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The Current Application Status and Expectation of Machine Learning in Unmanned Farm

Baoju Wang, Yubin Lan, Mengmeng Chen, Baohu Liu, Guobin Wang, Haitao Liu

Abstract


With the successful application of machine learning in biological information, face recognition and other fields, it also provides power for the development of unmanned farms. Firstly, this paper expounds the basic concepts of unmanned farm and machine learning. At the same time, it analyzes the application of machine learning in planting and animal husbandry. This paper expounds its application in field weed identification, crop pest detection and crop yield prediction in planting. In animal husbandry, this paper analyzes the application status of machine learning in accurate identification and classification of fish, pigs and other livestock, fish feeding decision-making system and production line prediction of chickens and cattle. It is pointed out that machine learning has some disadvantages, such as difficulties in obtaining and marking training samples, performance defects of embedded chips, and lack of professionals. A general unmanned farm database should be established to study the expert system that can predict the health status of animals and monitor the growth environment of animals in real time. The embedded research of machine learning should be strengthened, and machine learning combined with 5G, big data, sensors and other technologies will become the research direction of unmanned farm in the future. This paper summarizes the application status, problems and prospects of machine learning in unmanned farm, hoping to provide references for further research in the future.

Keywords


Machine Learning; Unmanned Farm; Crop Management; Animal Husbandry; Accurate Identification; Production Forecast

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References


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DOI: https://doi.org/10.32629/jai.v4i2.492

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Copyright (c) 2021 Baoju Wang, Yubin Lan, Mengmeng Chen, Baohu Liu, Guobin Wang, Haitao Liu

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