Intelligent Monitoring System Based on Distributed Object for Layer House
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    Abstract:

    In view of the present situation that the development of the layer breeding industry from scattered to intensive and large-scale, the traditional breeding methods cannot meet the requirements of the development. In order to real-time monitor and early warn the egg production environment and the production process of laying hens under the conditions of non-human interference, as well as the protection of animal welfare, 3Tiers, the networking software architecture based on distributed objects that can be called remotely, combining the sensor technology and cloud technology, was used to develop layer house real-time monitoring system. 3Tiers networking software architecture took integration of large amounts of heterogeneous data, the demand of monitoring sensors and remote interactive performance with sensors into consideration, which totally met the requirements of scaling farming. The system realized scaling layer house real-time production environment parameters acquisition and real-time video monitoring, production management, production process management, basic information management, statistical management, early warning management, system management and push management functions. Considering the thermal environment had an important impact on the health and welfare of laying hens and production performance. A large number of environmental data in the system was used to evaluate the microclimate environmental comfort in China Agricultural University Shangzhuang Station. Then egg production rate, death rate and feed consumption of a henhouse in Huangshan were used to verify the evaluation of the environmental comfort. The results showed that during the 24h cycle and the whole period from November 2016 to April 2017, the value of the microclimate environment in the layer house of Shangzhuang Station was less than 70, which meant that the group of laying hens was always in the comfort zone. With the environmental data and production data analysis of a henhouse from July to October of 2016, it verified that when laying hens were in comfort zone, laying rate was increased, the death rate was decreased, and the feed consumption was more close to the standard.

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History
  • Received:January 25,2017
  • Revised:
  • Adopted:
  • Online: October 10,2017
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