AIoT based structural health monitoring and diagnostics

   School of Engineering

This project is no longer listed on and may not be available.

Click here to search for PhD studentship opportunities
  Prof Gui Yun Tian  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

The project will work with industry globally to address global challenges of energy efficiency, digital transformation, safety and security in investigation of novel sensing, intent of things, and AI for nondestructive testing, structural health monitoring and diagnostics such as corrosion monitoring, battery status of charges, pipeline integrity, wearable devices, smart composite, smart skin etc.  

By combining flexible sensing material, programmable device structure, high-efficiency wireless signal transmission and AI-enhanced data analytics, this project aims to develop a sensing system that can work with complex structures in various application areas for condition based maintenance and digital transformation. 

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains colleagues from all sectors of society.  We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent.  We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices. 

Computer Science (8) Engineering (12) Physics (29)


J Zhang, GY Tian, AMJ Marindra, AI Sunny, AB Zhao, A review of passive RFID tag antenna-based sensors and systems for structural health monitoring applications, Sensors 17 (2), 265, 2017;
CA Tokognon, B Gao, GY Tian, Y Yan, Structural health monitoring framework based on Internet of Things: A survey, IEEE Internet of Things Journal 4 (3), 619-635, 2017

 About the Project