Vol. 10, Issue 8, Part D (2025)

Author(s): Pooja Nitharwal, Adany S, Ishwar Bhabhor and Asem Ameeta Devi

Abstract: Animal welfare, encompassing both physical health and mental well-being, is a critical component of modern livestock production, yet traditional assessment methods are often invasive, subjective or labor-intensive. Recent advances in behavioral biometrics offer non-invasive and reliable indicators of welfare in domestic species. This review synthesizes progress in automated monitoring technologies, including wearable sensors, computer vision, AI analytics, GPS, RFID and acoustic systems, which enable continuous assessment of locomotion, feeding, resting behavior, social interactions and stereotypies. Behavioral parameters such as frequency, duration, intensity and variability have proven sensitive for detecting pain, stress, disease, heat load and lameness, while supporting precision feeding, reproductive management and early disease surveillance. In parallel, biometric identification methods using muzzle prints, iris patterns, genetic markers and automated traceability enhance livestock management and biosecurity. These developments align with established welfare frameworks such as the Five Freedoms and Five Domains. However, challenges remain regarding data interpretation, validation under field conditions and scalability for commercial application. Overall, behavioral biometrics and automated identification represent a significant step toward improving animal health, productivity and sustainability while reducing reliance on invasive assessment methods.