本文系统梳理了智慧畜禽技术在鸡、猪、牛等代表性畜禽品类中的应用现状、发展趋势与探索方向，识别现存问题并提出对策建议。智慧畜禽技术已在多领域实现规模化应用：环境调控技术可实时优化养殖环境并处理异常；信息采集技术通过传感器、视觉识别、深度学习等实现畜禽状态监测与精准识别；通过精准饲喂技术达成饲料智能配比、投喂及消耗监测全流程优化；养殖管理平台集成环境监测、远程调控、生产溯源等通用与个性化功能。在发展探索层面，智慧育种通过信息技术与育种工作深度融合，缩短育种周期并提升企业效益，智能育种大模型初步构建并加速品种改良；活体贷借助信息技术实现畜禽活体资产确权与数据核验，一定程度上解决养殖企业融资难题。当前智慧畜禽养殖发展面临个体识别精准度不足、数字化发展不均衡、标准缺失、平台数据共享不畅、养殖模型匮乏等问题。对此，本文提出提升识别精度、制定统一标准、推动平台共用共享、推进养殖模型开发应用等建议。随着技术的不断进步和养殖需求的变化，信息技术在畜禽养殖中的应用将会更加广泛和深入，本文为推进畜禽产业高质高效发展提供参考。

This paper systematically sorted out the application status, development trends, and exploration directions of smart livestock and poultry technology in representative categories such as chickens, pigs, and cattle, identified existing problems, and put forward countermeasures and suggestions. Smart livestock and poultry technology had achieved large-scale application in multiple fields: environmental regulation technology could optimize the breeding environment in real time and handle abnormalities; information collection technology realized the monitoring of livestock and poultry status and accurate identification through sensors, visual recognition, deep learning, and other means; precision feeding technology achieved the whole-process optimization of intelligent feed proportioning, feeding, and consumption monitoring; and breeding management platforms integrated general and personalized functions such as environmental monitoring, remote regulation, and production traceability. At the level of development and exploration, smart breeding, through the in-depth integration of information technology and breeding work, shortened the breeding cycle and improved enterprise benefits; intelligent breeding large models were initially built and accelerated breed improvement. Livestock and poultry live asset loans used information technology to realize the confirmation of rights and data verification of live livestock and poultry assets, which solved the financing problems of breeding enterprises to a certain extent. Currently, the development of smart livestock and poultry was faced with problems such as insufficient accuracy of individual identification, unbalanced digital development, lack of standards, poor platform data sharing, and insufficient breeding models. In response, this paper put forward suggestions such as improving identification accuracy, formulating unified standards, promoting platform sharing, and advancing the development and application of breeding models. With the continuous advancement of technology and changes in breeding needs, the application of information technology in livestock and poultry breeding would become more extensive and in-depth. This paper provides a reference for promoting the high quality and efficient development of the livestock and poultry industry.