Right now about 334 million people across the globe are suffering from asthma. People with asthma are sensitive to things which may not bother normal people at all. For example they may feel uncomfortable with increased levels of smoke, pollen or fog in air. The number of people suffering from asthma has been rising sharply over the years, pollution being one of the biggest reasons. Though controlling pollution is a broad topic, but preventing oneself from asthma is an easier way out. It is important to keep track of what triggers asthma attack in a patient, because symptoms do not occur right after the exposure to the triggering parameters. The delay in attack occurs depending on how much the person is sensitive to the factor. Thus we try to propose a model of a smart asthma prediction system using Internet of Things.