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Title slide for our video
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What users see when visiting the web app, in landscape orientation
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A data point from our web app showing the CO2 concentration
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Pressing on any of the blue markers provides date, time, location, and CO2 concentration data
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Pinging the server using iNetTools on a 4G Verizon iPhone
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Some of the text below the map on the web app
Inspiration
One sure way to incentivize helping with climate change is to build a market on the real-time monitoring of carbon removal. Essentially this is the live trading of carbon credits. Well, we can’t have someone buying a carbon credit that’s significantly inaccurate because a carbon removal machine ran tens of milliseconds too long and removed grams, kilograms, or even tonnes more than the credit was for. That led to the idea for this project.
What it does
The project is in two parts - CO2 data collection through IoT and an output of the CO2 results to a web dashboard using AWS Wavelength. Pressing the blue markers yields date, time, location, and CO2 concentration data. Our goal was to get data into the platform, then make it accessible for further apps to build off the data in AWS.
How we built it
Collection - Sensirion SCD40 CO2 sensor with Adafruit Bluefruit LE Feather M0 connected via Bluetooth to an old Android phone acting as a gateway to AWS IoT Core.
Output - To simulate lots of data coming in from multiple carbon removal devices at multiple times, in addition to the IoT Core data,we have an EventBridge-triggered AWS Lambda function that outputs trend data to DynamoDB for many locations every 2 seconds. DynamoDB was chosen as our application’s data store for its ultra-fast read and write speeds.
From there, we launched an instance in the Denver Wavelength zone with our web application. Pinging it from a 4G Verizon iPhone in Denver within the zone yielded 20-30 ms latencies compared to the same phone outside the zone in Wichita, KS, which was about 80-120 ms. Yes, I drove there from Denver, actually for my father-in-law’s 100th birthday party which happened to coincide nicely with this test.
Challenges we ran into
We were anticipating more team members but in the end it was just me. So there was a time crunch, but it was fun to complete nonetheless.
Accomplishments that we're proud of
Our work borrowed from open source as mentioned in the following repositories. These are our contributions back to open source, under a MIT license so anyone can freely build upon this work.
The IoT app for Android phones:
The web app (visible on a Verizon phone in the Denver AWS Wavelength zone):
What we learned
If a 4G phone can transact this quickly, a 5G phone would be blazing fast through Wavelength, giving us the accuracies needed for the carbon removal marketplace we envision.
What's next for Carbon Removal Monitoring
We plan to continue building out the platform - maybe we can discuss further with folks at AWS on how to best continue our implementation.
Built With
- adafruit
- amazon-web-services
- arduino
- dynamodb
- ec2
- iam
- iot
- iot-core
- java
- javascript
- lambda
- node.js
- python
- sensirion
- vue
- wavelength
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