IoT based indoor air quality monitoring system

With the increase in urban population and the development of industrialization, the monitoring and protection of air quality have become an increasing concern. In order to improve people's awareness of ambient air quality, the development of iot based indoor air quality monitoring system is imperative. In this paper, the design and realization of iot based indoor air quality monitoring system will be introduced in detail.

System Requirement Analysis

Before designing an indoor air quality monitoring system, it is first necessary to analyze the system requirements and define the functional and performance requirements that the system needs to meet. The main system requirements include:

1. Real-time monitoring: the system can collect, analyze, transmit, and display air quality data in real-time.

2. Multi-parameter monitoring: the system needs to be able to monitor multiple air pollution indicators at the same time, such as PM2.5, PM10, CO2, temperature, humidity, and so on.

3. Distributed Layout: The monitoring equipment needs to be distributed in different geographic locations for comprehensive air quality monitoring.

4. Data storage and analysis: the system needs to have the ability to store historical data, analyze data trends, and generate reports.

5. Alarm and warning function: When the air quality reaches a dangerous level, the system is able to issue an alarm and provide real-time warning.

System Design and Composition

Based on the above demand analysis, we can design the following indoor air quality monitoring system.

1. Sensor node: the sensor node is the core component of the system, which is responsible for collecting air quality related data in the environment. The sensor module can measure a variety of indicators, such as PM2.5, PM10, CO2, temperature, humidity, etc., and is able to send the collected data to the communication module in the form of digital signals.

2. Communication module: the communication module is responsible for the data transmission between the sensor nodes and the cloud server. The communication module uses wireless communication technology, such as Wi-Fi, cellular network, or LoRaWAN, to send the data collected by the sensor nodes to the cloud server and receive commands to control the sensor nodes.

3. Cloud server: the cloud server is the data processing and storage center of the whole system. It receives data from sensor nodes and processes, stores, and analyzes them in real time. According to different user requirements, a corresponding data display interface, early warning system, and report generation functions can be developed.

4. User Terminal: The user terminal device can be a cell phone, tablet PC, computer, etc. Users can view air quality data in real-time, receive early warning information, and generate relevant reports through the terminal device.

System workflow

The workflow of the system can be divided into four main steps: data acquisition, data transmission, data processing, and data display. Each step is described in detail below.

1. Data acquisition: Collect air quality data in the environment through sensor nodes, including PM2.5, PM10, CO2, temperature, humidity, and other indicators. The sensor node sends the collected data in the form of digital signals to the communication module.

2. Data transmission: the communication module sends the collected data to the cloud server through wireless communication technology. The transmitted data needs to be encrypted to ensure data security.

3. Data processing: the cloud server receives the data sent by the sensor nodes and processes, stores, and analyzes them in real-time. The system can generate real-time alarm information according to the trend of the data, and send warning information to the user when the air quality reaches a dangerous level.

4. Data display: Users can view air quality data in real time, receive warning information, and generate relevant reports through terminal equipment. The system can provide a visual interface to intuitively display air quality conditions and trends.

Advantages and Prospects

Iiot-based indoor air quality monitoring system has the following advantages and prospects:

1. Real-time: the system can monitor the air quality in real-time, and provide real-time data and warning information to help users understand the environmental conditions in time.

2. Accuracy: the accuracy of data collected by sensor nodes can be guaranteed, which improves the accuracy of air quality monitoring.

3. Comprehensiveness: The system supports multi-indicator monitoring, which enables a comprehensive understanding of air quality issues.

4. Expandability: the system can flexibly add new sensor nodes as needed and expand the processing capacity of the cloud server accordingly.

5. Wide application prospects: the intelligent air quality monitoring system can be widely used in cities, industrial areas, schools, hospitals, and other places, which is of great significance for improving air quality and protecting people's health.

This paper describes in detail the design and realization of an intelligent air quality monitoring system based on the Internet of Things. By analyzing the system requirements, we designed four main components, namely, sensor nodes, communication modules, cloud servers, and user terminals, and elaborated the workflow of the system. The system has the advantages of real-time, accuracy, comprehensiveness, and scalability, and has a broad application prospect. By establishing an intelligent air quality monitoring system, we can better understand the ambient air quality situation and provide strong support for improving air quality and protecting people's health.