Personalization Exercise of PM2.5 Inhalation Prediction Model and Platform Deployment

• Main Authors: CHANG, YU-HSIANG, 張佑祥
• Other Authors: CHANG, YUE-SHAN
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/fh94rq

碩士 === 國立臺北大學 === 資訊工程學系 === 105 === In recent years, air quality and the environmental quality are getting more and more concern in public, many people are pay attention to the air quality of their surroundings. As one of air pollution PM2.5 will be affected to human body directly, it was invisible to the naked eye. According to many epidemiological studies have demonstrated the health hazards of PM2.5, including early death, bronchitis, asthma, cardiovascular disease, lung cancer, and etc. According to the Ministry of Education Sports Department of the 104 year exercise survey report, the people have to do exercise is about 83%, which the largest proportion is outdoor sports. The top three are walking 42.4%; jogging 27.8%; basketball 12.7% and other outdoor sports, we focus on PM2.5 inhalation and retention after exercise. The goal of this study was to establish a system to predict PM2.5 inhalation and retention during exercise. We used questionnaires to collect user awareness of PM2.5 in the exercise field and use Bruce Protocol to determine heart rate and ventilation. And then use the exponential regression to establish the ventilation model used to predict PM2.5 inhalation and retention, and the design an APP allows the user to know the PM2.5 inhalation after the exercise and retention to reach the warning effect.