Automated activity analysis of pregnant, pre-partum, and post-partum dromedary female camels using YOLOv8 and SAMURAI tracking

Abstract

Introduction Behavioral monitoring during reproductive stages is vital for camel welfare and effective farm management. This study aimed to assess daily activity patterns in pregnant, prepartum, and postpartum dromedary camels using AI-based video analysis tools. Methods Two experiments were conducted under farm conditions in Fujairah, UAE. In Experiment 1, YOLOv8 with SAMURAI tracking analyzed short 15-minute video segments from 25 pregnant camels at selected times. In Experiment 2, 12 camels with colored neck collars were continuously monitored during late pregnancy, parturition, and postpartum. Results In Experiment 1, camels exhibited clear circadian rhythms, with increased sitting and sleeping activities at night, and heightened eating, drinking, and standing/walking during daylight hours. In Experiment 2, significant behavioral shifts were observed across reproductive states. Prepartum camels displayed elevated standing durations (699.7 ± 45.7 min/day) and reduced eating (128.3 ± 48.2 min/day), indicating prepartum restlessness. Postpartum camels gradually regained normal activity levels, with increased sitting (722.3 ± 65.4 min/day), sleeping (194.0 ± 15.4 min/day), and eating (229.1 ± 20.9 min/day) within the first 24 hours after calving. Discussion These findings validate the use of the YOLOv8–SAMURAI system and long-term collar-based identification as reliable, non-invasive tools for automated camel activity assessment. The observed activity markers provide meaningful indicators for reproductive status and recovery, enabling early detection of health or welfare issues. This research supports the development of precision management systems for camels in intensive farming environments.