基于分布式对象的蛋鸡舍设施养殖数字化智能监测系统

为了在非人为干扰条件下,可实时监测预警蛋鸡生产环境和生产过程,保障动物福利,本文基于可被远程调用的分布式对象的3Tiers物联网软件体系结构,将传感器技术和云技术结合在一起,设计了蛋鸡舍设施养殖数字化智能监测系统。3Tiers物联网软件架构考虑了大量的异构数据集成和对传感器设备的监测、远程交互性能的需求,满足了本研究中对规模化蛋鸡生产过程的研究要求。系统实现了规模化蛋鸡舍的实时生产环境参数采集和视频监控、生产资料管理、生产过程管理、基础信息管理、统计管理、预警设置管理、系统管理和推送管理功能。考虑到温热环境对蛋鸡健康福利和生产性能有着重要的影响,利用系统中的大量环境数据,对中国农业大学上庄实验站大鸡舍内的小气候环境舒适度进行评价,并结合产蛋率、死淘率和耗料,在黄山养殖场对环境舒适度评价进行了验证。通过对上庄鸡舍24 h周期内和2016年11月—2017年4月的环境情况进行分析,结果表明实验蛋鸡舍内的小气候环境温湿指数始终小于70,蛋鸡群始终处于舒适区;而通过对养殖场鸡舍2016年7—10月份的环境数据和生产数据进行分析,验证了当蛋鸡处于舒适区时,产蛋率提升,死淘率下降,耗料更接近标准。

Intelligent Monitoring System Based on Distributed Object for Layer House

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.