An asthma warning ubiquitous service

[[abstract]]A decision support system based on multiplayer perceptron was developed to indicate the possible morbidity of asthma diseases. The inputs of the system included indices of weather and air pollution. The outputs were levels of asthma outpatients. The cross validation assessment method was applied to assess the generalization of the system. In particular, we investigated the accuracy of the result, when medical records were handled using one week mean data. The results showed that the proposed MLP-based decision support system could achieve very high prediction accuracy (>96%). It is promising on indication of ambient air pollutants and weather for asthma patients. Furthermore, we builded a medical web service in this thesis as an application of the Global Positioning System (GPS). For an asthmatic patient, he or she can carry a portable GPS device to prevent possible morbidity of asthma during his or her outdoor activities of daily livings. To reduce possible allergy asthma, the GPS-enable device which sending user’s position continuously consults a remote server to decide whether current ambient air quality will threaten user’s health or not. The server of the detecting system collects real-time data from the network of national air quality monitoring stations. For the response to a remote query, the server makes decision of warning messages according to a proposed asthma neural network model. The proposed system is hopeful for asthmatic patient