Inspiration

The health impacts of poor air quality are not equally shared, as many studies have shown there is disproportionate impact of air pollution based on socioeconomic and environmental factors. However, air quality is only measured at a regional level, making it impossible to identify local areas of pollution and address them. SkyBox aims to address this by gathering air quality data at a mile-by-mile level, providing a tool for researchers to generate custom static maps and also a platform for the public to view air quality data in their area.

What it does

SkyBox uses a P2.5 Dust Sensor and an Air Quality Sensor to measure, record, and transmit accurate data of the levels of particulate matter and various gasses in the immediate air to map out the air quality of local areas. This data is mapped with GPS location and used to generate an overlay on an interactive map that one can use to analyze air quality on a local scale just by checking a website.

How we built it

The SkyBox hardware is built on a custom-designed 3D-printed chassis that holds an Arduino Uno wired up to a P2.5 Dust Sensor and an Air Quality Sensor. The chassis was designed in Fusion 360 and can be mounted to anything from busses, to delivery vans, to drones.

The SkyBox software is a combination of Arduino and Python scripts. The Arduino code interfaces with the SkyBox to record sensor data and send it over the serial port, where it is parsed with a Python script that writes the data to a csv file and then uses the Maps API to generate the Air Quality Map. The same data is used to create the interactive public Air Quality Map as well.

Challenges we ran into

Initially, we intended to demo the SkyBox by mounting it on a drone and flying it around at various locations and altitude to collect data. We worked towards this vision by 3D printing a prototype package and testing if the drone could carry this load. Although the combined weight of the electronics and the chassis of the Skybox was only ~200 grams, our particular drone wasn’t able to lift off. Armed with the knowledge that there are indeed drones that could lift the weight of this load, we pivoted to optimizing the final SkyBox for mounting on a car to collect data. This allowed us to record and transmit our air quality data at ground level.

The Arduino GPS Module that we purchased for this project wasn’t functional after much troubleshooting. The air quality data needed location data to indicate the location of the sample, so we decided to seek an alternate solution.

We had to learn how to use serial port communication to receive sensor data and then picked up certain data parsing techniques to make the data easy to use for our map generation.

Never used Google Maps API so had to get acquainted.

Accomplishments that we're proud of

  • 3D modeling a chassis that could hold all the electronics in a safe, compact, and stable manner
  • Being able to submit a hackathon project as freshmen with a team of only two people
  • Generating accurate visualizations of our local air quality
  • Sleeping more than 3 hours

What we learned

  • Cheap drones meant for flying shouldn’t be expected to carry payloads, so test that before spending lots of time with the assumption that it can
  • 3D Printers take a long time to print (sad)
  • Hardware-Software projects with two people is kind of hard

What's next for SkyBlock

  • We intend on featuring a GPS module so the SkyBox doesn’t require additional hardware to determine location data.
  • We hope to test with a higher payload drone to validate our concept of gathering air quality using the future infrastructure of delivery drones.
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