Lestaree

From Renewable to Responsible, Lestaree it!

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Inspiration

Many nations still rely significantly on energy imports to meet their domestic needs in the connected world of today. This dependency, however, poses a serious risk since, in times of global crisis, such as pandemics, geopolitical conflicts, or supply chain interruptions, a domino effect may occur in which energy shortages in one area lead to economic and social instability in other areas. Many countries have consider to made their own energy self-sufficiency a strategic imperative in recognition of this risk.

This application is inspired by the urgent need to support countries in achieving long-term energy independence. By leveraging data-driven insights and predictive analytics, the app aims to assist policymakers, researchers, and energy planners in identifying domestic energy potential, optimizing resource allocation, and formulating sustainable energy strategies. Ultimately, the goal is to empower nations to reduce their reliance on external energy sources and build resilient, self-sufficient energy systems for the future.

What it does

  • Maps solar, wind, and hydro energy potential across Indonesia
  • Predicts energy output and forecasts environmental waste footprints
  • Visualizes insights through interactive dashboards
  • Guides decision-makers with a built-in AI chatbot that provides:
    • Tailored waste reduction strategies
    • Site-specific suggestions
    • Policy-aligned recommendations

How we built it

Frontend: Three.js, Next.js, Tailwind

Backend: PostgreSQL, Supabase

ML Model: Numpy, Pandas, Scikit-learn, XGBoost, Matplotlib

This system uses trained ML models on public datasets to forecast environmental conditions and predict energy output based on real-time data from selected areas. A Next.js frontend displays the results, while a Gemini API-powered chatbot enhances the experience by summarizing forecasts and offering sustainability tips, such as waste management and energy-saving suggestions. Together, this creates a smart, interactive energy management solution.

Challenges we ran into

  • Lack of sleep
  • Lack of datasets and open sources

Accomplishments that we're proud of

Finished the project on time.

What we learned

  • Integrate LLM API & fine tune models to increase web usability
  • Handle time-series data
  • Use interactive 3D models to build website

What's next for Lestaree

  • Integrating with real-time data by incorporating live streams of environmental data.
  • Empower IoT usage as the input stream of Lestaree.
  • Improving scope of renewable energy resources (Biomass, Geothermal, etc)

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