Jiann-Shing Shieh received the B.S. and M.S. degrees in chemical engineering from National Cheng Kung University, Tainan, Taiwan, in 1983 and 1986, respectively, and the Ph.D. degree in automatic control and systems engineering from the University of Sheffield, Sheffield, U.K., in 1995. He is currently a Professor with the Department of Mechanical Engineering, a Joint Professor with the Graduate School of Biotechnology and Bioengineering, and also serves as the Provost of Yuan Ze University, Taoyuan, Taiwan. He has published more than 150 papers in peer-reviewed international journals. His research interests include biomedical engineering, particularly in bio-signal processing of ECG, BP, EEG, SPO2, center of pressure position signals, artificial intelligent analysis and control, medical automation, pain model and control, critical care medicine monitoring and control, dynamic cerebral autoregulation research, and brain death index research. Dr. Shieh also serves a Section Editor of the Journal of Clinical Medicine and an Academic Editor of the Journal of Healthcare Engineering. He is also a principal investigator for Taiwan Experience Education Program for nearly 4 years as the following topic: Industry 4.0 - Research on Smart Production and Management.

Two topics for this IIPP project:

1. The Industry 4.0 standard will change the landscape of all production-based industries. Digitalization and minimization devices will be the key driving factors of future factory concepts, and together with IoT, AI, big data analysis, edge computing, fog computing, and cloud computing, real-time intelligent sensors (including not only monitoring sensors but also modelling, critics, fault detection and isolation, and over the air update algorithms) will open a new era of process control. The aim of this project is doing real-time intelligent sensor design to improve performance under uncertain environmental conditions. In order to complete certain tasks without the intervention of any other systems or supervisor (human), these intelligent sensors should be able to adapt to their surroundings when facing different conditions (i.e., external interfere or internal variations in parameters).

2. Wearable sensors are becoming very popular recently due to their ease of use and flexibility in recording data from home. They can range from simple adhesive sensors to more sophisticated, stretchable implants to monitor health or for diagnosis. The basic unit of a wearable sensor is the electrodes or wires, the power source, and the interface/communication unit, which can be a smartphone or other types of signal receivers. One of the most important features of a wearable sensor is flexibility: It has to flex, stretch and twist without straining the sensory part and maintain the quality of the measured signal. In this project, special attention is given to the AI technologies that are utilized in signal processing and diagnosis in order to reduce the computationally intensive and less memory hardware.