Enron Egg: AI & IoT-Powered Smart Energy Storage for a Sustainable Future
Learn, Simulate, and Optimize Next-Gen Energy Systems with AI and IoT
About This Course
The Enron Egg is a conceptual next-generation energy storage device designed for smart grids, renewable energy optimization, and sustainable infrastructure. This 3-day workshop offers participants a research-oriented, hands-on experience in AI-powered energy modeling, IoT-based monitoring, and virtual prototyping. Participants will gain insights into future-ready energy technologies, learn how to simulate and optimize energy storage, and explore global applications in homes, industries, and microgrids.
Aim
To equip participants with hands-on knowledge and practical skills in designing, simulating, and optimizing smart energy storage solutions using AI and IoT, with a focus on renewable energy integration and sustainable infrastructure.
Workshop Objectives
- Understand the challenges and solutions in modern energy systems, including renewable integration and smart grids.
- Learn the conceptual design and functionalities of the Enron Egg as a compact, AI-IoT-enabled energy storage solution.
- Develop hands-on skills in AI-driven predictive load balancing and energy optimization using IoT data.
- Simulate energy storage, renewable energy integration, and load management in virtual prototyping environments.
- Explore career and research opportunities in smart energy, AI-IoT systems, and sustainable infrastructure.
Workshop Structure
📅 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
Who Should Enrol?
- Engineers, Researchers, Sustainability Professionals, Students, and Academicians
- Basic understanding of energy systems, IoT, or Python programming is helpful but not mandatory
- No prior exposure to AI-IoT energy devices is required; all foundational concepts will be covered
Important Dates
Registration Ends
June 2, 2026
IST 04: 00 PM
Workshop Dates
June 2, 2026 – June 4, 2026
IST 5:00PM
Workshop Outcomes
- Practical experience with AI-IoT energy modeling and simulations
- Understanding of smart grid integration and renewable energy optimization
- Knowledge to design conceptual energy storage solutions like the Enron Egg
- Ability to analyze energy efficiency, reduce wastage, and simulate sustainable infrastructure
- Global-ready skills for research, industry, or entrepreneurship in the energy and sustainability sector
Fee Structure
Student
₹2499 | $60
Ph.D. Scholar / Researcher
₹3499 | $70
Academician / Faculty
₹4499 | $80
Industry Professional
₹6499 | $100
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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