gas mass flow rate deviation assessment result. The gas mass flow rate deviation integrates the gas accumulation term, air intake, exhaust output, and personnel gas emissions. Its environmental gas mass balance equation is as follows:

[0070]

[0071] in, The gas mass flow rate deviation at the current moment, with dimensions of ; The effective volume for participating in concentration accumulation calculations, with dimensions of ; The original concentration measurement of the gas to be measured at the current moment, with dimensions of . ; This is the original concentration measurement of the gas to be measured at the previous sampling time, with dimensions of... ; The current sampling time interval, with units of . ; This is the number of the air inlet connected to the current room; For the first The real-time volumetric flow rate of each air inlet, with dimensions of ; For the first The inflow concentration corresponding to each air inlet, with dimensions of The outdoor background concentration data is mapped and assigned by the outdoor background data acquisition node, or it is collected in real time by an independent sensor set at the front end of the air inlet. Number the exhaust vent connected to the current room; For the first The real-time volumetric flow rate of each exhaust vent, in units of... ; The parameters for gas emission currently released inside the room, with dimensions of ;

[0072] The moving average used to determine the current node offset state The calculation formula is:

[0073]

[0074] in, This represents the total number of sampling windows within a preset time period.

[0075] The verification and analysis module extracts data features that characterize continuous measurement anomalies by using a moving average based on the correlation between changes in room concentration, the influence of upstream flow, the effect of exhaust ventilation, and the effect of personnel emission. The system calculates the gas mass flow deviation and moving average based on flow parameters, original concentration measurements, gas emission parameters, and effective room volume, and outputs the judgment results of indoor gas sensors that have experienced measurement drift.

[0076] When flow parameters, outdoor background concentration and personnel emission parameters are introduced simultaneously within the same system cycle, if the concentration change rate is greater than the preset concentration change rate threshold, the continuous deviation trend is obtained by the moving average of continuous time steps, so as to distinguish between transient data fluctuations and continuous measurement data anomalies.

[0077] In practical implementation, differential pressure sensors are installed in the pipes of the air inlet and outlet. The system collects the measured values ​​of dynamic and static pressure differences in each sampling cycle and corrects the gas density by combining temperature and humidity data, thereby calculating the real-time volumetric flow rate of the corresponding branch. At the same time, gas emission parameters are obtained based on the number of people and the standard gas emission coefficient per person. The verification and analysis module substitutes the above data with the effective volume of the room, the original concentration measurement value of the gas to be measured, and the upstream inflow concentration into the calculation, and outputs the gas mass flow rate deviation and its sliding average value at the current moment, providing a basis for subsequent determination of indoor gas sensor drift.

[0078] The compensation control module constructs a multi-constraint equation system based on the connection relationships between multiple rooms and ventilation ducts and the moving average value to locate the indoor gas sensor experiencing measurement drift. Using the moving average value as the deviation input, the least squares method is employed to fit and solve the multi-constraint equation system, with the objective function being:

[0079]

[0080] in, The total number of monitoring nodes, Let be the theoretical drift function of each node sensor, and the mapping relationship of the theoretical drift functions of each node sensor is as follows:

[0081]

[0082] in, The sensor's factory-calibrated drift rate is pre-stored in the system configuration terminal. For runtime, and The temperature and humidity compensation coefficients are obtained from a pre-set temperature and humidity compensation curve lookup table based on measured temperature and humidity data. The lookup table is generated by polynomial surface fitting of the same model sensor under different temperature and humidity gradients in the calibration test chamber. The theoretical drift of each node is obtained by solving the objective function. The node that deviates furthest from the factory calibration range is identified as the indoor gas sensor where measurement drift occurs.

[0083] After locating the indoor gas sensor experiencing measurement drift, the compensation control module performs in-situ concentration compensation and outputs the compensated concentration data. The calculation process is as follows:

[0084]

[0085]

[0086] in, This is a single-step concentration correction value, with dimensions of [missing information]. ; The moving average value corresponding to the indoor gas sensor that experienced measurement drift, with dimensions of ; The current sampling time interval, with units of . ; Let the effective volume of the target room be , with dimensions . ; The effective concentration output after compensation has dimensions of _____. ; The original concentration measurement output by the indoor gas sensor that has experienced measurement drift, with dimensions of ; The preset compensation gain coefficient is dimensionless and its value range is limited to (0,1], used to prevent system oscillation caused by excessive single compensation amplitude; the effective concentration output after compensation is obtained, and the step size and amplitude of single compensation are controlled based on the preset compensation gain coefficient.

[0087] The compensation control module uses multi-node joint analysis and airflow balance model to perform in-situ dynamic compensation for sensor anomalies and outputs calibrated monitoring data to the fresh air actuator.

[0088] The auxiliary verification module is used to send a command to the fresh air actuator to execute the linkage ventilation control when the comparison result between the sliding average value and the preset deviation threshold meets the linkage control conditions. At the same time, when the preset verification conditions are met, the system introduces the outdoor background concentration data provided by the outdoor background data acquisition node as a reference system, and uses the outdoor background concentration data to reset the zero-point reference value of the indoor gas sensor that has experienced measurement drift.

[0089] The configuration terminal, status acquisition module, flow monitoring module, verification and analysis module, compensation control module, and auxiliary verification module within the system are interconnected to collaboratively perform indoor environmental quality data acquisition and monitoring.

[0090] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An Internet of Things (IoT) system for indoor environmental quality data acquisition and monitoring, characterized in that, The system is applied to target buildings with ventilation ducts and multiple rooms, wherein the ventilation ducts include air inlets and air outlets; the system includes: a configuration terminal, a status acquisition module, a flow monitoring module, a verification and analysis module, a compensation control module, as well as an outdoor background data acquisition node, an indoor gas sensor, a differential pressure sensor, a temperature and humidity sensor, and a personnel counting device; The configuration terminal is used to preset initial parameters, which include the connection relationship between the plurality of rooms and the air inlet and air outlet of the ventilation duct; The status acquisition module is used to acquire the original concentration measurement value of the gas to be tested in the target building through the indoor gas sensor, acquire the measured value of the dynamic and static pressure difference of the ventilation duct through the differential pressure sensor, acquire outdoor background concentration data through the outdoor background data acquisition node, acquire temperature and humidity data through the temperature and humidity sensor, and acquire the number of people through the personnel counting device. The flow monitoring module is used to obtain the flow parameters of the air inlet and the air outlet based on the measured value of the dynamic and static pressure difference, and to obtain the gas emission parameters based on the number of people. The verification analysis module is used to determine the gas mass flow rate deviation assessment result based on the initial parameters, the original concentration measurement value, the flow rate parameter, and the gas emission parameter; The compensation control module is used to locate the indoor gas sensor that has experienced measurement drift based on the gas mass flow rate deviation assessment result and the connection relationship, determine the concentration correction value based on the gas mass flow rate deviation assessment result, and output the compensated concentration data.

2. The Internet of Things system for indoor environmental quality data acquisition and monitoring according to claim 1, characterized in that, The initial parameters also include: the effective volume of the plurality of rooms in the target building, the cross-sectional area of ​​the ventilation duct, the zero-point reference value of the indoor gas sensor, and the zero-point drift value of the differential pressure sensor.

3. The Internet of Things system for indoor environmental quality data acquisition and monitoring according to claim 1, characterized in that, The status acquisition module is also used to output a sampling period adjustment command based on the original concentration measurement value, including: calculating the concentration change rate at adjacent sampling times based on the original concentration measurement value; if the concentration change rate is greater than a preset concentration change rate threshold, switching the current sampling period of the corresponding indoor gas sensor to a preset high-frequency sampling period; if the concentration change rate is less than or equal to the preset concentration change rate threshold, controlling the indoor gas sensor to operate with a preset basic sampling period.

4. The Internet of Things system for indoor environmental quality data acquisition and monitoring according to claim 2, characterized in that, The flow monitoring module obtains the flow parameters of the air inlet and the air outlet of the ventilation duct based on the measured value of the dynamic and static pressure difference, and obtains the gas emission parameters based on the number of people, including: The real-time volumetric flow rate of the air inlet and the air outlet is determined based on the measured dynamic and static pressure difference, the temperature and humidity data, and the cross-sectional area of ​​the ventilation duct as the flow rate parameter; the gas emission parameter is calculated based on the number of people and the preset gas emission coefficient per person.

5. The Internet of Things system for indoor environmental quality data acquisition and monitoring according to claim 2, characterized in that, The verification analysis module determines the gas mass flow rate deviation assessment result, including: Based on the original concentration measurement, the flow rate parameter, and the gas emission parameter, a gas mass balance model is constructed in conjunction with the effective volume to calculate the gas mass flow rate deviation at the current moment; and a sliding average value is calculated based on the continuous gas mass flow rate deviation within a preset time period, and the sliding average value is used as the gas mass flow rate deviation evaluation result.

6. The Internet of Things system for indoor environmental quality data acquisition and monitoring according to claim 5, characterized in that, The system also includes an auxiliary verification module and a fresh air actuator; the auxiliary verification module is communicatively connected to the fresh air actuator; the auxiliary verification module is used to perform linkage control on the fresh air actuator based on the comparison result of the sliding average value and the preset deviation threshold, and to reset the zero-point reference value of the indoor gas sensor using the outdoor background concentration data when the preset verification conditions are met.

7. The Internet of Things system for indoor environmental quality data acquisition and monitoring according to claim 5, characterized in that, The initial parameters also include the current sampling time interval; the compensation control module locates the indoor gas sensor experiencing measurement drift based on the connection relationship and performs concentration compensation, including: Based on the connection relationship between the multiple rooms and the ventilation duct and the sliding average value, locate the indoor gas sensor that has experienced measurement drift; The concentration correction value is determined based on the sliding average value, the current sampling time interval, the effective volume of the multiple rooms in the target building, and the preset compensation gain coefficient. Concentration compensation is performed based on the preset compensation gain coefficient and the concentration correction value, and the compensated concentration data is output.

8. The Internet of Things system for indoor environmental quality data acquisition and monitoring according to claim 6, characterized in that, The auxiliary verification module performs linkage control when the comparison result between the sliding average value and the preset deviation threshold meets the preset linkage control conditions, and resets the zero-point reference value of the indoor gas sensor using the outdoor background concentration data when the preset verification conditions are met, including: When the original concentration measurement value is greater than the preset concentration threshold and the absolute value of the sliding average value is less than or equal to the preset deviation threshold, a linkage execution command is sent to the fresh air actuator. When the original concentration measurement value is greater than the preset concentration threshold and the absolute value of the sliding average value is greater than the preset deviation threshold, the linkage execution command output to the fresh air actuator is blocked, and the indoor gas sensor that outputs the original concentration measurement value is controlled to adjust the sampling cycle. When the number of people is zero for more than a preset time threshold and the gas emission parameter is less than a preset emission amount threshold, if the absolute difference between the original concentration measurement value and the outdoor background concentration data is greater than a preset bias threshold, the zero-point reference value correction of the corresponding indoor gas sensor is triggered; otherwise, the current zero-point reference value of the indoor gas sensor is maintained. In response to the shutdown signal of the fresh air actuator, the output value of the differential pressure sensor is read as the zero-point drift value of the differential pressure sensor, and the zero-point drift value of the differential pressure sensor is deducted in the subsequent calculation of the measured dynamic and static pressure difference.

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