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Monitoring of Farrowing Patterns in Pigs using Radar Sensor Data
For this project, the student will utilize datasets previously collected from farrowing sows in a controlled farm
setting. The data will be cleaned and pre-processed to remove noise and artifacts. The student will explore signal
and image processing techniques that can be applied to process radar data, e.g., 3D points with corresponding
velocity information (point cloud) and range-doppler maps. Then, the student will design a workflow to identify
farrowing patterns, i.e., the time of farrowing and the delivery intervals between piglets with the help of radar
signals. Lastly, Machine learning techniques, including supervised pattern recognition models, will be employed
to analyse the data and develop an alert system capable of identifying abnormal farrowing patterns.
Keywords: Radar, Sensing, Artificial Intelligence
Nature of the Thesis:
• Literature research: 10%
• Experimental: 10%
• Data and image processing and
programming: 70%
• Documentation: 10%
Requirements:
• Motivation to work in a
multidisciplinary team
• Programming skills in pytho
Nature of the Thesis: • Literature research: 10% • Experimental: 10% • Data and image processing and programming: 70% • Documentation: 10% Requirements: • Motivation to work in a multidisciplinary team • Programming skills in pytho
The aim of this study is to develop an advanced monitoring system that utilizes radar sensor data to continuously
and non-invasively track farrowing patterns in sows, enabling the early detection of birth problems and therefore,
contributing to enhanced animal welfare and reproductive performance.
The aim of this study is to develop an advanced monitoring system that utilizes radar sensor data to continuously and non-invasively track farrowing patterns in sows, enabling the early detection of birth problems and therefore, contributing to enhanced animal welfare and reproductive performance.
Master_Thesis_Proposal_Pig_Farrowing.pdf
