The adoption of AI-driven condition monitoring for asset health prediction is revolutionizing industries by enabling predictive maintenance and reducing unexpected downtime. However, in the Middle East, unique regional challenges complicate the deployment and effectiveness of these systems. This paper discusses key risks and challenges specific to the Middle Eastern context, such as extreme environmental conditions, data integration hurdles, cybersecurity vulnerabilities, and skill gaps in AI and data analytics.

Learning Takeaways:

• Geopolitical and industry-specific cyber security risks
• Elevate the threat landscape, especially for high-value assets in oil and gas, utilities, and manufacturing.
• Offering a roadmap to enhance the reliability and security of AI-based condition monitoring in the Middle East.

Head of Mechanical Department & Professor Ph.D. (Mechanical Engineering) Roorkee Institute of Technology (RIT) is a premier educational institution NAAC A++ Accredited in Roorkee, Uttarakhand, India. Experience 25+ year, Around 50+ research papers in international/national journals and conferences ,Best Researcher Award, RIT (2022). Expertise Vibration Analysis, Predictive Maintenance Condition-Based Monitoring with generative AI, Deep Machine Learning Applications in Vibration Analysis.