The Realization of Pig Intelligent Feeding Equipment and Network Service Platform

文献类型： 外文期刊

第一作者： Ma, Weihong

作者： Ma, Weihong;Fan, Jinwei;Ma, Weihong;Zhao, Chunjiang;Wu, Huarui;Ma, Weihong;Zhao, Chunjiang;Wu, Huarui;Ma, Weihong;Zhao, Chunjiang;Wu, Huarui

作者机构：

关键词： Management of pigs; Internet of things; Monitoring and warning; Reasoning and decision-making; Network service platform

期刊名称：COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE XI, CCTA 2017, PT II

ISSN： 1868-4238

年卷期： 2019 年 546 卷

页码：

收录情况： SCI

摘要： Proper feeding of pigs can increase the litter size and improve the disease resistance level. In recent years, intelligent and automatic equipment, which can collect feeding times, feed intake, feed time and growth conditions, have been applied to the pig feeding. Most equipment can feed both manually and automatically. Not enough attention has been paid to one pig's health condition, living environment, and dietary status, which should be considered together in order to make an accurate decision on the feed intake of each pig. At the same time, there are not many network service platforms in China which can effectively manage the intelligent and automatic equipment remotely and simultaneously. To improve pigs' productivity and enhance the intelligent management of pigs, wireless sensor network, intelligent sensors, network service platform, and reasoning and decision-making technology have been utilized in the management of pigs in multiple areas throughout China. Single feed intake, living environment information, fitness, and weight for pigs throughout China with different conditions were collected in the network service platform by using the intelligent feed equipment which had several different sensors. Meanwhile, the network service platform could recognize the identity of each pig and provide accurate feed remotely. The network service platform would send a text message or an audible and visual alarm to inform the pig keeper whether the pig's feed intake was proper. According to the reasoning and decision-making model we built in the network service platform, we can remotely obtain through the platform more accurate information within seconds as to each pig's feeding status. Moreover, the experiment showed that the feeding container was the key factor that influenced the precision of feeding, and the measured value was closely approximate to the target value with error correction.

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