Energy Efficient Household Rewiring
Appliance Lookup
This is a mockup for demonstration purposes only and does not yet contain any real data.
Project Description
In the next few decades, we’ll replace 1 billion household machines and appliances, and it's critical for the climate that we replace them with clean electric versions instead of the fossil fuel-based appliances of the past. To help consumers choose and compare these machines, take advantage of tax incentives, and assist contractors in finding the right fit, we need a centralized platform.
During the Spring 2024 semester, our team of four is diligently working on this project as part of the Computing for Good course at Georgia Tech. We are collaborating closely with Rewiring America to develop this essential tool.
Project Goals
Create a database and API for household electric appliances such as furnaces, heat pumps, and water heaters, and use it to build a consumer-facing web app.
Tasks:
- Collect nomenclatures: the organizational structure of appliance model numbers and what they represent.
- Determine how to represent it in a database.
- Create a parser that searches the database for matches.
- Construct a front-end that takes applicance model numbers, finds matches, and unpacks it for a user.
Team Members
Dan Turcza
Backend Development
Along with Kevin, Dan will focus on the data discovery workstream, which focuses on where appliance data sources are located. The goal is to have a comprehensive understanding of all makes/models of target appliances, validated by other aggregators in the space. Along with Chris, Dan will also focus on the data processing workstream, which is concerned with turning those data sources into usable data that fits our schemas. This will involve ingesting web resources and processing them to extract the data we care about. Dan is also the team liaison with Rewiring America since he has a preexisting relationship with them.
Kevin Ferri
Backend Development
Along with Dan, Kevin will focus on the data discovery workstream, which focuses on where appliance data sources are located. The goal is to have a comprehensive understanding of all makes/models of target appliances, validated by other aggregators in the space. Along with Ricky, Kevin will work on frontend dev and the UX to build a compelling and accessible web application that users can use to explore the data that we've collected. A stretch goal for this workstream is integration with other datasources such as financial incentives in order to allow for more complex applications.
Ricky Cheah
Front-End Development
Along with Kevin, Ricky will work on frontend dev and the UX to build a compelling and accessible web application that users can use to explore the data that we've collected. A stretch goal for this workstream is integration with other datasources such as financial incentives in order to allow for more complex applications. Ricky is also the main author of this website.
Chris Yang
Backend Development
Along with Dan, Chris will focus on the data processing workstream, which is concerned with turning those data sources into usable data that fits our schemas. This will involve ingesting web resources and processing them to extract the data we care about. Chris will also be the primary database developer, concerned with creating a viable database and serving API so that clients can make use of the data that we've collected.
Team Weekly Updates
Dan
Highlights: Midterm presentation slides and delivery. Some follow-ups to schema PR. Putting together demo presentation
Challenges: Too much presentation and not enough coding 😊 (plus travel). Also, the fact that we have a monorepo without monorepo tooling is starting to hurt a bit. Mobile experience with the new tabulator table is not great - the table gets cut off to the right and is hard to scroll.
Next Steps: Need to tweak the pipeline to separate LLM table normalization and column name mapping stages, since the latter should go as late as. Then need to start running more appliances
Kevin
Highlights: Read through peer reviews and summarized to the team in Slack. Added more coverage for heat pumps in the URL metadata file, and tackled a large part of the water heaters.
Challenges: Repeated model numbers across different manufacturers means that searching spec sheets can bring up only the same model from a different manufacturer that has better online visibility.
Next Steps: Continue increasing coverage for largest manufacturers first and begin collecting spec sheets for dryers. Take a breath-first approach to coverage across appliances.
Ricky
Highlights: Pushed new table format, updated columns, updated some input forms.
Challenges: Tried to implement selection feature on tabulator to improve UX but couldn’t find enough information online. Lacks freedom using tabulator for react.
Next Steps: Adjust table for mobile viewing, incorporate new API results into frontend.
Chris
Highlights: Finalised and integrated backend API to return data to front-end requests + researched on integrating database such as Postgres with Vercel.
Challenges: Vercel only permits vercel-compliant database and will lock down the project in the Vercel eco-system. This makes it hard for the partner to move out of Vercel later on.
Next Steps: Add versioning in the backend API. Instead of integrating Vercel Postgres into the backend for querying, create a db store with loading data from a raw json store alongside with the project.
P6 Demo Video
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P4 Presentation Slides
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Lighthouse Scores
