Telecom operators as well as cloud providers are constantly seeks approaches to maximise the efficiency of very high capacity networking infrastructure at lower costs, sharing infrastructure investment along with providing customised networking connectivity to meet end user needs. Virtualisation of network functions along with software defined networking technology is enabling enhanced flexibility with regards to network service provisioning. Coupled with insights gained via Artificial Intelligence will enable an intuitive network substrate that can act on knowledge. This theme seeks to research and develop knowledge defined network management techniques applied to both cloud and telecom networking infrastructure.

The very definition of the Internet is being redefined to meet the needs of an advancing society. Internet of Things is enabling various sectors to leverage Internet technologies to vastly improve productivity.

The Molecular Communications research theme is investigating communication for nano scale devices, in particular in biological environment. Nanotechnology has tremendous potential, especially in the field of medicine. Research to date has largely focused on developments of materials to improve the capabilities of nano devices. However, integrating communication capabilities to these devices will further improve the potential of nano devices. The research conducted in this theme is investigating communication between nano devices using molecular communications, where information is encoded into bio-molecules that are diffused into the environment, and decoded at the receiving end.

A new paradigm shift has occurred in the field of communication systems and networks, where artificial communication systems are created from biological components. These communication systems are known as molecular communication systems. Mobile Ecosystem and Pervasive Sensing (MEPS) Lab are investigating how molecular communications can be applied for biomedical application.

Mobile Ecosystem and Pervasive Sensing (MEPS) Lab’s research in this area is focused on achieving a passive monitoring model that facilitates a precision health approach. This requires advanced communication, collection, storage and analysis of big data from pervasive sensors such as wearable, implantable and ambient sensors to facilitate continuous monitoring of a person’s health/clinical condition.

This thematic area is focused on research relating to embedded sensing and control. This encapsulates research topics such as wearable and implantable wireless sensor network solutions and real-time cooperation of embedded and wearable sensor networks. Across the healthcare sector the capability to utilise such embedded system communications enables monitoring of patient’s health status at any time.

The maturation of the Internet of Things and Big Data technologies has produced some highly innovative services and applications. However, many application scenarios are constrained by low energy consumption or low latency requirements where it is necessary to utilise processing resources closer to the source of the data

Deep Learning algorithms have dramatically transformed the field of Artificial Intelligence in recent years and is not only driving a new breed of interaction models and interfaces to existing applications and services but also pushing the cognitive intelligence of technology forward at a rapid pace.

Augmented Reality and Virtual Reality technologies are achieving mass adoption in numerous sectors including education, manufacturing and gaming. Using a HMD “Head Mounted Display”, VR creates an environment via software that immerses the user in a virtual world which suspends belief.  AR is similar but uses holograms which are overlaid on the user’s real environment and enhances or adds to what they can see via data displays or 3D models. These technologies produce new immersive human machine interaction paradigms that are not only transforming how we consume information but also the speed of how we comprehend higher level concepts.

New emerging initiatives in the smarter cities and transport domains are leading to autonomous vehicles, enhanced data management and new applications of machine learning and analytics. This opens new opportunities focusing on the research and development of innovative products stemming from an Intelligence Transport Systems (ITS) and Smart Transportation systems. Such new platforms will encourage the need to move from car-centric systems to multimodal systems that take into consideration the citizen and the environment. This research theme will be heavily sensor driven and citizen centric.

An energy conscious society is pushing for more efficient and cost effective strategies to control energy usage and to increase the usage of renewables. This opens up  researching into the following areas: Distributed energy systems - moving away from large decentralised power generation with long transmission systems to smaller, intelligent and local generation; Virtual network metering/Peer to peer sharing - allowing prosumers (those producing and consuming energy) to share that energy with neighbours with balancing of transaction costs; Supply/demand balancing, peak shaving - intelligent demand usage away from peak expensive times; Time of use tariff incentives - incentivisation of consumers to alter their energy profiles; Renewables intermittency - balancing of the system with high penetration of variable renewable energy resources.