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TSSG RESEARCHER AMONG FINAL FIVE IN ‘MAKING AN IMPACT COMPETITION 2019’

By 12th December 2019 No Comments

As part of the research communication competition researchers explain why what they are doing matters to Irish society or in a global context

Mohit Taneja, a Software Research Engineer and Ph.D. Researcher with the Emerging Networks Lab at Telecommunications Software and Systems Group of Waterford Institute of Technology was one of the five finalists for this year’s ‘Making an Impact’ competition.

This is the 11th year of the research communication competition run the Higher Education Authority (HEA). The objective of this competition is the effective communication of research to a lay audience. The researchers will explain why what you are doing matters to Irish society or in a global context.

The competition saw five finalists compete to win two prizes of €2,500 each at The Lighthouse Cinema in Dublin on 4 December. The two winners were from University College Dublin and Trinity College Dublin.

Taneja said it was exciting to be shortlisted in the competition. “The project involved considerable efforts with the full-stack real-world farm deployment. We have worked on this project for over 3 years now, and it feels good to be nominated here, and that the work done is being recognised with this shortlist. Every member of the team has their share in the success of the project so far.”

The team includes Mohit Taneja, John Byabazaire, Nikita Jalodia, Dr. Alan Davy, and Paul Malone from TSSG, and Dr. Cristian Olariu from IBM.

Dr Sasitharan Balasubramaniam (Acting Director of Research, TSSG) had this to say about reaching the final: “This demonstrates the importance of communicating the importance of research to society, and in this particular case Mohit’s work in using sensor technologies to monitor the well-being of animals.”

About the project

SmartHerd, which has now been extended with follow-on IoF2020 funding as MELD (Machine Learning for Early Lameness Detection), is a project to detect early lameness in cattle. Cattle lameness is a considerable problem in the agri-industry. It causes pain and discomfort for the cow, while lowering fertility and milk yield for the farmer. Since current solutions come with high-initial costs and complex equipment, this solution utilises leg mounted sensors – measuring step count, lying time and swaps per hour – in combination with machine learning algorithms to identify lame cattle at an early stage. This data is analysed in the cloud and anomalies are sent to farmers’ mobile device to treat affected animals immediately and avoid further effects. As opposed to a general approach, this solution customises the data models to dynamically adjust as weather and farm conditions change. By detecting early lameness before it can be visually captured, treatment costs are decreased while animal welfare is improved. Moreover, the ongoing extension with MELD seeks to extend the developments to a beef herd, and includes global site deployments in farms in South Africa, Portugal, Israel, and Ireland.

The Emerging Networks Lab Research Unit

The project is based in the Emerging Networks Laboratory (ENL) research unit at TSSG. Their research focus is towards core networking and future networks and communications technology, as well as emerging network paradigms. ENL researchers strive to generate high quality research results in the domain, and have published in the leading international scientific journals and conference proceedings.