A Software System For Data Integration And Decision Support For Evaluation Of Air Pollution Health Impact

In this paper we present a software system for decision support (DSS - Decision Support System) aimed at forecasting high demand of admission on health care structures due to environmental pollution. The algorithmic kernel of the system is based on machine learning, the software architecture is such that both persistent and sensor data are integrated through a data integration infrastructure. Given the actual concentration of different pollutants, measured by a network of sensors, the DSS allows forecasting the demand of hospital admissions for acute diseases in the next 1 to 6 days. We tested our system on cardiovascular and respiratory diseases in the area of Milan.