AIR POLLUTION PREDICTION SYSTEM FOR SMART CITY

Smarter cities through prognostic understanding for unpolluted air!

The Air Pollution Prediction System for Smart Cities is an industry-first solution aimed at improving urban life by offering current and future data on air quality. This system uses a range of modern machine learning signal processing techniques and large datasets concerning the environment to forecast air pollution levels based on traffic intensity, emissions in industrial facilities, and weather conditions for different areas of the city. Using data collected from IoT sensors as well as satellite images and trends, the system educates city planners, environmental departments and the population to make the right decisions that will lead to the improvement of people’s health. These predictive measures are used in alerting and managing traffic flow that in turn minimizes the population’s exposure to the toxic pollutants.

Furthermore, the Air Pollution Prediction System constantly presents the user with an easy to understand front end that displays trends of air quality and pollution predictions. A observer can get real-time information, past data, and models to gain a complete appreciation of changes in air quality in their city. This clearly arranged interface promotes user participation in the monitoring of local air conditions and participation in campaigns to minimize pollution. Incorporating such a sophisticated predictive tool to the planning of cities will increase helpfulness to sustainability, health and overall quality of life for the future generations. The Air Pollution Prediction System is the effective way to develop urban planning, as well as enhance the quality of life for everyone.