Automated Diagnostic Approach in Swine Production with Focus on Locomotor Sensing

Currently, pig production faces several challenges in ensuring the individual welfare of animals, especially with the rapid expansion of the sector and the shortage of available labor. Locomotor problems, such as lameness, are among the leading causes of sow culling, economically affecting productivity and overall animal welfare. In this context, Precision Livestock Farming (PLF) has gained prominence as a strategy for introducing technologies into the field that enable the detection of various issues, including locomotor disorders, bringing benefits to both animals and producers and resulting in greater system sustainability. The objective of this study was to conduct a preliminary evaluation of the behavior of piezoelectric sensors under controlled loads as an initial step toward the development of a platform for detecting locomotor variables in intensive production systems. Laboratory tests were conducted without the presence of animals. A sensor system was developed and connected to a microcontroller for acquiring electrical signals generated by the manual application of five standardized masses (100g, 150g, 170g, 190g, and 200g) at regular intervals. The collected signals were smoothed and analyzed based on the average peak amplitude using Python software. The results showed a positive correlation between the increase in applied mass and the average amplitude of the signals, indicating the system's sensitivity to pressure variations. These responses reinforce the potential of the technology to detect loads under various conditions, such as animal body weight, for use in automated monitoring applications.