Precision Dairy – A Universal Agri Tech Sensor System

Precison Dairy1

Waterford Institute of Technology’s Telecommunication Software and Systems Group (TSSG) was awarded SFI funding in conjunction with Teagasc for a project titled “Using precision technologies, technology platforms and computational biology to increase the economic and environmental sustainability of pasture based production systems (PrecisionDairy)” in a joint venture initiative between Teagasc and Science Foundation Ireland (SFI) within the research theme known as ‘Future Agri-Food’. PrecisionDairy focuses on the use of ICT to develop an autonomous system capable of integrating, processing and managing data from diverse sensor environments (e.g. grass, animal) to deliver timely and effective farm management information to the farmers and influence the decision making process.

Precision dairy farming is an inherently interdisciplinary field incorporating concepts from bioinformatics, biostatistics, pasture and animal breeding, animal husbandry and nutrition, machine learning, sensor networking, autonomic network management and engineering. TSSG primarily focuses on the following tasks:

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Surprising Results in Gait Analysis Research

ExerScout Gait Analysis

The ExerScout Gait Analysis application is a non-marker based motion tracking system that automatically gathers data of an individual’s gait as they are on a treadmill.  This research began as 12 months Innovation Partnership and R&D with Elite Sports Performance which is an Irish company involved in appraising fitness and agility by evaluating fundamental movement patterns using the Functional Movement Screening (FMS) approach.

Elite Sports Performance came to the TSSG with an interest in developing an automated way in which FMS could be used by evaluating subjects whereby they would perform the tests, be assessed by software, and have sets of corrective exercises prescribed to them to allow them to improve their mobility, stability and flexibility and to reduce their risk of injury.

The GSK Human Performance Lab, a close partner of Elite Sports Performance, were intrigued by the application of ExerScout and tasked Elite Sports Performance to develop a feature that allowed the analysis of a persons’ gait using the Microsoft Kinect V2.  This new feature would then be compared to a state of the art 24 sensor treadmill that is available in GSK.

How did TSSG help?

TSSG developed this feature on the existing ExerScout platform along with further requests of assessing standing analysis, balance analysis and sitting analysis.

A complete Windows 10 application was developed in conjunction with the Microsoft Kinect V2 that can evaluate the 7 FMS tests, score each test, identify weaknesses and provide corrective exercises that will improve the scores given.  The application also has a media section that contains footage on each of the seven tests and all the corrective exercises that are associated with each test.

A series of algorithms have been developed which include methods for calculating a user’s step width, step length and stride length.  Not only does the application gather data on a person’s gait, it will also gather data on other gestures including stance, balance, other movements while performing the exercise on the treadmill.

The Windows 10 application gathers data from the Microsoft Kinect V2 sensor while a person is walking on the treadmill.  The Kinect V2 is a motion sensor that can measure three-dimensional motions of a person.  The data generated by the Kinect V2 is a frame by frame algorithmic calculation of various gestures.  A readout is displayed in the application of the calculations for each gesture that is being generated and they are also being stored in the cloud.  A skeleton representation of the person on the treadmill is also being displayed within the application.  For further analysis, the data can be exported to a CSV file and be analysed by an expert to identified trends etc.

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TSSG turns to ICT in Neuroscience

3d rendering of human  brain on technology background

Post doc Researcher, Michael Taynnan Barros and Director of Research, Sasitharan Balasubramaniam, both of TSSG, are working on an ICT-based approach to Brain Communication, Neurology and Neurodegeneration under the TSSG Brain Initiative. 

The TSSG Brain Initiative is multidisciplinary and crosses between multiple Research Units. The decision to start this new initiative and research direction is due to the importance of this new research field globally, where we are witnessing large amount of investments both in Europe (EU FET Flagship “Human Brain Project”) and the US (Obama “BRAIN” initiative). While the field of Brain research has predominantly been driven by Neuroscience, ICT has started to play a role in developing new approaches for understanding the operations of neural systems, as well as diagnosing diseases. TSSG has traditionally been an ICT research centre that focuses on research in communication networks and services, and it is the intention of this initiative to bring theories from traditional “communication and networking” to understand the brain’s communication process. The latter is mainly focused on new solutions to help patients suffering from neurodegenerative diseases. The other motivation for the creation of the initiative is the linkages we are now starting to witness between the brain and machines. This includes development of new brain-inspired algorithms for Artificial Intelligence (e.g. Deep Learning), as well as Brain-Machine Interfaces (BMI).


Neuroscience has exploded in recent years as a major prominent research field with an incredible amount of investment from both public and private sectors globally with the goal of understanding the brain completely as well as transferring this knowledge to engineering and technology in general. However, the slow pacing discoveries are not accompanied by technology advancements and therefore creates a gap. It is being realized, even more recently, that information and communication technology can be, together with nanotechnology and synthetic biology, the novelty needed in neuroscience to help it reach its goals. We explore this possibility by implementing the merge of this areas and studying both neurology and neurodegeneration medicine. We investigate the neuronal communications in the brain, which are separated by many scales and layers, and how their communication affect neurons well functioning and disease starting processes and spreading caused by communication failures. Neurodegeneration has increasingly affected people’s lives in many different forms due to the increase in life expectancy in the ageing society. We also investigate many different strategies for neurodegeneration treatment and diagnosis including optogenetics nanonetworks, synthetic biology, nanoparticles and silicon-in-a-cell chips. The TSSG Brain Initiative (TBI) is currently pursuing research in this area based on the Internet of Bio-Nano-Things vision [1], where both synthetic and natural nanomachines will be connected to the Internet to perform both sensing and actuation tasks, and in this case, inside the Brain. In the following you will find a review of two main strands in the TBI, which has been successful in terms of grants, publications and public engagement.

Wireless Optogenetics Nanonetworks

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Success in the IEEE Netsoft Conference & Workshop 2018


IEEE Conference on Network Softwarization (IEEE NetSoft) 2018 has been created as a flagship conference aiming at addressing “Softwarization” of networks and systemic trends concerning the convergence of Cloud Computing,  Software-Defined Networking (SDN), and Network Function Virtualization (NFV). IEEE Netsoft is technically sponsored by the IEEE Communications Society and the IEEE Computer Society.

TSSG Researchers submitted three papers and all of these were successfully accepted in this conference.

The first paper has been accepted in IEEE NetSoft 2018 main conference. In this paper, a network coding approach to In-Band control traffic sharing in Software Defined Networks has been proposed. In fact, the use of network coding has been proposed which encourages information  mixing  as packets  traverse the network. It is shown that network coding when applied to control plane  traffic  in  an  in-band  design  can  help overcome  losses  due to  congestion  and  link  impairments. Evaluation results  suggest that network coding aware in-band design can mitigate number of re-transmissions as well as total delay incurred by control packet losses.

Fayaz Akhtar, Mubashir Husain Rehmani, and Alan Davy, A Network Coding Approach to In-Band Control Traffic Sharing in Software Defined Networks,  IEEE Conference on Network Softwarization (IEEE NetSoft),2018.

The second paper has been accepted in IEEE International Workshop on Emerging Trends in Softwarized Networks (ETSN), Colocated with IEEE NetSoft, 2018. In the second paper, a link failure learning algorithm using Multi-armed bandit technique (LFL-MAB) has been proposed for Software Defined Network based Smart Grid. The proposed LFL-MAB algorithm will be run by the SDN controller. LFL-MAB algorithm has the capability to learn the strategy adopted by the attacker and select those communication links which are reliable, thus adapting to the changing network conditions dynamically. It is demonstrated through simulation results that the proposed algorithm outperform other approaches and ensure reliable communication and resiliency within the smart grid network.

Mubashir Husain Rehmani, Fayaz Akhtar, Alan Davy and Brendan Jennings, Achieving Resilience in SDN-Based Smart Grid: A Multi-Armed Bandit Approach, IEEE International Workshop on Emerging Trends in Softwarized Networks (ETSN), Colocated with IEEE Conference on Network Softwarization (IEEE NetSoft), 2018.

The third paper has been accepted in IEEE NetSoft 2018 main conference as well. In the paper, federation between different domain SDN controllers has been leveraged to provision end-to-end QoS in real-time as per an application or enterprise customer’s dynamic demands. Traditional and widely deployed mechanism of provisioning wide area network QoS – MPLS itself has been augmented with SDN breakthrough to embed dynamicity and agility into its rather rigid QoS provisioning process. The proposed SDN-MPLS QoS framework referred to as MPLS-as-a-Service has been implemented on a state-of-the-art testbed referred to as WaterFed hosted herein TSSG’s in-house data-center. Inter-domain QoS is seeing advancements from dedicated players such as SD-WAN vendors. With MaaS, the aim is to rather evolve this process natively from the network control or at the operator level itself and making the process dynamic enough to be suited for the economics of even smaller customers.

Sidhant Hasija, Rashid Mijumbi, Steven Davy, Alan Davy, Brendan Jennings and Keith Griffin, Domain Federation via MPLS and SDN for Dynamic, Real-time End-to-end QoS Support,  IEEE Conference on Network Softwarization (IEEE NetSoft),2018.


Job Title: Senior UX Designer/Developer
Department: Creative Design Unit (CDU), TSSG (
Commencement Date: Immediately
Location: TSSG, Carriganore Campus, Waterford Institute of Technology
Salary Range: €46,460 – €61,610 p.a.
Closing Date of Advert: 16:00 on Friday, 13th April 2018

Minimum Requirement: BSc. in Computer Science/Multimedia (or equivalent)

Position Details:

TSSG is seeking a Senior UX Designer / Developer to join its Creative Design Research Unit.  This is initially being offered on a temporary fixed term duration of 12 months.

Please note that interviews for this position will be held week beginning 23rd April 2018


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