Air Quality Visualizer and Forecast App
Developing an Algorithm for Air Quality Visualizer and Forecast App to generate granular, real-time, and predictive air quality information. This project builds a system that monitors current air pollution and predicts future air quality using AI/ML.
The Air Quality Visualizer and Forecast App is an AI-powered system designed to monitor, visualize, and predict air pollution levels in real time. Air pollution is a major environmental and health concern, especially in rapidly growing urban and semi-urban areas where monitoring infrastructure is limited. This project aims to provide granular and accessible air quality information to help people understand current pollution conditions and make informed decisions.
The system collects air quality and weather data from available datasets or APIs and processes it using machine learning techniques to predict future Air Quality Index (AQI) levels. By analyzing parameters such as particulate matter (PM2.5, PM10), temperature, humidity, and wind speed, the model can forecast pollution trends for the next few hours or days.
A user-friendly web dashboard visualizes the data through interactive maps, graphs, and alerts. Users can view real-time air quality levels in different locations and see predictions of upcoming pollution levels. The platform also provides health advisories and notifications when air quality becomes unhealthy.
This project is particularly useful for smaller cities or rural areas where air monitoring stations are limited. By combining data analysis, AI-based prediction, and visualization tools, the system helps create awareness about environmental conditions and supports better public health and environmental management.