EcoSense

Inspiration

EcoSense was a response to the growing frustration people feel with how confusing and overwhelming recycling and sustainability can be in everyday life. While people are aware of the worsening state of our home, it’s more difficult to be aware of what can be recycled, how their actions impact the planet, or where to even start. The new generations especially feel the pressure of solving problems they didn’t create, like climate change and pollution. EcoSense is designed to alleviate some of this stress through its simple, scan-based system that instantly provides clear, actionable insights on recycling, greatly contributing to the lives of everyday users.

What it does

Ecosense is an easy to use app which allows users to take a photo of an object to understand the recyclability of the material. Additionally, users can gain knowledge on how to recycle the material in question, and what impact their contribution can make. Through the information it provides, the app aims to influence more people into using renewable materials and saving the environment.

How we built it

We divided up the project into two parts: frontend and backend. This aided in dividing up our responsibility and increased our ability to work more efficiently. The team responsible for the frontend worked on the user interface of our application, creating a sophisticated look and while still ensuring the interface is user-friendly. The team responsible for the backend worked on flask servers and databases using MongoDB. The backend was essential for effectively responding to scans. When an object was being scanned, the application sends this data to the backend, which sends it to a trained machine learning model, which sends information about the identity of the object, its recyclability, and carbon footprint to the database, which is then delivered back to the front end, where it can be utilized by the user. We used MongoDB not only to store scanned product data, but also to save history logs so that users can revisit past searches. Our coding took place on Xcode.

Challenges we ran into

One of the earliest technical challenges we faced while developing EcoSense was getting the camera functionality to work properly. This was a task that turned out to be more time-consuming than expected due to the complexities of configuring the info.plist file in Xcode. Although capturing images is a fundamental part of the application, explicit permission declarations for privacy-sensitive resources like the camera are required. Any seemingly minor error prevented the application from accessing the camera, which stalled our testing and development.

Accomplishments that we're proud of

With the competition of this project, we hope that more people are more likely to recycle as they will not have to run into the problem of finding out which items are recyclable and not, since this is usually the major issue associated with recycling as some people feel that it may be too much of a hassle or even too overbearing, but with this app, it would make it ever so easier to do so. One thing we are happy to be able to add on was the search feature as with this, you can even look to see if you have scanned this item before, and it was something we weren't sure of adding as we initially thought it would be best to leave it as it is and not run into any other mishaps, which we did run along into when integrating that feature, but we were able to quickly fix it, and we are happy that we included it.

What we learned

How much plastic hurts humans and yet, people continue to ignore the benefits of recycling since many find it too confusing. We are always made aware of how much it contributes to global warming along with poisoning the waters with microplastics, and how the story of the island of trash was made well known with no action taken by individuals to reduce its effects. We know how other creatures such as turtles were affected by this epidemic, yet we don't seem to fear how we are also creatures who could be harmed by these microplastics, and how many undeveloped lands already are worried of water pollution and microplastics being mixed into their waterways. We learned how to work more as a group as each of us had their own respective code and it was harder to translate the task we wanted to each other as the code language varied between us and each part of the app, but we were able to simply give a bareboned explanation which we later worked up into our desire state in order to use it within our app.

What's next for EcoSense

Ecosense uses a basic machine learning model which is trained in object detection, and while its detections works with common materials like plastic, it might run into a few errors with unusual materials. We aim to fill this gap in the near future, by training our model more precisely. Additionally, while EcoSense currently provides users with useful information on recycling, we plan on expanding its reach and impact on users by incorporating additional information on carbon footprint, sustainability, ways to recycle scanned material, and impact on animal depopulation.