IoT Platforms and Applications Lab
The IoT Platforms and Applications Lab (PAL) carries out world-class research, development and experimentation on IoT middleware, platforms, services, systems and algorithms, forming the basis for innovative solutions to today’s most pressing problems. CITECORE PAL focuses on:
- IoT platform benchmarking
- large-scale IoT systems performance and scalability
- IoT-enabled context-awareness and reasoning enterprise-wide
- IoT device, data, semantics and context discovery
- real-time machine learning
- analytics and AI for IoT
- context-aware IoT security
- blockchain-enabled IoT for SLAs
- context-aware IoT systems in fog/edge computing
- IoT service-oriented context-aware systems with nature-inspired learning and adaptation strategies
- IoT-enabled multi-sensor fusion with feeds from social media data streaming
- swarm robotics as IoT actuating arm
- distributed goal reasoning for dynamic IoT
- cooperative IoT
- big IoT systems-as-a-whole perspectives
- platforms/middleware for cooperative IoT
- how things/devices can cooperate
- cooperation in mobility
- cooperation in robot societies
- machine learning in collections of cooperating things.
Cyber-Physical Systems Lab
The Cyber-Physical Systems Lab (CPS) carries out world-class research in IoT spanning physical-layer to services and applications. More specifically CPS Lab focuses on:
- IoT connectivity (machine-type communication and cellular IoT)
- physical-layer security
- distributed estimation/detection and computing
- smart grid communications and networking
- IoT systems and IoT-enabled applications
- IoT stream data fusion and analytics
- IoT service provisioning and allocations
- cloud/edge/fog computing and services for the IoT
- reliability models for the IoT
- IoT privacy, security, trust and reputation.
Security and Privacy Research in IoT Lab
The mission of the Security and Privacy in IoT Lab (SPYRIT) is to address the security and privacy challenges relevant to IoT-enabled smart and critical infrastructures by developing techniques and tools for their effective mitigation. SPYRIT draws on strong capability in the areas of:
- security protocols
- network security
- data security
- formal methods
- applied machine learning
- device security
- malware analysis
- digital forensics and privacy-preserving techniques to address the security and privacy challenges in the IoT ecosystem.
Our vision is to pioneer new directions for IoT security that are adaptive, scalable and responsive to the dynamic threat domain that massively interconnected IoT systems will operate in, with a focus on application domains such as industrial IoT (IIoT), smart cities, smart grids, supply chain and logistics, intelligent transport systems, defence and health.
For more information about SPYRIT please contact Professor Robin Doss.
Machine Intelligence Lab
The Machine Intelligence Lab conducts world-class research to harness the transition from a process-defined world to a data-driven one by creating and developing future AI technologies and techniques that will have transformational effects across the economy and society. We aim at designing intelligent algorithms that automate problems of data analysis, planning and decision-making. The lab pursues interdisciplinary research within the areas of pattern analysis, machine learning and AI aimed at discovering the principles underlying the design, development and deployment of artificially intelligent systems.
For more information and enquiries contact the centre director.
Research Centre Director
Professor Arkady Zaslavsky
+61 3 924 45305
Email Arkady Zaslavsky