Team Four Frontiers| What Is Our Carbon Footprint?
Awards & Nominations
Team Four Frontiers has received the following awards and nominations. Way to go!
What Is Our Carbon Footprint?
Scrutinise, Gather, Inform: An Interdisciplinary Approach Towards Carbon Emission Scenario
Summary
We have assessed about locating available sources around us and built an application with an approximation model about the quantification of available carbon sources. we converted the footprint relation in financial expense, which will make the task easier for app users. Moreover, we designed a hardware prototype. Which will be planted into inter and intra city vehicles. This device will collect GHG data in ppm and store that into SD card within which we can map an entire country. The user-friendly interface will encourage normal users as well as scientists and regular data users to explore their necessary information from our site and app.
How We Addressed This Challenge
Our goal was to Identify local Carbon sources and to estimate the amount of carbon emission from our locality. In our approach, we developed an application to identify local Carbon emission sources and to calculate personal carbon footprint. We also designed a Hardware prototype to locally quantify the number of greenhouse gases emission throughout the country. This project will help a better understanding of local carbon sources and aid policymakers to take decisions. Using our application anybody can locate a local GHG source around him. And by collecting thousands of data through this remote sensing process we will be able to map the whole country. We aim to raise public awareness by informing people of personal carbon footprints. Our also aim to map the entire country using our application and data collecting hardware device.
Website:https://fourfrontiers.wordpress.com/
How We Developed This Project
This is our planet our home. Our planet is losing its balance. Our negligence towards this planet has left our planet at stake. Every action we do that release carbon leaves a footprint. As the earth's temperature is rising, glaciers are melting, the seawater level is increasing, our environment is losing its balance. But we humans are acting like nothing is happening, everything is normal. We team four frontiers believe that we can make a change or we can help NASA make a change in the reviving mission of our ancestral home.
Go to the application: https://mellow-wine-5265.glideapp.io/
We emphasized on identifying local sources of GHG emission and quantify personal carbon footprint. We believe quantifying personal carbon footprint through our app we can make people aware. As NASA mentioned, local-to-national carbon footprints are much more uncertain on the ground, so we have developed a solution using remote sensing and cloud computing technic.
Coding Language: C/C++(Matlab & Arduino)
Software tools:
- Matlab
- Arduino Software
- Proteus
- Maptionnaire
- Glide App
Hardware tools:
- Arduino
- MQ4 & MQ135
- SD card
- Solar panel
- GPS
We have successfully done the project what we were intended to do. Our application and hardware data collecting device is highly efficient in locating and identifying local sources of GHG emission thus raising public awareness.
But due to COVID 19 pandemic situation, we couldn't build the hardware device. Instead of that, we have built a software design into Proteus.
How We Used Space Agency Data in This Project
Chlorophyll works as a sink for green house gases. With the help of NASA's Worldview data we have analyzed Chlorophyll level. We have also analyzed sentinel-2 landsat data. Landsat Imagery use was another challenge for us as we were completely new to this field.Nevertheless after a good study, we collected imagery data of sentinel-2 landsat from Landlasktool source.Using Snap software we retrieved the spectral band from False color image and calculated NDVI index which can easily be found from pixel info for every latitude,longitude. Lower NDVI pixel stands for comparatively barren land and industrial sites.
Moreover data collecting hardware device will collect data and store that raw data into SD Card. We will extract suitable information for policy makers using NASA open sources API and machine learning model.