TSSG research is spearheading the development of next-generation digital technologies that enable seamless tech-mediated interaction.

The breadth of TSSG’s research expertise is unique globally and the Centre’s structure supports collaborative innovation with industry to unlock the potential of digital content. TSSG has attracted over €30million funding from research and industry collaborations.

what we do

TSSG Key Research Areas

Emerging Networks Laboratory

The Emerging Networks Laboratory (ENL), is a TSSG Research Unit comprising 19 researchers focussing on challenges relating to the evolution of the communications networking and service technologies that will see widespread deployment in the next 10 years. ENL is recognised as a leading research group in the network and service management field worldwide, producing high quality scientific publications and graduating highly skilled PhD and MSc graduates. Its work is in large part driven by its research partnerships with the Irish R&D divisions of leading technology companies including IBM, Cisco, Intel, Ericsson, Dell EMC to name a few.

The Emerging Networks Laboratory (ENL) focus on the following key research themes:

Knowledge Defined Networks

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.

Beyond 5G Technologies

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.

Fundamentals in Molecular Communication

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.

Mobile Ecosystem & Pervasive Sensing

The field of Digital Health and associated Precision Healthcare initiatives is undergoing explosive growth both in academic research and commercial settings reflected by a growing body of ground breaking publications and findings, formation of new research centres and Labs. The MEPS Lab at TSSG spearhead research in areas such as Biomedical Nano and Molecular Communications, Pervasive Sensing and Movement and Gait Analysis.

The Mobile Ecosystem & Pervasive Sensing (MEPS) Unit focus on the following key research themes:

Biomedical Nano and Molecular Communications

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.

Pervasive Sensing

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.

Embedded System Communications

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.

AI & Machine Learning

The Artificial Intelligence and Machine Learning Unit at TSSG focuses on research and development of data driven services. Over the past 10 years the Unit (previously known as the Data Mining and Social Computing Unit – DMSC) has collaboratively developed cutting edge technology for companies such as: Disney, NTT Data, eDrive, TekTronics, Glanbia, and ServisBot. Our research staff have a wide range of experience across data science and engineering disciplines and specialise in deploying technologies in the agriculture and active ageing sectors.

The AI & Machine Learning (AIML) Unit focus on the following key research themes:

Fog Data Analytics

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

Artificial Intelligence

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

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.

ICT for Smart Infrastructure

The Programmable & Autonomous Systems Unit seeks to research, develop and commercialise techniques, tools and algorithms that will ensure that citizens can benefit from the digital evolution. We advocate that future digital platforms, in particular transport and energy, must exhibit a set of fundamental characteristics if they are to cope with rapidly changing requirements in such a complex environment.

Programmable – a system, service or platform whose logic is separated from its operation. By building programmable systems, we ensure that they are future proofed and flexible so that their features and functionalities can evolve as requirements evolve.

Autonomous – a system, service or platform is autonomous if it can perform its activities in a fashion that requires minimal human supervision in the face of complex and changing environmental conditions.

By directing our research into these two highly complementary topics, we can ensure that society can take full advantage of the new digitally connected world.

The PAS Lab focus on the following key research themes:

Intelligent and Smart Transport Systems

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.

Smart Energy

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.

What We Offer

Providing comprehensive services for establishing innovation through collaboration.

  • Securing of research funding
  • Management of European R&D Projects
  • Management of European R&D Programmes
  • Project Management and Collaboration
  • Proposal Writing and Preparation
  • Project Communication (Dissemination & Exploitation and Marketing & Communication)
TSSG brain initiative

aims to utilise expertise and knowledge from communication systems and networks to address challenging questions of the brain and nervous system.

View all Initiatives

Read the latest publications related to current TSSG research.

Chamil Kulatunga , Kriti Bhargava , Dixon Vimalajeewa , Stepan Ivanov .
Cooperative in-network computation in energy harvesting device clouds
Cooperative in- network computation in energy harvesting device clouds, Sustainable Computing: Informatics and Systems 16, 106 – 116 .
2017 .
Dixon Vimalajeewa , Eric Robson , Donagh Berry , Chamil Kulatunga .
Evaluation of Non-linearity in MIR Spectroscopic Data for Compressed Learning
New Orleans, USA, IEEE Computer Society, 2017 .
2017 .
K. Bhargava , S. Ivanov .
A fog computing approach for localization in wsn
2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1–7 .
Oct 2017 .
Featured Project

The ceFIMS-CONNECT project was initiated in March 2014 and aims to continue the good work of the ceFIMS project…

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