Lameness Prediction using AI & Sensor Data

Overview

Lameness is a critical welfare and economic issue in dairy farming. This research utilizes accelerometer data collected from commercial settings to predict lameness events automatically and accurately.

Methodology

• Data Source: Large-scale commercially created datasets comprising sensor readings.
• Algorithms: Implementation of various Machine Learning techniques, ranging from traditional classifiers to State-of-the-Art (SOTA) Deep Learning models.
• Validation: Rigorous testing against veterinary diagnoses to ensure model reliability.

Impact

The project aims to enable early detection of lameness, allowing for timely intervention and reducing animal suffering.