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Project title

Artificial Intelligence application for Farming

Primary Funding Agency

DAFM

Co-Funding Organisation(s)

Lead Organisation

Munster Technological University

Lead Applicant

Not listed

Project Abstract

The APP4FARM project aims to develop a decision support system (DSS) for precision farming that integrates sensor data and machine learning models to improve nitrogen management in agricultural systems. The system will collect data on soil conditions, microbial activity, and weather patterns to help farmers make informed decisions about crop management. To achieve this, the project will implement a monitoring module and a forecasting module. The monitoring module extracts suitable information from raw data collected by different field sensors, uses data fusion techniques to compute non-measured quantities, and applies geostatistical and interpolation techniques to spatialize the data. The forecasting module will use machine learning (ML) models and meteorological and chemical data to predict quantities such as nitrogen oxides loss up to 3 days in advance. The integration between hardware and software modules is performed through a state-of-the-art communication system, and a dashboarding system presents the results to different users based on their needs. By analysing the relationships between microbial communities, nutrient cycling, and GHG emissions, the APP4FARM project will provide insights into the environmental impacts of agricultural practices, and ultimately support sustainable agriculture. Two pilot sites with different climate and temperature conditions have been selected to validate the developed sensor and test the DSS system, including Demmin, Germany and the The Teagasc Agricultural Catchments Programme (ACP) in Ireland. The project's expected outcomes are the development of a cost-effective and efficient DSS for precision nitrogen management, the reduction of nitrogen losses and greenhouse gas emissions, and improved soil health and productivity in agricultural systems.

Grant Approved

�246,901.57

Research Hub

Climate Change

Research Theme

3. Climate Solutions, Transition Management and Opportunities

Start Date

01/06/2023

Initial Projected Completion Date

31/05/2026