📅 Day 1: Foundations of Smart Energy & Enron Egg Concept
- Global energy challenges and renewable adoption trends
- Introduction to energy storage technologies and smart grids
- Conceptual overview of the Enron Egg – AI & IoT-enabled compact energy storage
- Basics of IoT integration and AI-driven energy monitoring
🛠️ Hands-on:
- Simulate energy consumption using virtual IoT sensors
- Build a simple energy monitoring dashboard for a microgrid
📅 Day 2: AI & IoT for Energy Optimization
- IoT-enabled real-time energy monitoring and control
- AI-driven predictive load balancing and energy demand forecasting
- Modeling energy storage and renewable integration for optimization
- Strategies to improve energy efficiency in homes and industries
🛠️ Hands-on:
- Create an AI-IoT energy optimization model using Python & Google Colab
- Integrate virtual IoT data to optimize load distribution
📅 Day 3: Prototype Simulation & Future Applications
- Conceptual Enron Egg prototype: modularity, connectivity, and energy efficiency
- Simulate renewable energy integration and load management
- Evaluate environmental impact: carbon reduction and net-zero initiatives
- Career pathways, research opportunities, and entrepreneurial prospects in AI-IoT energy
🛠️ Hands-on:
- Virtual prototype: energy storage with renewable integration
- Case study: optimize energy distribution for efficiency and sustainability
🧰 Tools & Platforms Covered:
- IoT & Simulation: Wokwi (Arduino/Raspberry Pi), Node-RED, Adafruit IO
- AI & Analytics: Python, Google Colab, NumPy, Pandas, Scikit-learn
- Visualization & Dashboards: IoT dashboards, Matplotlib, Plotly
- Resources: Cloud-based simulation environments or local systems
