Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation

Area of Science:

• Agricultural Technology
• Animal Science
• Supply Chain Management

Background:

• The dairy livestock export industry faces evolving demands for efficiency and traceability.
• Long-distance transportation presents unique challenges for animal welfare and supply chain accuracy.

Purpose of the Study:

• To critically evaluate the potential of Artificial Intelligence (AI) and sensor technologies in dairy livestock export.
• To explore the application of the Internet of Things (IoT) for livestock enumeration, identification, and traceability during transport.

Main Methods:

• Review of novel applications of AI, IoT, and sensor technologies in livestock enumeration and identification.
• Analysis of technological advancements for monitoring behavioral patterns and real-time weight in cattle.
• Evaluation of benefits and challenges associated with technology integration in livestock export.

Main Results:

• AI and IoT enable precise livestock traceability through enumeration and identification.
• Real-time monitoring of behavior and weight improves accuracy in long-haul transportation.
• Innovations offer enhanced animal welfare, reduced supply chain errors, and increased productivity.

Conclusions:

• Successful integration of AI, IoT, and sensor technologies can significantly improve the dairy livestock export industry.
• Addressing challenges like data security, adaptability, and ethical considerations is crucial for sustainable adoption.
• These technologies are pivotal for a more efficient and competitive global dairy sector.