Simulation and Design of an Internet of Things Network for Air Quality Monitoring in MATLAB Using Smart Sensors
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One of the most burning environmental issues of the contemporary urban and industrial areas has turned out to be air pollution which poses serious threats to human health, ecological balance, and overall sustainability. The traditional monitoring stations are very precise, but expensive, sparsely distributed geographically and cannot give high spatial temporal information. To overcome these constraints, the presented study suggests to simulate and design an Internet of Things (IoT)-based air quality monitoring system with the use of low-cost and smart sensors and use MATLAB/Simulink as the main development environment. The suggested framework will incorporate particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and volatile organic compound (VOC) sensors. The nodes have a microcontroller unit (ESP32 or Raspberry Pi), wireless communication system (Wi-Fi, LoRa, or NB-IoT), and an energy management system powered by a solar to maintain sustainability. A variety of data pre-processing methods (calibration, temperature and humidity compensation, noise elimination with digital filters, and Kalman filtering) are performed at the edge level to improve measurement accuracy prior to transmission, followed by the simulation of the end-to-end system (data acquisition and transmission, cloud integration and visualization) with the help of MATLAB/Simulink. Moreover, more complex algorithms like sensor fusion and machine learning models (Artificial Neural Networks (ANNs) and Long Short-Term Memory (LSTM) networks) are used to enhance air quality index (AQI) prediction and allow making predictions in the short term on pollution. The system is evaluated by use of performance metrics like: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), correlation coefficient (R2), energy consumption and network latency to determine the anticipated outcome of this research; a scalable, cost-effective, and energy-efficient IoT network that will be able to offer reliable real-time air quality monitoring and forecasting. The solution is a part of the smart city plans, aids policy-making regarding the environment, and contributes to the increase of the public awareness of their health through providing them with the accessible and high-quality air quality data.
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