Considering the increase in time we spend indoors and the appearance of the new Coronavirus, the quality of our indoor air is now more important than ever. Unfortunately, we are not constantly aware of what is roaming in our air as it is not visible to the naked eye. MillionAIR aims to eradicate this issue by improving our air quality monitoring devices. Even though many of these air quality and air pollution sensors already exist, we wanted to combine the new found knowledge of Artificial intelligence with these devices to further advance our identification of these particles. This is by attaching cameras and microscope lenses to identify the particles and microorganisms in the air. It will do so by taking images and allowing artificial intelligence to identify them with the data cache calibrated/logged on the device with previously stored specifications of common particles and microorganisms. This will allow us to place purifying devices for more specific targets. Therefore, aiding in the purification process of the air supply.
According to the WHO, household air pollution kills 4 million people a year. The lack of fresh air due to prolonged quarantine at home is putting people suffering from diseases affected by bad air quality and pollution at a higher risk of developing exacerbations of their diseases. We were inspired to choose this challenge by our wanting to help everyone stay aware of their environment and what harmful particles they could potentially be breathing using a smart, high quality air monitoring system. Personally, as one of our members suffers from asthma this is something that directly affects her as an individual. This project will help identify what triggers the attacks and asthamtic symptoms. It will aim to make her life and the lives of others similarly affected easier especially during the COVID-19 lockdown with limited access to fresh air.
Our approach towards developing our project started at researching and reading through multiple NASA resources that displayed air quality data. We began by exploring the already existing air quality/pollution monitors, sensors etc. We initially wanted to create a mechanism similar to BAM1020 on our own however after careful research we learnt that BAM1020 is an already existing device. Therefore, we focused on advancing it as we always knew that we wanted to include Artificial intelligence to make our monitoring a smarter process. We’re working to mirror what NASA is currently working on which is advancing and improving their spaceships. Their developed systems “test technologies to monitor aerosols in spacecraft.” similar to what we are trying to achieve on earth. Components of our project are the BAM1020 and the raspberry pi, a microscope lens with a magnification ranging from 900x to 1200x, Raspberry Pi high quality camera, and the integration of machine learning using TensorFlow.
https://docs.google.com/presentation/d/1_vt-tGrruR5th7tuwUnGAePOLQDBOKcGZBsj73kTqP8/edit?usp=sharing
https://earthdata.nasa.gov/earth-observation-data/near-real-time/hazards-and-disasters/air-quality
https://earthdata.nasa.gov/learn/pathfinders/health-and-air-quality-data-pathfinder
https://www.epa.gov/outdoor-air-quality-data/air-data-basic-information
https://www.nasa.gov/mission_pages/station/research/long_duration_sorbent_testbed
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https://www.nasa.gov/content/life-support-systems
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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6062327/
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https://www.dec.ny.gov/chemical/8539.html
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https://www.dec.ny.gov/chemical/8539.html
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https://earthobservatory.nasa.gov/features/Aerosols
https://www.careforair.eu/en/what-principled-do-the-air-quality-sensors-work-on/
https://data.sa.gov.au/data/dataset/adelaide-cbd-air-quality-monitoring-station-particle
https://earthobservatory.nasa.gov/images/146596/airborne-particle-levels-plummet-in-northern-india
https://earthdata.nasa.gov/learn/pathfinders/covid-19