Air quality detection system, method and equipment based on wireless sensor network

Abstract

The invention discloses an air quality detection system, method and device based on a wireless sensor network, the system comprises sensor units installed at all indoor positions, and also comprises a detection base station, the sensor units are in communication connection with the detection base station through a ZigBee protocol; the system further comprises an HVAC system and a demand control ventilation module arranged in the HVAC system. The demand control ventilation module is used for adjusting the ventilation rate of the HVAC system according to data of the sensor unit. The system comprises a detection base station and an HVAC system, and further comprises a context sensing module, the context sensing module is connected with the detection base station and the HVAC system, and the context sensing module is used for adjusting the HVAC system through data of the sensor unit according to a preset rule. And the indoor air quality condition can be accurately reflected. By means of the real-time data, the system can find out the air pollution problem in time and take countermeasures rapidly, and it is ensured that indoor air is always kept within the healthy standard.

Description

Technical Field

[0001] The present invention relates to the field of air quality detection of the Internet of Things, and in particular to an air quality detection system, method and equipment based on a wireless sensor network. Background Art

[0002] Indoor Air Quality (IAQ) is a term that describes the quality of air in a building; specifically it refers to the health and comfort of building occupants. It refers to the nature of the air that circulates throughout the spaces where we work and live. Today, air pollution under the roof is a growing problem. Since individuals spend 90% of their time indoors (schools, offices, institutions, commercial facilities), indoor air quality is the most important factor affecting people's health, comfort, and safety. Indoor air pollution can lead to health problems known as Sick Building Syndrome (SBS) and Building Related Illness (BRI). The symptoms of SBS do not fit the pattern of any specific disease. It is difficult to trace any specific source, and the symptoms ease after leaving the building. However, the symptoms associated with Building Related Illness (BRI) do not ease after leaving the building. BRI is caused by microbial contamination or exposure to specific chemicals and can cause allergies.

[0003] Indoor air quality can be affected by microbial contaminants (mold, fungus) that are largely dependent on the temperature and humidity conditions of the room, gaseous pollutants (including carbon monoxide, carbon dioxide, volatile organic compounds, etc.), and dust particles or aerosols. These pollutants can adversely affect the health of building occupants. Inadequate ventilation can increase indoor pollutant levels because not enough outdoor air is introduced to dilute emissions from indoor sources. High temperatures and humidity can also increase the concentration of some pollutants. The use of ventilation to dilute pollutants, indoor source control, and air filtration are the primary methods for maintaining good indoor air quality in most buildings.

[0004] These health problems are closely related to the concentration of indoor pollutants (such as carbon dioxide, particulate matter, volatile organic compounds, etc.). In order to avoid such adverse effects, an air quality monitoring system is most needed. Therefore, it is urgent to develop a system that can effectively monitor and control indoor air quality to determine the environmental health status of indoor spaces. This system is combined with the context-aware framework (CAF) and provides environmental information as input for controlling the HVAC (heating, ventilation and air conditioning) system in smart buildings. It realizes intelligent control of the HVAC system, automatically adjusts the ventilation volume according to factors such as indoor air quality and occupancy density, keeps the indoor air quality within a safe range, and saves energy at the same time. Summary of the invention

[0005] The technical problem solved by the present invention is to provide an air quality detection system based on a wireless sensor network, which can minimize unnecessary energy consumption while ensuring air quality, thereby reducing the energy expenditure of a building.

[0006] The technical solution adopted by the present invention to solve the technical problem is: an air quality detection system based on a wireless sensor network, including sensor units installed at various positions indoors, and also including a detection base station, wherein the sensor unit is connected to the detection base station through a ZigBee protocol;

[0007] Also included is an HVAC system and a demand control ventilation module disposed in the HVAC system, the demand control ventilation module being configured to adjust a ventilation rate of the HVAC system based on data from the sensor unit;

[0008] It also includes a context perception module, which is connected to the detection base station and the HVAC system respectively, and is used to adjust the HVAC system according to preset rules based on the data of the sensor unit.

[0009] Furthermore, the sensor unit is a CO sensor, a CO2 sensor or an aerosol monitor.

[0010] Furthermore, it also includes a data acquisition module and a display module, and the data acquisition module is connected to the detection base station and the display module respectively;

[0011] The data acquisition module is used to receive sensor data of the detection base station and display the sensor data in the display module.

[0012] The present invention also discloses an air quality detection method based on a wireless sensor network, comprising the air quality detection system based on a wireless sensor network as described above,

[0013] S100: The sensor unit detects CO, CO2 and aerosol data at various locations in the room, and communicates with the detection base station through the ZigBee protocol to transmit monitoring data in real time;

[0014] S200: The demand control ventilation module obtains CO2 concentration data from the detection base station and adjusts the ventilation rate of the HVAC system according to the CO2 concentration data;

[0015] S300: The context perception module obtains monitoring data of the detection base station for subscription and use by the HVAC system. When the monitoring data triggers a predefined rule, the HVAC system executes an operation corresponding to the predefined rule.

[0016] Furthermore, the method further comprises step S400: the data acquisition module acquires data of each sensor unit in the detection base station, and displays the acquired data in the display module.

[0017] Furthermore, a remote access step is also included, specifically, an administrator can remotely monitor the detection data in the detection base station and control the HVAC system.

[0018] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned air quality detection method based on a wireless sensor network are implemented.

[0019] The present invention also discloses a computer device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; wherein:

[0020] The memory is used to store computer programs;

[0021] The processor is used to execute the steps of the above-mentioned air quality detection method based on wireless sensor network by running the program stored in the memory.

[0022] The beneficial effect of the present invention is that the technical solution of the present invention can accurately reflect the indoor air quality status by real-time monitoring of multiple key pollutants in the air, such as carbon dioxide (CO2), carbon monoxide (CO), particulate matter (PM2.5, PM10), etc. With the help of these real-time data, the system can promptly detect air pollution problems and quickly take countermeasures, such as starting the ventilation system or adjusting the air conditioning settings to ensure that the indoor air is always within the health standard. This continuous air quality monitoring and control can not only effectively reduce the occurrence of "sick building syndrome" and "building-related diseases", but also significantly improve the health level and quality of life of residents. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of the architecture of an air quality detection system based on a wireless sensor network according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention.

[0025] like Figure 1As shown, the embodiment of the present application discloses an air quality detection system based on a wireless sensor network, including sensor units installed at various positions indoors, and also including a detection base station, wherein the sensor unit is connected to the detection base station through a ZigBee protocol;

[0026] Also included is an HVAC system and a demand control ventilation module disposed in the HVAC system, the demand control ventilation module being configured to adjust a ventilation rate of the HVAC system based on data from the sensor unit;

[0027] It also includes a context-aware framework (CAF), which is connected to the detection base station and the HVAC system respectively. The context-aware framework is used to adjust the HVAC system according to preset rules based on the data of the sensor unit.

[0028] Specifically, the sensor unit of the present application adopts the Waspmote sensor node produced by Libelium, equipped with a gas sensor board. Specifically, the gas sensor board can be a TGS2442 sensor for detecting CO and a TGS 4161 sensor for detecting CO2, or a DustTrakDRX 8533 aerosol monitor of TSI for detecting particulate matter in the air.

[0029] This system can accurately reflect the indoor air quality by real-time monitoring of a variety of key pollutants in the air, such as carbon dioxide (CO2), carbon monoxide (CO), particulate matter (PM2.5, PM10), etc. With these real-time data, the system can promptly detect air pollution problems and quickly take countermeasures, such as starting the ventilation system or adjusting the air conditioning settings to ensure that the indoor air is always within the health standard. This continuous air quality monitoring and control can not only effectively reduce the occurrence of "sick building syndrome" and "building-related diseases", but also significantly improve the health level and quality of life of residents.

[0030] In this embodiment, a data acquisition module and a display module are also included, and the data acquisition module is connected to the detection base station and the display module respectively;

[0031] The data acquisition module is used to receive sensor data of the detection base station and display the sensor data in the display module.

[0032] Specifically, the detection base station receives data from the sensor nodes regularly through the ZigBee protocol. The data acquisition module is built by the Python program, which is responsible for parsing the data packets and displaying the real-time monitoring data. Users can view the real-time and historical data through the user interface.

[0033] The configuration of the above modules can realize a more intuitive and accurate observation of the detected air quality data, thereby enabling better subsequent adjustments to the HVAC system.

[0034] The present invention also discloses an air quality detection method based on a wireless sensor network, including the air quality detection system based on a wireless sensor network described above, characterized in that:

[0035] S100: The sensor unit detects CO, CO2 and aerosol data at various locations in the room, and communicates with the detection base station through the ZigBee protocol to transmit monitoring data in real time;

[0036] S200: The demand control ventilation module obtains CO2 concentration data from the detection base station and adjusts the ventilation rate of the HVAC system according to the CO2 concentration data;

[0037] S300: The context perception module obtains monitoring data of the detection base station for subscription and use by the HVAC system. When the monitoring data triggers a predefined rule, the HVAC system executes an operation corresponding to the predefined rule.

[0038] Specifically, the operation process of the indoor air quality monitoring system is a continuous and automated process, starting with data collection from sensor nodes, which are scattered throughout the monitoring area and collect environmental data on temperature, humidity, gas concentrations, and particulate matter levels in real time. Through the built-in wireless communication module, these data are transmitted to the central base station, which acts as a coordinator for the entire network and is responsible for receiving, preliminarily processing, and storing data. In the central database, the data is securely stored and optimally indexed for quick retrieval and analysis. The user module, as a display of the system, extracts data from the database and presents it to the user, allowing the user to intuitively understand the current indoor air quality status.

[0039] The demand-controlled ventilation module and the context-aware module work together to adjust the ventilation system to maintain indoor air quality based on real-time sensor data and occupancy. The demand-controlled ventilation module controls the ventilation rate by monitoring CO2 concentration, which is a reliable indicator of occupancy. Based on the difference in CO2 concentration between indoor and outdoor, the demand-controlled ventilation module can dynamically adjust the ventilation rate to ensure that the indoor air quality is within a healthy range while reducing unnecessary energy consumption. With CO2-based ventilation control, the system can effectively save energy, especially in environments with large occupancy changes, such as conference rooms, shopping malls, etc.

[0040] The context-aware module contains a rules engine for making decisions based on sensor data. These rules can be set based on conditions such as air quality index (AQI) to trigger a response from the system. The rules engine evaluates the sensor data based on the set trigger conditions and performs the corresponding actions. When a rule is triggered, the context-aware module performs the corresponding action. For example, if the CO2 concentration exceeds a certain threshold, CAF may notify the HVAC system to increase ventilation, or send an alert to the user.

[0041] Examples of preset rules:

[0042] 1) AQI below 50 (good air quality): At this time, the demand control ventilation module adjusts the ventilation rate according to the actual occupancy in the building, maintaining minimum fresh air input to save energy.

[0043] 2) AQI between 51 and 100 (moderate air quality): Continue to maintain ventilation based on occupancy, and no additional system adjustments are required.

[0044] 3) AQI between 101 and 150 (unhealthy for sensitive groups): At this time, the system increases the ventilation rate and sends alerts to sensitive groups (such as children, the elderly or people with respiratory diseases).

[0045] 4) AQI exceeds 150 (unhealthy or higher): The system operates at maximum ventilation rate and sends alerts to all users via SMS or email. At higher AQI levels (such as AQI greater than 200), the system may also trigger an emergency notification requiring evacuation.

[0046] Specifically, the following is a specific embodiment of the application:

[0047] Step 1: Demand Analysis

[0048] Determine the rooms, areas or floors that need to be monitored based on the structure and usage of the building. Determine the air quality parameters that need to be monitored (such as CO2, CO, PM2.5, PM10, temperature, humidity, etc.) and select appropriate sensors based on these parameters.

[0049] Step 2: Sensor Installation

[0050] Choose the appropriate sensor module according to the monitoring parameters. For example, the TGS2442 sensor can be used to detect CO, the TGS4161 sensor can be used to detect CO2, and the DustTrak DRX 8533 can be used for particulate matter monitoring. Use the appropriate wireless sensor network module ZigBee, the specific choice depends on the layout of the building, signal coverage and data transmission requirements. Choose the appropriate base station and data collector to receive the sensor data and transmit it to the central control system.

[0051] Arrange the sensor locations according to the building plan. Make sure the sensors cover the entire monitoring area and avoid installing them in corners where air circulation is too frequent or too closed. Calibrate the sensors before installation to ensure accurate readings. Calibration can be performed using laboratory standard gases or reference equipment.

[0052] Step 3: Communication network settings

[0053] Install the base station in a suitable location to ensure that it can maintain good communication with all sensor nodes. The mesh network structure of the ZigBee protocol can be used to enhance signal coverage. Configure the communication protocol and frequency between the sensor and the base station to ensure stable and reliable data transmission. A gateway device can be used to convert sensor data from the ZigBee network to the Internet Protocol (IP) for communication with the central system.

[0054] Step 4: Software system configuration

[0055] Deploy a server in the central control room to receive, store, and process data. Select appropriate server hardware configuration and storage devices based on the data volume and processing requirements. Develop or configure a data acquisition program written in Python to receive data packets from the base station and parse them into usable air quality data. Set up a database for storing air quality data, using the relational database MySQL to handle large-scale data.

[0056] Deploy the context-aware module CAF (ContextAware Framework), deploy the CAF middleware on the server, and configure its connection with the sensor network. CAF is responsible for managing sensor data and providing it to the decision module at the application layer. Define the automatic control rules of the HVAC system based on the thresholds of air quality parameters. For example, when the CO2 concentration exceeds the preset value, CAF will instruct the HVAC system to increase ventilation.

[0057] This method can accurately reflect the indoor air quality by real-time monitoring of multiple key pollutants in the air, such as carbon dioxide (CO2), carbon monoxide (CO), particulate matter (PM2.5, PM10), etc. With these real-time data, the system can promptly detect air pollution problems and take quick countermeasures, such as starting the ventilation system or adjusting the air conditioning settings to ensure that the indoor air is always within the health standard. This continuous air quality monitoring and control can not only effectively reduce the occurrence of "sick building syndrome" and "building-related diseases", but also significantly improve the health level and quality of life of residents.

[0058] In this embodiment, step S400 is also included: the data acquisition module acquires data of each sensor unit in the detection base station, and displays the acquired data in the display module.

[0059] The configuration of the above modules can realize a more intuitive and accurate observation of the detected air quality data, thereby enabling better subsequent adjustments to the HVAC system.

[0060] This embodiment also includes a remote access step, specifically: an administrator can remotely monitor the detection data in the detection base station and control the HVAC system.

[0061] The setting of this step can realize the control of the HVAC system anytime and anywhere, making the use of this system more user-friendly.

[0062] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the air quality detection method based on a wireless sensor network are implemented.

[0063] In addition, the computer-readable storage medium of this embodiment may adopt any combination of one or more computer-readable storage media, wherein the computer-readable storage medium includes electrical, optical, electromagnetic, infrared or semiconductor systems, devices or components, or any combination thereof.

[0064] The present invention also discloses a computer device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; wherein:

[0065] The memory is used to store computer programs;

[0066] The processor is used to execute the steps of the above-mentioned air quality detection method based on wireless sensor network by running the program stored in the memory.

[0067] As an embodiment of the present invention, the communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0068] As an implementation mode of the present invention, the communication interface is used for communication between the above-mentioned terminal and other devices.

[0069] As an embodiment of the present invention, the memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0070] As an embodiment of the present invention, the above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0071] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An air quality detection system based on wireless sensor network, Features: It includes sensor units installed at various locations indoors, and also includes a detection base station, wherein the sensor units are connected to the detection base station through a ZigBee protocol; Also included is an HVAC system and a demand control ventilation module disposed in the HVAC system, the demand control ventilation module being configured to adjust a ventilation rate of the HVAC system based on data from the sensor unit; It also includes a context perception module, which is connected to the detection base station and the HVAC system respectively, and is used to adjust the HVAC system according to preset rules based on the data of the sensor unit.

2. The air quality detection system based on wireless sensor network as claimed in claim 1, Features: The sensor unit is a CO sensor, a CO2 sensor or an aerosol monitor.

3. The air quality detection system based on wireless sensor network as claimed in claim 1, Features: It also includes a data acquisition module and a display module, wherein the data acquisition module is connected to the detection base station and the display module respectively; The data acquisition module is used to receive sensor data of the detection base station and display the sensor data in the display module.

4. An air quality detection method based on a wireless sensor network, comprising an air quality detection system based on a wireless sensor network as claimed in any one of claims 1 to 3, Features: S100: The sensor unit detects CO, CO2 and aerosol data at various locations in the room, and communicates with the detection base station through the ZigBee protocol to transmit monitoring data in real time; S200: The demand control ventilation module obtains CO2 concentration data from the detection base station and adjusts the ventilation rate of the HVAC system according to the CO2 concentration data; S300: The context perception module obtains monitoring data of the detection base station for subscription and use by the HVAC system. When the monitoring data triggers a predefined rule, the HVAC system executes an operation corresponding to the predefined rule.

5. The air quality detection method based on wireless sensor network as claimed in claim 4, Features: The process also includes step S400: the data acquisition module acquires data from each sensor unit in the detection base station, and displays the acquired data in the display module.

6. The air quality detection method based on wireless sensor network as claimed in claim 4, Features: It also includes a remote access step, specifically: the administrator can remotely monitor the detection data in the detection base station and operate the HVAC system.

7. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the air quality detection method based on a wireless sensor network in any one of claims 1 to 6 are implemented.

8. A computer device, It is characterized in that It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; wherein: The memory is used to store computer programs; The processor is used to execute the steps of the air quality detection method based on a wireless sensor network according to any one of claims 1 to 6 by running the program stored in the memory.

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