AI-Integrated IoT Solution for Enhanced Indoor Air Quality Management

This project implements a smart indoor air quality monitoring system using an advanced air quality sensor. The system measures volatile organic compounds (VOCs) and environmental parameters, ensuring a comprehensive understanding of indoor air conditions. By integrating with an IoT platform, it provides real-time data collection, remote access, and cloud-based storage, making it suitable for smart homes, offices, and healthcare facilities.

AI algorithms analyze VOC levels and environmental trends, detecting anomalies and predicting air quality changes. Alerts are generated for unhealthy air quality levels, enabling proactive interventions. A user-friendly mobile app provides live air quality monitoring, historical data visualization, and personalized recommendations for maintaining healthier indoor environments.

Key Features:

• Accurate monitoring of indoor air quality focusing on VOC levels.
• IoT-based real-time data transmission and cloud storage.
• AI-enhanced analysis for anomaly detection and air quality predictions.
• Mobile app for live tracking, alerts, and actionable insights for better air quality management.

This project includes source code, complete hardware setup, detailed analysis, and a 200-page project report in soft copy, making it an ideal choice for students exploring IoT and AI applications in smart and healthy living.