Machine learning research between NUI Galway and McHale Engineering

The NUI Galway Agricultural Machinery Research Group and McHale Engineering are working on a research project that will focus on developing sensor solutions and accompanying machine learning models to optimise the efficiency and driving practices.

The NUI Galway Agricultural Machinery Research Group and McHale Engineering are looking to host a Career-Fit Plus Research Fellow position. This partnership have successfully obtained career-fit funding from Enterprise Ireland, in the past.
The research project will focus on developing sensor solutions and accompanying machine learning models to optimise the efficiency and driving practices of harvest machinery while working with a local farm contractor. A variety of implements are used in collecting grass silage in Northern Europe. These implements are generally used with a tractor with high horsepower engines, consuming significant amounts of fuel. Fuel economy and time constraints are significant factors for a machinery operator and owners during the harvest season.
The research project will aim to provide proven machine learning models to optimise driving patterns and fuel economy in a constrained environment. The research must balance crop yield, feed quality, driver well-being and machinery lifespan. A fellow appointed will have access to a significant dataset of already collected data and asked to contribute towards sensing solutions on state-of-the art prototype machinery.
McHale Engineering is now the largest producer of agricultural machinery in Ireland. The company is recognised for bringing innovative, high output, heavy duty agricultural solutions to the market place. The McHale Group of Companies has experienced strong growth over the last decade. In the last 6 years the business has doubled its turnover and their products are sold into over 55 countries around the world.
The NUI Galway Agricultural Machinery Research Group specialises in applying IOT sensor solutions for operations for agricultural machinery in challenging environments. The group hosts expertise in Digital Signal Processing, Machine Vision, Machine Learning and data analytics. The group reside in the National University of Ireland, Galway. The group has a strong publication record and has close ties to automotive and agricultural technology firms.

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