HackStack

Project Info

WattWise

Devpost

This project did not submit a demo video on Devpost.

Inspiration

and

What it does

Paying Utilities is always a mess. The prices are never consistent, and the consumer never really gets a transparent way to decide their own prices, nor have open access to information about it. Producers, especially those who own renewable sources of energy sources of energy such as solar panels, on the other hand tend to have a surplus of energy, which is often times wasted. The one thing in common consumers and producers have is the power grid they're connected to - and we make it possible to have an open market, where the sellers and buyers themselves decide their prices for their own levels of consumption/production.

How we built it

Fetch.ai Agents for each consumer and producer, and the market they are based on. We used ML models with Tensorflow to analyze the market prices to provide the stakeholders with open access to this information that is based on statistical data, and parameters such as Location, Weather, Season, Time, etc. We used Flask and React as the basic tech stack for the user interfaces and application.

Challenges we ran into

We initially started with an idea to create a decentralized blockchain network, which turned out to be out of scope for the time period of the hackathon, with the additional complexity of each Fetch.ai Agent. We were also focused too much on the technical backing of the project that we almost ignored the UI experience, which made it difficult to create a great working demo.

Accomplishments we're proud of

This was a very technically complex idea that we decided to take on. Even though we had to downgrade the technical complexity we initially hoped to build, it's a great proof of concept as an interface that can be built upon heavily in the future.

What we learned

We learnt the real technical nuances that go behind building decentralized systems from scratch.

What's next

We will go onto build the initial idea of the app we had. We will also make use of fetch.ai's AI agents to facilitate the free market exchange of energy, and to potentially make them Autonomous Economic Agents (AEAs). We will further strengthen the models the bidding and exchanges are based upon.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • HTMLIn code
  • JavaScriptIn code
  • PythonIn code
  • ReactIn code
  • FlaskClaimed
  • TensorFlowClaimed

5 of 7 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

60 KB

Source files

25

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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