Abstract
Motivations● Air pollution is a vital issue the world is facing right now.
● People spend nearly 90% of their time indoors. 20,000 times a day, we inhale and exhale with little thought or effort. Yet, we know very little about what we’re breathing. ● Air quality, especially indoor air quality, significantly affects people’s health, mood, and qualities of life. ● Some people have doubts about the function of their air purifiers. ● A real-time monitor based on sensors can provide detailed information. ● Air purifiers can start working automatically when needed, so that redundant energy will be saved. |
Our Approach
● Hardware:
Atmel board integrated with temperature sensor, VOC sensor and dust sensor. ● Cloud Computing: AWS OpsWorks stack implemented with a Node.js server layer and a MySQL/RDS database layer. ● Experiments: Indoor air quality of a bedroom with two people sleeping at night for one week. Indoor air quality of a kitchen, with variables like cooking bacon, spraying cleaning product and environmental variables like window, kitchen hood and air purifier. ● Data Analysis: Decay functions developed by linear regression of common pollutants. ● Graph Computing: Graphs of original data, moving average and linear regression computed locally. Real-time data displayed by ThingSpeak. |
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