Graduate Programs

Credit-Bearing Micro-Credential in Intelligent Infrastructure Systems

The 6-credit-hour graduate Credit-Bearing Micro-Credential in Intelligent Infrastructure Systems (CBMC-IIS) aims to provide Engineering students with knowledge, skills, and practical applications of Structural Health Monitoring (SHM) and smart infrastructure systems. Students will also learn the principles and applications of Digital Twins (DTs) in the planning, design, construction, and operation of integrated infrastructure systems, including transportation and urban assets. CBMC-IIS addresses infrastructure challenges and supports the United Nations Sustainable Development Goals (SDGs), particularly the goals of building resilient infrastructure and sustainable cities and communities. It is open to: (i) current undergraduate engineering students fulfilling the admission requirements of CBMC-IIS, and (ii) leaners holding a Bachelor’s Degree in civil engineering or a related discipline.

Admission

Current engineering undergraduate students:

• Students should satisfy the admission requirements of the Bachelor-Master Accelerated Option
• Successful Completion of STAT 210 Probability and Statistics, GENG 230 Computer Programming, MECH 305 Mechanics of Materials, and CIVL 310 Structural Analysis.

Holders of a bachelor’s degree in Civil Engineering or a related discipline

• Learners should satisfy the admission requirements of the UAEU Engineering Master’s Program

Non-stackable towards a degree:

• Learners should hold a bachelor’s degree in civil engineering or a related discipline and have at least one year of work experience following the completion of their bachelor’s degree. Such applications will be considered on a case-by-case basis.

Targeted Students

The CBMC-IIS targets learners holding a bachelor’s degree in civil engineering or a related discipline, as well as meritorious UAEU undergraduate engineering students who are willing to develop knowledge and skills in AI-assisted structural health monitoring and digital twin technologies to support infrastructure assessment, predictive maintenance, and informed decision-making throughout the infrastructure lifecycle.

Program Objectives

• Provide engineering students with advanced knowledge of structural health monitoring and digital twins to assess and manage the performance of civil infrastructure.
• Train engineering students to utilize data analytics, AI-informed reasoning, and digital technologies to support decision-making for infrastructure safety and lifecycle management.
• Prepare engineering students to demonstrate professional responsibility, effective communication, and teamwork related to smart infrastructure systems.

Program Learning Outcomes

Upon successful completion of this program, students will be able to:

• Critically explain the principles, technologies, and integration of structural health monitoring systems, digital twins, and AI techniques in intelligent infrastructure applications.
• Analyze and interpret infrastructure data using signal processing, digital modeling, and AI-based techniques to assess structural performance and support engineering decisions.
• Communicate technical analyses and recommendations while working both independently and collaboratively, demonstrating ethical and professional responsibility.

Degree Requirements

Required Credit Hours : minimum 6 hours

CBMC Courses (6 CHs)