📅 Module 1 – Urban Solar Potential Assessment Using AI and Geospatial Data

• Welcome Address & Overview: Introduce the theme, objectives, and outcomes of the course.
• Urban Energy Systems & Distributed PV: Explore the evolution of urban solar systems and the importance of rooftop and façade PV in achieving carbon-neutral cities.
• AI-Powered Rooftop & Façade Detection: Learn about deep learning models like DeepLabv3+ and CNNs for detecting solar potential on rooftops and facades.
• Geospatial Techniques for Solar Mapping: Understand how to integrate high-resolution satellite, LiDAR, and drone imagery for solar potential mapping.
• Tools for Irradiance Estimation: Learn how to extract solar-accessible surfaces and estimate solar irradiance using open-source platforms and datasets.

📅 Module 2 – AI Modeling, Digital Twins & Solar Simulation in Urban Environments

• Spatial Digital Twins for Solar Planning: Learn how to build interactive urban energy models to simulate PV deployment across cities.
• AI & GIS Integration: Integrate AI models with city-wide GIS databases for city-level solar energy planning.
• Generative & Predictive Modeling for Solar Performance: Understand how generative models like SolarGANs can predict façade irradiance, and how deep learning can forecast solar yield and shading.
• Urban Density & Solar Access Optimization: Explore how urban density and morphology influence solar access, and learn AI-based methods to optimize solar capture in high-density environments.

📅 Module 3 – AI-Driven Decision Support, Urban Energy Strategy & Policy Integration

• Multi-Criteria Optimization in PV Deployment: Learn how AI-based decision-support systems can help urban planners and architects balance technical, economic, spatial, and aesthetic constraints in solar PV deployment.
• Economic & Regulatory Considerations: Understand the financial aspects of solar energy, including PV payback, amortization, and cost-benefit modeling.
• Policy Mechanisms for Solar Integration: Discover the role of policy in incentivizing façade-integrated solar and other energy-positive initiatives.
• Global Case Studies & Implementation Frameworks: Study successful global implementations of solar energy in urban environments and how they were shaped by interdisciplinary collaboration.
• Shaping the Future of Urban Solar Design: Reflect on the future of urban solar design and its integration with smart cities and energy-positive initiatives.

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.