We all came to the National Day of Civic Hacking interested in finding a project that would help reduce water waste.

How it works

We envision two versions of this web app. V1 is a simple analysis of someone's water bill. We provide a breakdown of water usage into categories, using some back-of-the-envelope calculations, data from a user's water bill and some survey data put into a web form. This profile would be saved so that information only needed to be entered once (and updated as needed). Recommendations on reducing water usage are also provided. At some point, these recommendations would be customized to each user. Users can also share their results on Social Media. We will also have a Facebook page/Twitter account to provide tips and remind people to analyze their water bills.

In V2, users need to "opt-in" to a competition, paying a nominal fee (e.g., $5), to enter a pool. Here, users will not only have their water bill analyzed, but also they will compete to reduce their water usage against neighbors. Winners are awarded quarterly. After the first opt-in we will get sponsorships to provide prizes (only from companies that offer water efficiency technologies. Social media presences from V1 would post the winners as well (and the amount they won).

Challenges I ran into

For V1, we had to gather data on water usage and design the calculations for estimating water usage by category. We located a variety of useful data sources, since water usage, especially at the time of hackathon, is a hot topic in California.

In V2, we had tough decisions to determine which people would qualify for the competition (e.g., vacation houses can't count, there must be some minimal level of water usage). We also had to make decisions about what winning means (whether it's absolute usage or percent reduction).

Accomplishments that I'm proud of

We came up with this idea and built it in a little over 24 hours, after beginning the hackathon with another idea that did not work out.

What I learned

The water wasted by various residential categories is higher than we expected in many areas (e.g., toilets).

What's next for Banking Blue

  • Adding user accounts and historical data for users to round out V1.
  • Increasing the characteristics that users can submit in their profile and incorporating those characteristics into calculations. For example, high efficiency appliances both input and as a output recommended to users who don't currently have any.

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