Programme Lead: Dr SUN Sumei

Industrial internet of things (IIoT), through providing secure connectivity to things, machines, robots, autonomous systems (AS) such as unmanned aerial and ground vehicles (UAVs, AGVs), computers, and people, is a key enabler for intelligent industrial operations using advanced data analytics to realize transformational business outcomes.

The IIoT Thematic PhD Programme, led by Dr Sumei Sun, Lead Principal Investigator, and a fellow of the International Electrical and Electronics Engineers (IEEE), in partnership between Institute for Infocomm Research (I2R) of Agency for Science, Technology, and Research (A*STAR), and National University of Singapore (NUS), Nanyang Technological University (NTU), and Singapore University of Technology and Design (SUTD), aims to research and address fundamental issues, and develop leading-edge IIoT technologies, with the following focus:
• Ultra-low latency, ultra-high reliability machine type communications
• Dense and massive machine type communications
• Software-defined cognitive heterogeneous industrial wireless communications
• Industrial cyber-physical security
• Advanced data analytics, machine learning, and deep learning for industrial applications
• Edge and fog computing
• Inter-play of communications, caching, computing, control, and security

The PhD students will be jointly supervised by I2R scientists and university professors. They are able to access I2R resources, including computational infrastructure, laboratory and testbed facilities. At the same time, the students will be fully plugged into the IIoT Research Programme, addressing the pressing and real industry challenges, and deliver high-impact research outcomes

Contact Us. for more information!

Blockchain for IoT Applications
Blockchain Security in IoT
Cyber-Physical Authentication and Attack Detection for IIoT Systems
Data Driven Approach to Cyber-Physical System Security
Deep Fuzzing IIoTs
Degradation Management in Preventive Maintenance
Event-driven wireless networking and edge computing in IIoT scenarios 
Flying Access Networks for Future IoT
IIoT Based on IEEE 802.11ah
Machine Learning for IIoT Security
Model-based Fuzzing of IoT
Real-Time Decision Making with Digital-Twins
Reliability Analysis of IoT
Robust wireless networking and edge computing for real-time actuation in IIoT scenarios
Scalable Network Access with Service Guarantees for IIoT Systems
Trustworthy power grid space signatures for secure IoT
Ultra-low latency machine communications
Wireless Camera IoT Networks