PowerPulse is an AI + IoT-powered platform that predicts home energy usage, detects consumption spikes, and delivers personalized, context-aware energy-saving recommendations using Google Gemini.
It combines live weather data, simulated IoT sensor input, and predictive analytics to make sustainability intuitive and actionable.
Most households have no real-time awareness of when and how their energy costs spike.
Smart thermostats and dashboards exist, but they:
- Require expensive hardware, and
- Don’t provide personalized insights based on lifestyle, comfort, or behavior.
PowerPulse uses AI to:
- Forecast short-term (12 h) energy usage from weather, home size, and preferences.
- Detect inefficiencies or peak-hour patterns.
- Quantify CO₂ and cost impact of simple actions (e.g., raising thermostat by +2 °F).
- Coach users in natural language — with Gemini generating concise, friendly recommendations.
Key differentiator: behavioral optimization and tight feedback loops (predict → explain → coach) — no hardware required.
- Weather API: Temperature and humidity for the next 12 hours.
- IoT or Simulated Data: Household size, A/C power, thermostat settings.
- User Preferences: Comfort mode (Eco, Budget, Comfort).
- Predicts hourly consumption (
predicted_kwh) vs baseline. - Detects spikes and peak tariff hours.
- Calculates CO₂ and cost savings for each corrective action.
- Generates personalized recommendations using Google Gemini.
- Real-time energy metrics (kWh, $, CO₂).
- Forecast chart for next 12 hours.
- GEMINI CHAT recommendations: short, data-driven nudges.
- Weather widget for contextual awareness.
| Feature | Description |
|---|---|
| 🔮 Energy Forecasting | Predicts hourly consumption using weather trends |
| 🚨 Peak Detection | Flags high-usage or peak-tariff hours |
| 💬 AI Coach (Gemini) | Generates contextual, human-like recommendations |
| 🌡️ Weather-Aware Insights | Integrates real outdoor temperature & humidity |
| ⚙️ IoT-Ready | Works with simulated or real smart device data |
| 💰 Impact Metrics | Quantifies CO₂ and dollar savings per suggestion |
cd backend
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --reload --port 8000cd frontend
npm run dev- Connect with smart thermostats (Nest, Ecobee) for real-world automation.
- Parse utility bills to auto-calibrate baseline and costs.
- Neighborhood leaderboard to gamify sustainable energy habits.
- Share achievements and compare CO₂ savings with local peers.
- Historical trend visualization using PostgreSQL + Grafana.
- Predict weekly or seasonal energy spikes using extended weather data.
- Cut 5–10% of electricity use during peak hours.
- Reduce daily CO₂ emissions by up to 0.5 kg.
- Build awareness and actionable, sustainable habits through AI-driven coaching.
- Translate real data into tangible actions — empowering users to save both money and the planet.