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Smart Agrivoltaic Systems

AI for Smart Agrivoltaic Systems

Original price was: USD $99.00.Current price is: USD $59.00.

Optimizing crop yield, water usage, and energy production.

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About This Course

This 3-day, hands-on course introduces the exciting world of AI applications in agrivoltaics, where crop production and solar energy work together. Participants will explore how AI can optimize land use, crop yields, irrigation, and energy generation using digital twins, predictive analytics, and decision-support tools. By the end of the course, you’ll have the practical skills to design and manage sustainable food–energy–water systems that integrate agriculture, renewable energy, and smart technologies.

Aim

The aim of this course is to provide participants with the knowledge and tools to apply AI to agrivoltaic systems, focusing on optimizing crop yields, improving water efficiency, and enhancing solar energy generation. Through hands-on modeling, digital twins, and decision-support tools, participants will learn how to design sustainable food–energy–water systems for the future of agriculture and renewable energy.

Course Structure

📅 Module 1 – Foundations of Agrivoltaics & AI-Driven Precision

  • Welcome & Course Orientation: Get an introduction to the synergy between agriculture and solar energy through AI-driven design.
  • Agrivoltaics Overview: Understand the concept of dual land-use for food, water, and energy, exploring the environmental and socio-economic benefits, microclimate, and water management.
  • Crop Selection & Microclimate Dynamics: Learn about shade-tolerant crops, panel orientation, height, and spacing, and how these factors impact both crop yield and energy generation.
  • Basic AI & Data Wrangling: Discover the data sources used in agrivoltaics, including sensors, imagery, and yield records, and learn how AI plays a role in site assessment and design.
  • Hands-On: Access and explore solar cell data from open databases (e.g., NREL, Perovskite Database).

📅 Module 2 – AI Modeling & Systems Optimization

  • Advanced Agrivoltaic Design & Digital Twin Modeling: Explore AI-enhanced simulation and digital twin modeling for agrivoltaic systems, analyzing performance under varying environmental conditions.
  • AI for Water Optimization & Microclimate Control: Learn how AI can optimize irrigation scheduling, monitor evapotranspiration, and apply reinforcement learning for efficient water use.
  • Real-Time Monitoring & Predictive Analytics: Understand how smart sensors, IoT, and machine learning work together to predict crop yield and optimize system performance.

📅 Module 3 – Integrated Decision Support, Policy & Future Innovations

  • Multi-Criteria Decision Support: Use AI tools to optimize crop yield, water use, energy generation, and economics, making data-driven decisions.
  • Economic & Policy Frameworks: Understand the economic and policy aspects of agrivoltaic projects, including cost-benefit analysis, financing, regulations, and land-use mechanisms.
  • Case Studies & Global Perspectives: Explore examples from the U.S., India, Japan, Europe, and pilot farms to see how agrivoltaics is being applied around the world.
  • Looking Ahead: Discuss the future of agrivoltaics with innovations such as spectral-selective panels, vertical farming, and AI-guided adaptive shading.

Course Outcomes

  • Understand Agrivoltaic Principles: Learn how AI can optimize crop–energy–water systems in agrivoltaic applications.
  • Apply AI Models & Digital Twins: Gain hands-on experience using AI and digital twins for yield enhancement, irrigation optimization, and energy generation.
  • Use Smart Sensors & IoT for Monitoring: Understand how to use real-time data to support decision-making and optimize agrivoltaic systems.
  • Evaluate Economic, Technical & Policy Aspects: Learn how to assess the costs, benefits, and regulatory frameworks for agrivoltaic projects.
  • Design Sustainable Systems: Develop strategies for integrating food, energy, and water in a sustainable and adaptive way using AI.

Who Should Enrol?

  • PhD Scholars & Researchers: In agriculture, renewable energy, and AI.
  • Academicians & Faculty: Working on sustainable farming and energy systems.
  • Industry Professionals: In solar energy, precision agriculture, and smart farming technologies.
  • Students: Interested in agrivoltaics, AI applications, and sustainable food–energy–water systems.

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Certification

  • Upon successful completion of the workshop, participants will be awarded a Certificate of Completion, validating their skills and knowledge in advanced AI ethics and regulatory frameworks. This certification can be added to your LinkedIn profile or shared with employers to demonstrate your commitment to ethical AI practices.

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