AirAware - Air Quality Visualizer

AWS LambdaAWS RDSFastAPIPostgreSQLMachine Learning

✦ Project Overview

A cloud-native platform designed to monitor and forecast air quality (AQI) and weather patterns. It features an automated ETL pipeline, time-series forecasting for AQI trends, and anomaly detection for pollution spikes, all served via a FastAPI backend.

✦ Key Features

♥Real-time AQI monitoring and visualization
♥Time-series forecasting for future air quality trends
♥Anomaly detection for sudden pollution spikes
♥Scalable cloud-native architecture on AWS

✦ Methodology

A serverless cloud-native architecture designed for scalability and real-time processing:

01.

Data Ingestion (ETL)

AWS Lambda functions trigger periodically to fetch open API data, cleaning and normalizing it before storing it in RDS PostgreSQL.

02.

Predictive Modeling

An LSTM-based time-series model runs on the historical data to forecast AQI trends for the next 24 hours.

03.

API Layer

FastAPI serves the processed data and predictions to the frontend, ensuring low-latency responses and efficient JSON serialization.