Development of an Air Quality Monitoring and Prediction Mobile Application

Many urban residents are exposed to high levels of air pollution, which frequently breach statutory limits, especially during winter months. This exposure poses health risks, particularly for individuals with pre-existing respiratory conditions. Existing awareness tools lack real-time prediction capabilities and user engagement features, limiting their effectiveness in prompting timely protective actions.

A technology company aiming to develop a mobile app to monitor, forecast, and raise awareness about air pollution levels, particularly targeting urban populations concerned with respiratory health.

• Create a user-friendly mobile application that provides real-time air quality information for urban areas.
• Integrate machine learning models to predict near-future air pollution levels, enabling proactive user actions.
• Increase user awareness and health safety by delivering timely alerts based on pollution forecasts.
• Achieve broad accessibility by developing a free-to-use application with lightweight design.
• Enhance user engagement through intuitive UI/UX and personalized notifications.

• Real-time display of pollutant levels such as carbon monoxide, nitrogen dioxide, and particulates.
• ML-based prediction model to forecast air quality indices in user's location over a short-term horizon.
• User alerts and notifications based on pollution levels and predictive insights.
• Lightweight, intuitive UI for quick access to air quality data and forecasts.
• Customization options for user-specific health considerations (e.g., respiratory conditions).
• Mapping and location-based services for localized air pollution data.

• Air quality monitoring stations and APIs providing pollutant level data.
• Weather services for contextual environmental data.
• Push notification systems for real-time alerts.

• Application should load within 2 seconds on standard mobile networks.
• Scalability to support increasing user base without performance degradation.
• Data security and privacy compliance (e.g., GDPR).
• High availability and reliability, aiming for 99.9% uptime.

This project aims to raise public awareness about air pollution, enabling users to take timely protective actions, especially vulnerable populations. It is anticipated to contribute to improved respiratory health outcomes, with the app facilitating early warnings and predictive insights that could lead to a significant reduction in pollution-related health incidents. The solution's predictive capabilities are expected to increase user engagement and trust in air quality data, ultimately improving urban health management strategies.