Pollution particles are found all around us, from direct sources, such as construction sites to chemicals emitted from industries and automobiles. Particle pollution is composed of solid particles large enough to be seen with the naked eye, such as dust and smoke, found in the air, and smaller particles that can be made up of hundreds of different chemicals. Small particles pose the greatest health problems because they can get deep into your lungs and bloodstream. Most people are aware of the negative health and environmental effects that result from air pollutions but they do not know how much pollution is actually around them and how much of these pollution particles they are breathing in daily.
"As a team, coding the various functions for our project was complicated but inspired us to move forward and promote our team cohesion. All we ask of you is .........How many Particle Pollutants are you Breathing In?
Our solution is to create a device that would be able to detect the levels of dust emitted from chemicals, construction sites, unpaved roads, fields, smokestacks, and reactions of chemicals in the air and alert the user. It alerts users through a mobile app that shows the level of dust, facts about pollution and an informative graph. When people are informed of what is in the air they are breathing everyday it can help them avoid certain areas of high pollution and be more aware of what they are breathing.
The visual presentation of our device, Eco Aer, was built using an Arduino Uno and a PM sensor wired to a breadboard with 3 LED bulbs that act as our indicator of the presence of dust. We chose to use an Arduino because it is simple microcontroller that is easy to use. Our visual presentation is created with the combination of the Arduino software and Processing . We chose to code in Processing because we know that the Arduino software is very "friendly" to Processing. When the indicator detects dust , it gives a percentage of the amount of dust in the air. Based on this percentage a graph is made. An increase of the graph indicates that there is more dust. A decrease indicates less dust.
Our mobile air pollution sensor and mobile app is still in development. In its completed stage our mobile air pollution sensor will be in the shape of a watch and be an additional feature to FitBIt. The mobile device will have built in particle pollution sensors that detect the percentage of dust in the air. When the percentage of dust is above 35%, indicating a high amount of dust, the device will alert the user playing a sad song and display the color red. When the percentage of dust is below 15%, indicating a low amount of dust, the device will alert the user by playing a happy song and display the color green. When the percentage is between 15% and 35%, indicating a moderate amount of dust, the device will alert the user. The device will also have built in sensors that detect other airborne pollutants such as carbon monoxide, sulfur oxides, nitrogen oxides, and lead.
Organization: Girls Who Code
Student: Neziah Whitson
Project Team Members: Neziah Whitson, Kelly Haung, Carmen Kwong, Militsa Zaklan
Type of Work: App
Location: Bay Area - Moody's
Grade: 11th Grade
Year Created: 2015
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