Ventilation control system and method based on Internet of Things

Abstract

The invention discloses a ventilation control system and method based on the Internet of Things, and relates to the technical field of environment control and regulation, and the system comprises an environment data collection module, a central control module, a ventilation execution module, a communication module and a user interaction module. Temperature, humidity, carbon dioxide concentration and PM2.5 concentration are monitored in real time through the environment data acquisition module, the central control module calculates ventilation demand intensity according to a ventilation demand function, and the operation frequency and air volume output of ventilation equipment are dynamically adjusted through a formula, so that a set environment target value is met. The communication module is used for remotely transmitting data and instructions, and the user interaction module provides real-time data display and parameter adjustment functions. The system further comprises an energy-saving mode, and when the ventilation requirement is lower than a set threshold value, the operation frequency of the equipment is reduced so as to reduce energy consumption. In addition, the system has fault detection and alarm functions, and equipment abnormity is judged by monitoring operation parameters and a user is notified in time.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental control and regulation, and more particularly, to an Internet of Things-based ventilation control system and method. Background Art

[0002] With the continuous acceleration of industrialization and urbanization, air pollution and environmental quality problems have become increasingly serious. In industrial production, agricultural greenhouse cultivation, and the operation of public buildings, air quality management has become an important task. Traditional ventilation systems usually adopt fixed parameter settings or simple timing control methods, and there are the following main problems:

[0003] Poor ventilation effect: Traditional ventilation systems cannot dynamically adjust operating parameters according to real-time environmental changes. For example, in industrial workshops, the production process will cause fluctuations in temperature, humidity, and pollutant concentration. Ventilation equipment with a fixed air volume cannot effectively respond to this change, which may lead to local air pollution or the emergence of high-temperature areas.

[0004] Serious energy waste: Most traditional ventilation systems operate at maximum demand, and still maintain a high operating state even under low-load conditions (such as at night or when the number of people decreases), resulting in energy waste. Especially in large public buildings, such as shopping malls and office buildings, the energy consumption problem is particularly prominent.

[0005] Lack of intelligent monitoring and regulation: Traditional systems usually rely on manual parameter settings and lack the ability to collect and analyze environmental data in real time. For abnormal air quality conditions (such as high concentrations of carbon dioxide or PM2.5), they cannot respond in a timely manner. In addition, it is difficult for users to understand the operating status of the system remotely, and they cannot quickly adjust the operating strategy of the ventilation equipment.

[0006] High maintenance cost: Due to the lack of intelligent monitoring of the equipment operating status, traditional ventilation systems cannot detect faults or abnormal operations in advance and often rely on regular manual inspections. This method not only increases the maintenance cost, but also may lead to the failure not being detected in time, thus affecting the ventilation effect or the service life of the equipment.

[0007] In recent years, the rapid development of Internet of Things technology has provided new opportunities for the intelligentization of ventilation systems. The Internet of Things-based ventilation control system can collect environmental data in real time through a sensor network and achieve dynamic regulation in combination with intelligent algorithms, and the specific advantages are as follows:

[0008] Real-time monitoring and response: Internet of Things technology can achieve real-time monitoring of temperature, humidity, carbon dioxide concentration, and particulate matter concentration, and calculate the current ventilation demand based on the collected data, so as to dynamically adjust the operating status of the fan and valve.

[0009] Energy - saving and efficient: Through precise control, the Internet of Things system can adjust the operation of devices according to actual needs, avoiding energy waste. For example, it can reduce the operating frequency under low - load conditions and enhance the ventilation capacity under high - demand conditions, thus significantly reducing energy consumption.

[0010] Remote monitoring and management: Users can view the system operation status in real - time through mobile devices or PC terminals and remotely adjust parameters or switch operation modes. At the same time, the system can also share data through the cloud platform to support ventilation management in multiple regions.

[0011] Intelligent fault detection and alarm: The Internet - of - Things - based system can analyze device operation parameters in real - time (such as fan frequency, power consumption, etc.) to determine whether the device is abnormal. When a deviation is detected, the system will actively alarm and provide fault information to help users quickly locate the problem.

[0012] Although there have been some studies and developments on Internet - of - Things - based intelligent ventilation systems, the current technical solutions still have deficiencies. For example, some systems lack the ability to comprehensively calculate multiple parameters (such as temperature and humidity, carbon dioxide, and PM2.5 concentration), resulting in a single regulation strategy and being unable to comprehensively optimize the ventilation effect. In addition, most existing systems have insufficient depth in monitoring and regulating the operation of devices, lacking dynamic correlation modeling between power consumption and ventilation demand, and it is difficult to achieve high - precision energy - saving optimization.

[0013] Based on the above background, the present invention proposes an Internet - of - Things - based ventilation control system and its method. This system can collect a variety of environmental parameters in real - time, comprehensively calculate the ventilation demand, and dynamically adjust the operation status of ventilation devices to achieve intelligent management with high energy - saving efficiency. By introducing intelligent algorithms, remote monitoring, and fault - detection functions, the present invention significantly improves the ventilation effect while greatly reducing energy consumption and maintenance costs, having significant technical advantages and broad application prospects. Summary of the Invention

[0014] The purpose of the present invention is to solve the problems raised in the above - mentioned background technology and provide an Internet - of - Things - based ventilation control system and its method.

[0015] The above object of the present invention is achieved as follows: An Internet - of - Things - based ventilation control system, comprising: An environmental data acquisition module for collecting environmental parameters , where: represents temperature (unit: °C) and is collected in real - time through a high - precision temperature sensor; represents humidity (unit: %) and the air humidity is monitored through a humidity sensor; represents carbon dioxide concentration (unit: ppm) and the air quality index in the environment is collected through a carbon dioxide sensor; represents the PM2.5 concentration (unit: μg / m3), and measures the particulate matter content in the air through a particulate matter sensor; The central control module is used to receive environmental parameters , and calculates the ventilation demand through an embedded algorithm, generating corresponding ventilation control instructions; The ventilation execution module is used to control the operating state of ventilation equipment (including fans, exhaust fans, valves, etc.) according to the ventilation control instructions, dynamically adjusting the air volume and wind speed; The communication module is used to realize the remote transmission of environmental parameters and control instructions, and realizes the real-time interaction of data through a wireless communication protocol (such as Wi-Fi, LoRa or 5G); The user interaction module is used for users to view environmental parameters and equipment operating states through a mobile terminal, and remotely adjust system settings and control strategies.

[0016] As a preferred technical solution of the present invention, the central control module uses the following ventilation demand function for calculation: Where: is the environmental target value set by the user, representing the target temperature, humidity, carbon dioxide concentration and PM2.5 concentration; is the weight coefficient of each environmental parameter, used to measure the influence degree of each parameter on the ventilation demand, and satisfies the constraint condition is the ventilation demand intensity, which is a comprehensive index. The larger the value, the higher the ventilation demand of the current environment. This function comprehensively evaluates the ventilation demand by performing weighted calculations on the differences between the actual environmental parameters and the target parameters.

[0017] As a preferred technical solution of the present invention, the central control module calculates the operating parameters of the ventilation equipment based on the ventilation demand function where: Where: is the operating frequency of the ventilation equipment (unit: Hz), used to control the rotation speed of the fan; is the equipment operating efficiency coefficient, determined according to the specific model and characteristics of the ventilation equipment. The operating parameter is directly proportional to the square root of the ventilation demand intensity , and can reduce the equipment operating frequency when the demand is low, thereby reducing energy consumption.

[0018] As a preferred technical solution of the present invention, the air volume output by the fan in the ventilation execution module Is linearly related to the operating parameters Show a linear relationship: Where: Is the air volume output by the fan (unit: m 3 , h), reflecting the actual ventilation capacity of the fan; m Is the fan characteristic coefficient, related to the physical structure of the equipment and the performance of the motor. By controlling the operating parameters , the system can precisely adjust the air volume output of the fan to meet the ventilation requirements of different scenarios.

[0019] As a preferred technical solution of the present invention, the power consumption of the ventilation equipment Is calculated according to the operating frequency Calculate 2 ; Where: Is the power consumption (unit: W), used to evaluate the energy consumption level of the equipment operation; Is the power coefficient, related to the equipment specifications and the operating load. The power consumption is directly proportional to the square of the operating frequency, indicating that the energy consumption of the fan increases more significantly during high-frequency operation. Therefore, reasonable control of is crucial for energy conservation.

[0020] As a preferred technical solution of the present invention, the central control module includes an energy-saving mode. When the ventilation demand intensity is , the operating parameters are adjusted to , where: Is the lowest threshold of the ventilation demand, preset by the user;

[0021] Is the lowest operating frequency of the ventilation equipment, preventing the equipment from stopping due to too low a frequency. The energy-saving mode can significantly reduce the energy consumption of the equipment and is applicable to scenarios such as at night or when the environment is stable. As a preferred technical solution of the present invention, the central control module also includes a fault detection function. By continuously monitoring the relationship between the operating parameters Where: is the fault judgment error threshold, which is determined by the device characteristics and operating environment; when this condition is met, the system determines that there may be abnormalities in the ventilation equipment, such as fan overload, blockage, or motor failure, and sends alarm information to the user terminal through the communication module. This function can effectively ensure the stability and safety of the system operation.

[0022] As a preferred technical solution of the present invention, the user interaction module supports remote parameter adjustment, and users can set target parameters through a mobile terminal and the weight coefficient , and real-time monitor the operating status of the ventilation equipment. After the user adjusts the parameters, the central control module recalculates the ventilation demand function , and dynamically adjusts the operating parameters .

[0023] The present invention also provides an Internet of Things-based ventilation control method, including the following steps: Step 1: Collect environmental parameters through the environmental data collection module Step 2: Upload the environmental parameters to the central control module through the communication module ; Step 3: The central control module calculates the operating parameters of the ventilation equipment according to the ventilation demand function: ; Step 4: The ventilation execution module adjusts the air volume output of the fan according to the operating parameters ; Step 5: Real-time monitor the power consumption of the equipment , judge whether a fault occurs, and if an abnormality is found, trigger an alarm; Step 6: The user views the environmental data and the operating status of the equipment through the user interaction module, and adjusts the target parameters and the weight coefficient when necessary, to achieve remote management of the system.

[0024] Compared with the prior art, the present invention has the following beneficial effects: By collecting environmental parameters in real time and dynamically calculating the ventilation demand in combination with intelligent algorithms, the present invention can accurately adjust the operating frequency and air volume of the ventilation equipment, significantly improve the ventilation efficiency, and ensure that the environmental parameters are maintained within the target range. Compared with the traditional ventilation system with fixed timing or fixed parameters, the present invention can be flexibly adjusted according to actual needs, solving the problem of poor ventilation effect during environmental fluctuations.

[0025] The present invention reduces energy waste by introducing an energy-saving mode that automatically lowers the operating frequency of equipment under low-load conditions. Meanwhile, through an accurate power consumption calculation model, the relationship between energy consumption and ventilation requirements is optimized, avoiding unnecessary high-power operation, and is particularly suitable for large-area, high-energy consumption scenarios such as industrial plants and public buildings.

[0026] The system integrates a fault detection and alarm function, which can monitor the operating status of equipment in real time and notify users in a timely manner when abnormalities occur, effectively reducing the risk of equipment failure. In addition, through the user interaction module, users can remotely view environmental data and adjust control parameters to achieve convenient intelligent management. This design not only improves the security of the system but also reduces manual operation and maintenance costs, enhancing the overall user experience. Brief Description of the Drawings

[0027] To more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0028] Figure 1 It is a system block diagram of a ventilation control system based on the Internet of Things according to the present invention. Detailed Embodiments

[0029] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0030] The following combines the attached Figure 1 drawings and multiple embodiments to describe the detailed embodiments of the present invention in detail.

[0031] Embodiment 1: A ventilation control system based on the Internet of Things for industrial plants; This embodiment describes an intelligent ventilation system used in an industrial plant, which effectively solves the problems of high temperature, dust, and excessive carbon dioxide concentration by dynamically adjusting the operating status of ventilation equipment.

[0032] 1. System composition: Environmental data acquisition module: Install multiple groups of sensors in different areas of the plant to monitor temperature ( ) and humidity ( , carbon dioxide (degree) C), and PM2.5 (degree) Q). The sensor is connected to the central control module by wire or wirelessly.

[0033] Central control module: Receives real-time data from the environmental data acquisition module , calculates the wind demand intensity through a preset algorithm , and generates a control signal based on the demand.

[0034] Ventilation execution module: Includes multiple industrial fans and valves for dynamically adjusting the operation frequency and air volume , to achieve uniform air circulation and cleaning.

[0035] Communication module: Through Wi-Fi or LoRa technology, realizes the remote transmission of environmental data and sends control instructions to the ventilation execution module.

[0036] User interaction module: Users can view real-time environmental parameters and equipment operation status through a mobile APP or PC terminal, and can also adjust the target environmental parameters according to (such as target temperature, humidity, etc.).

[0037] 2. System parameters and working principle: The factory needs to maintain a temperature of °C, and the humidity is within , the carbon dioxide concentration does not exceed ppm, and the PM2.5 concentration does not exceed μg / m³.

[0038] The weight coefficient is .

[0039] Calculate the ventilation demand intensity: The central control module calculates the ventilation demand function in real time: : where is the real-time collected environmental parameter.

[0040] Adjust the equipment operation frequency: According to calculate the fan operation frequency where is the equipment efficiency coefficient, determined according to the equipment specifications.

[0041] Determine the fan output air volume: The air volume has the following relationship with the operation frequency : where is the fan characteristic coefficient. Energy consumption calculation: Calculate the fan power consumption in real time

[0042] Among them is the power coefficient.

[0043] 3. Example operation: Suppose the environmental parameters in the factory building at a certain moment are °С, , ppm, μg / m’ Calculate the ventilation demand intensity: .

[0044] Determine the operating frequency: Output air volume: Rate consumption: 4. Energy-saving mode and fault detection: When the environmental parameters are close to the target values (such as at night or when the number of people decreases), if ,, the system switches to the energy-saving mode and reduces the fan frequency to Hz, saving energy consumption.

[0045] Monitor the operating status of the fan in real time: If it is found that the deviation exceeds the threshold , the system triggers an alarm and notifies the user through the APP.

[0046] Example 2: Intelligent ventilation for agricultural greenhouses; control system; 1. Target values of environmental parameters; This embodiment is applied to an agricultural greenhouse to provide a suitable crop growth environment by precisely controlling the temperature, humidity and carbon dioxide concentration.

[0047] Target temperature value: °C; Target humidity value: Target carbon dioxide concentration value: ppm; Weight coefficient .

[0048] 2. Actual operation example: Suppose the environmental parameters are °C, , ppm, Calculate the ventilation demand: .

[0049] Operating frequency: Air volume: The system adjusts the air volume according to temperature and humidity fluctuations, and monitors the carbon dioxide concentration in real time to ensure meeting the photosynthesis requirements of crops.

[0050] Example 3: Intelligent ventilation system for public buildings; 1. Environmental target parameters: This example describes a ventilation system used in shopping malls and office buildings, aiming to dynamically regulate air quality.

[0051] Temperature °C; Humidity Carbon dioxide concentration ppm; PM2.5 concentration μg / m³ Weight coefficient .

[0052] 2. System operation: The environment in the shopping mall is °C, ppm, μg / m³, Ventilation demand intensity: , Operating frequency , Air volume: .

[0053] The system increases the air volume during peak periods to reduce the carbon dioxide concentration, and switches to the low-power mode at night to maintain the minimum ventilation demand.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A ventilation control system based on the Internet of Things, characterized in that: include: Environmental data collection module: used to collect environmental parameters , in: Indicates temperature, which is collected in real time through a high-precision temperature sensor; Indicates humidity, and monitors air humidity through a humidity sensor; Indicates the concentration of carbon dioxide, and collects air quality indicators in the environment through carbon dioxide sensors; Indicates PM2.5 concentration, which is measured by a particle sensor to measure the amount of particulate matter in the air; Central control module: used to receive environmental parameters , and calculate the ventilation demand through embedded algorithms to generate corresponding ventilation control instructions; Ventilation execution module: used to control the operating state of the ventilation equipment according to the ventilation control instructions, and dynamically adjust the air volume and wind speed; Communication module: used to realize remote transmission of environmental parameters and control instructions, and to achieve real-time data interaction through wireless communication protocols; User interaction module: used for users to view environmental parameters and equipment operating status through mobile terminals, and remotely adjust system settings and control strategies.

2. The system according to claim 1, characterized in that The central control module uses the following ventilation demand function Perform the calculation: in: Environmental target values ​​set by the user, representing target temperature, humidity, carbon dioxide concentration, and PM2.5 concentration; is the weight coefficient of each environmental parameter, which is used to measure the influence of each parameter on ventilation demand and meet the constraints: ； The ventilation demand intensity is a comprehensive indicator. The larger the value, the higher the demand for ventilation in the current environment.

3. The ventilation control system based on the Internet of Things according to claim 2 is characterized in that: The central control module is based on the ventilation demand function Calculate operating parameters of ventilation equipment in: It is the operating frequency of the ventilation equipment, used to control the speed of the fan; It is the equipment operating efficiency coefficient, which is determined based on the specific model and characteristics of the ventilation equipment.

4. The ventilation control system based on the Internet of Things according to claim 3 is characterized in that: The fan output air volume in the ventilation execution module With operating parameters Linear relationship: in: It is the air volume output by the fan, reflecting the actual ventilation capacity of the fan; It is the fan characteristic coefficient, which is related to the physical structure of the equipment and the motor performance.

5. The ventilation control system based on the Internet of Things according to claim 4 is characterized in that: Power consumption of ventilation equipment According to the operating frequency calculate: in: Power consumption is used to evaluate the energy consumption level of equipment operation; is the power factor, which is related to equipment specifications and operating load.

6. The ventilation control system based on the Internet of Things according to claim 1, characterized in that: The central control module includes an energy-saving mode. When running parameters Adjusted to ,in: It is the minimum threshold for ventilation demand, which is preset by the user; It is the minimum operating frequency of the ventilation equipment to prevent the equipment from stopping due to too low frequency.

7. The ventilation control system based on the Internet of Things according to claim 6, characterized in that: The central control module also includes a fault detection function, which monitors the operating parameters in real time. , output air volume and power consumption The relationship between the two is used to determine whether the equipment has a fault. The judgment basis is: in: It is the fault judgment error threshold, which is determined by the equipment characteristics and operating environment. When this condition is met, the system determines that the ventilation equipment may have an abnormality, such as fan overload, blockage or motor failure, and sends the alarm information to the user terminal through the communication module.

8. The ventilation control system based on the Internet of Things according to claim 1, characterized in that: The user interaction module supports remote parameter adjustment, and users can set target parameters through mobile terminals and weight coefficient , and monitor the operating status of the ventilation equipment in real time. After the user adjusts the parameters, the central control module recalculates the ventilation demand function , and dynamically adjust operating parameters .

9. A ventilation control method based on the Internet of Things, comprising the following steps: Step 1: Collect environmental parameters through the environmental data collection module ; Step 2: Transmit environmental parameters through the communication module Upload to the central control module; Step 3: The central control module is based on the ventilation demand function Calculate operating parameters of ventilation equipment ; Step 4: The ventilation execution module is based on the operating parameters Adjust the fan output volume ; Step 5: Monitor the power consumption of your device in real time , determine whether a fault occurs, and trigger an alarm if an abnormality is found; Step 6: The user checks the environmental data and equipment operation status through the user interaction module and adjusts the target parameters if necessary. and weight coefficient , to achieve remote management of the system.

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