01
Sensing Data
Acquire reliable field data from images, ToF sensors, thermal imaging, and sensing signals.
Lab Positioning
Not isolated technology demos,
but complete system-level problem solving.
The core value of iCPS Lab is to integrate artificial intelligence, sensing data, and physical environments into systems that can be deployed, verified, and continuously improved. Our research starts from problem definition and returns to real application settings such as healthcare, manufacturing, and smart cities.
02
AI Interpretation
Turn data into explainable decision support through model design, training, and validation.
03
System Deployment
Combine edge computing and human-machine interfaces to bring technology into clinics, production lines, and real environments.
Research Philosophy
Starting from field problems, we make research outcomes truly usable.
Principal Investigator
Professor Wan-Jung Chang
Wan-Jung Chang, Ph.D.
Lab Leadership
Interdisciplinary training for engineers who solve real problems.
“The value of engineering education lies in exploring the unknown and returning technology to society. We expect our team not only to master advanced technologies, but also to deliver practical solutions for clinical and industrial needs.”
Professor Chang has long focused on AIoT and edge computing, building a highly interdisciplinary research environment in the Department of Electronic Engineering at NKUST. The lab connects hospitals and technology industries externally, while guiding students to transform ideas into verifiable system outcomes internally.
AIoT
Smart sensing integration
Edge AI
Edge deployment applications
XR
Immersive training systems
Two-Way Impact
Connecting clinical and industrial fields while training research talent.
🤝
For Partners
Clinical-Industrial Collaboration
We have experience in industry-academia collaboration and clinical field validation. The lab supports enterprises and hospitals with customized technical assessment, AI system development, and proof-of-concept validation.
- ✓AI-assisted systems for clinical pain points
- ✓Smart factory defect detection and automation deployment
- ✓Advanced technology transfer and joint R&D
🎓
For Students
Start Your Research Journey
PhD students, master’s students, and undergraduate project students are welcome to join. You will not only study theory, but also participate in data processing, model training, system integration, paper publication, and competition practice.
- ✓Complete training from algorithm development to system deployment
- ✓Guidance for domestic and international conferences and journals
- ✓Hands-on experience through innovation competitions and industry-academia projects
Core Applications
Three Core Research Areas
With AIoT as the technical foundation, the lab connects healthcare AI, smart manufacturing, and smart transportation so that models become deployable application systems rather than accuracy numbers alone.
Healthcare AI
Digital Healthcare and Smart Care
Integrating thermal imaging, ToF sensors, and AI skeleton recognition for psychiatric self-harm warning, patient behavior recognition, automated ear lesion diagnosis, tongue rehabilitation, and XR training for surgical instrument education.
Smart Manufacturing
Industry 4.0 Smart Manufacturing
Using Edge AI to develop low-latency, high-accuracy automated defect detection systems for production-line issues such as capacitor missing solder and product packaging defects.
Smart City
Smart Transportation and IoT
Deploying reliable IoT sensing networks to support bidirectional interaction between network communication and the physical world, with applications in traffic monitoring, environmental sensing, and sustainable cities.
Join / Collaborate / Build
The next deployable AI system may start here.
Whether you are seeking clinical-industrial collaboration, joining a research project, or learning more about lab outcomes, we welcome you to contact us through the website or by email.