AI-Driven Predictive Maintenance for Renewable Energy Systems” utilizes artificial intelligence to anticipate and prevent equipment failures in renewable energy installations, enhancing efficiency and reducing downtime for sustainable energy production.

Aim: The aim is to integrate artificial intelligence to predict and mitigate equipment failures in renewable energy systems, thereby optimizing operational efficiency and extending the lifespan of energy-producing assets.

Intended For :

• • Technical Expertise: Participants should have a background in engineering, specifically in renewable energy or maintenance engineering.
  • AI Proficiency: A solid understanding of artificial intelligence and machine learning is required.
  • Industry Professionals: Open to professionals currently working in the renewable energy sector.
  • Academic Researchers: Academics and researchers specializing in renewable energy, AI, or predictive maintenance.
  • Students: Advanced-level students enrolled in engineering, AI, or environmental science programs.
  • System Operators: Individuals who manage or operate energy systems and are looking to enhance their maintenance protocols.
  • Policy Makers: Regulators and policy makers interested in promoting the adoption of advanced technologies in renewable energy.
  • Investors: Venture capitalists and investors looking to support innovations in renewable energy technology.