Abstract: Abstract: The behavioral information and body conditions of animals are significant in precision livestock farming. And they have a considerable relationship with animal’s welfare and diseases. Therefore, perceiving animals’ body and behavior information harmlessly is critical to livestock breeding. A research review of diseases detection, body conditions detection, individual identification, behavioral analysis, and so on with noninvasive monitoring technologies was presented focusing on some prevalent livestock, including pigs, cows, sheep and chicken. And a summary of the advantages and disadvantages of 3 noninvasive monitoring technologies, i.e. sensor monitoring, image monitoring and sound monitoring in all the aspects was presented in this review. Sensor monitoring has been applied in the monitoring of feeding and drinking behaviors of animals, the identification of location of free-ranging animals and daily behaviors monitoring. Various sensors such as temperature transmitter and acceleration transducer have been used for years, so sensor monitoring is more reliable compared with the other 2 technologies. However, it is hard to design stable and suitable sensors which can work for a long period of time under the bad conditions in animal husbandry. As for image monitoring, it has been applied in the estimation of weight and body contour of animals, behaviors monitoring and body temperature measurement. Images of animals are acquired by cameras and thermal infrared imager and then processed with different methods to mine information. Although image monitoring influences animals least, it is susceptible to lighting conditions sometimes. Algorithms need to be developed to improve accuracy of image identification and reduce environmental influence. Besides, sound monitoring in animal husbandry has been applied in diseases detection, emotional state recognition, daily behaviors monitoring and estimation of feed intake of free-ranging animals. Calls of animals can be easily obtained with microphones, while meanings and contents of which are essential to understand. Feature parameters and methods are fundamental to get animal’s sound meaningfully. The combination of Mel Frequency Cepstrum Coefficent (MFCC) and Hidden Markov Model (HMM) is proved to have good performance. Sound monitoring technology shows good identification performance in laboratory, while it is not as good as what scholars think due to the noisy animal husbandry filled with people talk, noise of clanging doors and wind. Thus, there is a need to update algorithms to improve identification accuracy in animal husbandry. Those 3 monitoring technologies are harmless to animals during the process of monitoring, while some supervision methods now available worldwide require device implanting or operation to the livestock, which is hence detrimental for increasing welfare. Whereas for the noninvasive monitoring technology, it can effectively cut down the manpower consumption, reduce the damage and stress response during the monitoring, lower the influence on the animals caused by observer, and then enhance the animal welfare. Sensor monitoring, image monitoring and sound monitoring perform well in different ways. It is worth a try to combine 2 or 3 of them to realize better monitoring performance in animal husbandry. Many attempts of noninvasive monitoring have been made and many products have been applied in some western countries, while Chinese scholars attempted to study it just decades years ago. Considering this, Chinese scholars should learn from western scholars and develop advanced noninvasive monitoring equipment.