Intersection of all the ground members disciplines: sustainable engineering, machine learning, and computer science.

What it does

The user can ask Google Home about how to properly dispose of different kinds of waste to promote a more eco-friendly household.

How we built it

Since our application consisted of 3 layers (data mining, natural language processing, and hardware integration), we split the work according to those components. We wrote a Python script to mine data and integrated a waste disposal database into the Google Cloud Platform, particularly Dialogflow and Firebase, to work with Google Home's built-in natural language processing system.

Challenges we ran into

Integrating different data formats to create our waste disposal database, i.e. web scraping into .csv files, Google Sheets and Firebase into Dialogflow

Accomplishments that we're proud of

Our ability to work with new tools and concepts, i.e. firsthand experience with Google Cloud Platform, data mining, and integration of natural language processing hardware (Google Home)

What we learned

How to use Dialogflow to facilitate conversations with Google Home, sync Google Sheets with Firebase, explore data mining strategies

What's next for gEco-Home

Expanding on the Visual Intelligence functionality: by implementing visual sensors of waste being thrown away, gEco-Home will be able to properly identify the item and its proper method of disposal, collecting multidimensional data (time, image recognition and frequency) to observe trends in improper waste management

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