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 focusses 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 Things/Devices Can Cooperate; Cooperation in Mobility; Cooperation in Robot Societies; Machine Learning in Collections of Cooperating Things.
Cyber Physical Systems (CPS) Lab carries out world-class research in IoT spanning physical layer to services and applications. More specifically CPS Lab focusses 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 Internet of Things; IoT privacy, security, trust, reputation.
Security and PrivacY Research in IoT (SPYRIT) Lab carries out world-class research and addresses the security and privacy challenges relevant to IoT-enabled (smart) infrastructure by developing techniques and tools for their effective mitigation. More specifically, SPYRIT Lab focusses on IoT-enabled Infrastructure including Secure Protocols; System Resilience; Secure Cooperation; Trust & Reliability; Access & Control. Focus on IoT-enabled Data includes Data Integrity; Data Provenance; Information Leakage; Privacy-preservation & Storage; Anomaly Detection.
Contact: Professor Robin Doss, email@example.com
Machine Intelligence Lab (Mil) is primarily associated with Data-to-Intelligence (D2I) Centre and its secondary affiliation is with CITECORE.
Contact: Professor Antonio Robles-Kelly, firstname.lastname@example.org