This document describes the development and implementation of an air quality monitoring system that supports artificial intelligence (AI) to increase the accuracy and efficiency of air quality assessments.As urbanisation and industrial activities increase, air quality monitoring has become crucial to public health and environmental sustainability. This system aims to provide real-time and predictable analytical data to help alleviate air pollution.
The proposed system uses a network of low-cost sensors distributed to various countries to collect data on pollutants such as PM2, PM10, NO2 and CO2. These sensors transmit data to a central server that processes AI algorithms and analyzes information. Car learning models are trained in historical air quality data to identify models and predict future air quality levels.
In addition, the system includes a friendly user interface that shows real-time air quality indicators and warns users about dangerous conditions. By integrating AI, the system may also suggest useable judgments, such as optimum time for external activities based on projected air quality.
In conclusion, the Air Monitoring System using the AI not only provides precise data in real time but also empowers communities with knowledge to make informed decisions about their health and environment. This innovative approach may contribute significantly to improving air quality management and public awareness.
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Project Source Code
Installation Guide
Data Sets and Samples
Usage Terms
Deployment Guide & More
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