3. Research on developing an embedded IoT system integrated with AI for real-time environmental air quality monitoring - a pilot application in Hanoi
Keywords:
Internet of Things (IoT); Air quality monitoring; PM2.5; Time series forecasting; ARIMA; Long Short-Term Memory (LSTM); Real-time data analysis; Environmental monitoring.Abstract
Air pollution, particularly fine particulate matter (PM2.5), poses a serious challenge in major cities such as Hanoi. This study develops an air quality monitoring system based on Internet of Things (IoT) technology, enabling real-time collection and analysis of air quality data, including parameters such as PM2.5, CO₂, temperature, and humidity. The system was tested in Hanoi and integrated with time series forecasting models AutoRegressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) to provide predictions of future pollution trends. Experimental results demonstrate the system’s capability for accurate monitoring and forecasting, thereby supporting governmental agencies in implementing timely preventive measures.