Asthma is a chronic, often devastating, condition that has no cure and causes a remarkable economic burden to the associated family as well as to the government and state. But it can be controlled and managed with personal diagnostic of triggering factors of asthma and through preventive care. Sometimes it is as simple as avoiding air pollutants like dust, tobacco smoke etc. Asthma attack triggered from air pollution could easily be avoided if there is a way to monitor air pollution level continuously in the surroundings. In this paper, we have presented a system that will be able to predict possible asthma attack for individuals and alert them. The system is developed using an air pollutant monitoring device combined with an Android application. Using supervised learning technique and analyzing (frequently taken) air pollutant data, the system will help to reduce asthma attacks for asthma patients. Also analyzing personalized data of individuals it will be possible to recommend a new user about the safe and unsafe zone of the city. As a by-product, it will be possible to create a high-density air pollution map of cities to monitor air pollution