  Asthma is a chronic disease of the airways of the lungs. It results in
inflammation and narrowing of the respiratory passages, which prevents air flow
into the airways and leads to frequent bouts of shortness of breath with
wheezing accompanied by coughing and phlegm after exposure to inhalation of
substances that provoke allergic reactions or irritation of the respiratory
system. Data mining in healthcare system is very important in diagnosing and
understanding data, so data mining aims to solve basic problems in diagnosing
diseases due to the complexity of diagnosing asthma. Predicting chemicals in
the atmosphere is very important and one of the most difficult problems since
the last century. In this paper, the impact of chemicals on asthma patient will
be presented and discussed. Sensor system called MQ5 will be used to examine
the smoke and nitrogen content in the atmosphere. MQ5 will be inserted in a
wristwatch that checks the smoke and nitrogen content in the patients place,
the system shall issue a warning alarm if this gas affects the person with
asthma. It will be based on the Artificial Neural Networks (ANN) algorithm that
has been built using data that containing a set of chemicals such as carbon
monoxide, NMHC (GT) acid gas, C6H6 (GT) Gasoline, NOx (GT) Nitrogen Oxide, and
NO2 (GT) Nitrogen Dioxide. The temperature and humidity will be also used as
they can negatively affect asthma patient. Finally, the rating model was
evaluated and achieved 99.58% classification accuracy.
