中国农业科学院农业信息研究所 中国农学会
Agricultural Information Institute of CAAS China Association of Agricultural Science Societies
En
Ch
中国农业科学院农业信息研究所 中国农学会 主办

AI检索

订阅

返回顶部
当前位置: 首页 > 文章 > 海水养殖水质监测与分析系统设计与实现 水产学杂志 2023 (4) 99-108
Position: Home > Articles > Design and Implementation of a Water Quality Monitoring and Analysis System for Mariculture Environment Chinese Journal of Fisheries 2023 (4) 99-108

海水养殖水质监测与分析系统设计与实现

作  者：
刘明剑;刘丽丽;朱宏升;张思佳
单  位：
中国人民解放军战略支援部队信息工程大学;设施渔业教育部重点试验室(大连海洋大学);大连海洋大学信息工程学院
关键词：
水产养殖;监测;分析与预测;SSM框架;LoRa
摘  要：
为了提高水产养殖过程中的信息化与智能化，揭示养殖水环境动态变化与养殖生产效率间的关系，基于SSM(Spring+Spring MVC+My Batis)框架研发了海水养殖环境监测与分析系统，实现了对养殖工厂内多监测点的pH、盐度和温度传感数据的实时采集、分析与存储，以及对养殖生产过程数据有效管理。该系统利用LoRa(Long Range Radio)低功耗物联网通信技术和Netty框架实现服务端与传感器的通信，将前端传感数据远距离传输至后端服务平台；采用SSM框架开发了Web后端服务器框架，前端使用Websocket技术推送数据，实现实时页面数据刷新。在此基础上，基于Pearson算法分析了监测传感指标数据之间的相关性，通过指数平滑算法预测传感数据变化趋势。验证结果表明该系统可以有效在线实时监测和预测养殖水质参数变化，为实现精准养殖提供重要支持。
译  名：
Design and Implementation of a Water Quality Monitoring and Analysis System for Mariculture Environment
作  者：
LIU Mingjian;LIU Lili;ZHU Hongsheng;ZHANG Sijia;College of Information Engineering, Dalian Ocean University;Key Laboratory of Environment Controlled Aquaculture(Dalian Ocean University), Ministry of Education;People's Liberation Army Strategic Support Force Information Engineering University;
关键词：
aquaculture;;water quality monitoring;;analysis and prediction;;SSM framework;;LoRa
摘  要：
In order to improve the informatization and intelligence of aquaculture process and reveal the relationship between dynamic changes in aquaculture environment and aquaculture production efficiency, a mariculture environment monitoring and analysis system is developed based on SSM(Spring+Springmvc+Mybatis)framework to realize the real-time collection, analysis and storage of pH,salinity and temperature sensing data at multiple monitoring points in an aquaculture farm, as well as the effective management of aquaculture production process data. The system uses LoRa(Long Range Radio)low-power internet of things communication technology and netty framework to realize the communication between the server and the sensor, and transmits the front-end sensing data to the service platform over a long distance.The back-end uses SSM framework to complete the development of Web back-end server framework, and the front-end uses websocket real-time push technology to push real-time data and refresh page data in time. On this basis, the correlation analysis relationship between monitoring sensor index data based on Pearson algorithm and the prediction function of sensor data change trend through exponential smoothing algorithm was completed. Finally, the verification test showed that the system effectively monitored and predicted the changes in aquaculture water quality parameters online and in real time, which provides an important support for enterprises to achieve precision aquaculture.

相似文章

导出引用
计量
文章访问数: 8
HTML全文浏览量: 0
PDF下载量: 0

所属期刊

推荐期刊

友情链接Friendly link
农业信息研究所Agricultural information institute 农业智能知识服务平台Agricultural intelligent knowledge service platform 农业学术服务平台Agricultural Knowledge Service System 中国知网CNKI 维普网VIP 万方WANFANG DATA
联系我们Contact us

电话Tell：010-82109652-808

邮箱E-mail：agrijournal@caas.cn

服务Service
关于我们About us 意见建议Opinions and suggest
版权说明Copyright
单位：中国农业科学院农业信息研究所 中国农学会 © 2017中国农业科学院农业信息研究所 ICP备案号：京ICP备09089781号-46