智慧农业（中英文）2026，Vol.8Issue(1)：86-103,18.
生猪智能检测技术研究进展与未来展望
Research Progress and Future Prospects of Pig Intelligent Detection Technology
摘要
Abstract
[Significance]The pig industry is a key sector of animal husbandry.With the continuous expansion of farming scale,tradition-al manual inspection methods can no longer meet the demands of modern production in terms of efficiency,accuracy,and animal wel-fare.In recent years,intelligent pig monitoring technologies based on multi-source data,such as images,depth information,sensors,and sound,have developed rapidly,providing new solutions for health monitoring,behavior recognition,weight assessment,and phys-iological state management during the farming process.As a crucial foundation for upgrading the pig industry toward intelligent and precise farming,it is of significant value to systematically review the current research status,application progress,and future trends of the technological system.[Progress]This paper focuses on the main research areas in intelligent pig monitoring,systematically sum-marizes the commonly used data types and their applications in farming scenarios from the perspective of matching data sources with application objectives.First,research based on infrared images mainly focuses on non-contact acquisition of body temperature infor-mation,which is used for disease early warning and health monitoring,offering clear advantages in reducing stress responses and in-creasing monitoring frequency.Second,visible-light images are widely applied in behavior recognition and health analysis,supporting automated identification and quantification of behaviors such as feeding,resting,and aggression,thereby facilitating dynamic under-standing of pig herd behavior patterns and changes.Third,depth images and three-dimensional information demonstrate unique value in body measurement extraction and weight estimation,promoting the development of non-contact,continuous weight monitoring.Fourth,wearable sensors enable continuous monitoring of pig's health,lameness risk,and daily behavioral rhythms by recording phys-iological data such as body temperature,acceleration,and feeding activity in real time.Finally,audio signals,an emerging data type in recent years,have shown potential in monitoring abnormal sounds such as coughing,providing a new approach for the early detection of respiratory diseases.On this basis,this paper further summarizes the research and application of intelligent detection equipment.Current equipment presents a development trend in two aspects:one focuses on single indicators such as body temperature and weight,characterized by precise collection and rapid feedback;the other integrates multiple functions including image acquisition,body temperature detection,behavior recording,and identity recognition through mobile platforms such as inspection robots,enabling full-scenario and all-weather intelligent detection and improving the automation and refinement level of pig farm management.With the growth of industrial demand,various types of equipment are gradually moving from laboratories to commercialization,providing important support for intelligent breeding.[Conclusions and Prospects]Despite the rapid development of intelligent pig detection tech-nology,multiple challenges still exist.At the data level,interference from lighting,occlusion,and noise in different scenarios can af-fect the stability of detection results;at the hardware level,some equipment suffers from high costs and needs improvement in reliabil-ity;at the model level,differences across pig farms,breeds,and growth stages still lead to insufficient adaptability;at the application level,data continuity,system stability,and equipment maintenance costs in large-scale scenarios require further optimization.These factors collectively restrict the large-scale promotion of intelligent detection technology in the industry.Future research directions will exhibit the following common trends:First,achieving contactless operation and multi-scenario adaptability to minimize disturbance to pigs and enhance stability in complex environments.Second,advancing the integration of multimodal data fusion and deep learning to establish stronger correlations among multi-source data such as images,sensors,and audio.Third,developing individualized health and growth models to provide a scientific basis for precision feeding and management.关键词
生猪智能检测/智能养殖/多源数据/智能检测技术/智能检测装备Key words
intelligent pig detection/intelligent farming/multi-source data/intelligent detection technology/intelligent detec-tion equipment分类
农业科技引用本文复制引用
肖德琴,吕玉定,黄一桂,爨凯旋..生猪智能检测技术研究进展与未来展望[J].智慧农业（中英文）,2026,8(1):86-103,18.基金项目
国家重点研发计划项目(2021YFD200802) （2021YFD200802）
广东省现代农业产业体系智慧农业关键共性技术创新团队(2024CXTD28) National Key Research and Development Program(2021YFD200802) （2024CXTD28）
The Innovation Team of Key Common Tech-nologies for Smart Agriculture under the Guangdong Modern Agricultural Industry System(2024CXTD28) （2024CXTD28）
