摘要
为了促进中国智能渔业的发展,该文开发了一种基于物联网三层体系架构的螃蟹养殖基地监控系统,由水质监控、气象监控、视频监控、智能控制和远程服务中心组成,实现了对螃蟹养殖基地的本地和远程全方位智能监控。该系统采用STC15F2K60S2嵌入式单片机作为底层控制器芯片,通过RS485协议采集传感器数据,实现水质多参数(溶解氧、p H值、温度),气象多参数(温度、湿度、风向、风速、气压、雨量、光照)的监测;视频监控采用萤石云平台,实现养殖基的安防和养殖池塘水上、水下摄像;养殖设备采用PLC控制,实现投饵机、增氧机的智能控制。整个系统组网采用ESP8266 WIFI模块,接入AP基站,通过搭建的服务器管理程序,用户可以通过电脑浏览器或者手机APP在任何具备网络覆盖的地方远程浏览养殖基地数据。该系统应用于上海海洋大学崇明蟹种养殖基地,并对其通信稳定性、数据准确性和Android客户端进行测试,整个系统通信成功率为98%以上,溶解氧平均相对测量误差为0.016 mg/L,温度为0.031℃,p H值为0.023,其他各项指标均达到要求。系统运行到今,稳定可靠,能够满足水产养殖的需要,并可作为示范进行推广应用。
Aquaculture plays a vital role in our social and economic life,but its long production cycle,high labor intensity,low production efficiency,large waste of resources,and severe susceptibility to disease,significantly restrict the healthy development of the aquaculture industry.Facing a growing consumer market,traditional farming methods are increasingly unable to meet the demands of the public,creating great uncertainty in this crucial industry.This paper aims to develop a holistic management system for the crab farming,by combining technologies such as internet of things(according to the three-layer architecture of service layer,application layer and executive layer)and big data to systematically monitor and control aspects across the entire system.The system mainly includes the following aspects:1)Aquaculture center water quality and environment sensor network:A distributed sensor network is required for continuous and real-time monitoring of key water quality parameters(including dissolved oxygen,pH value,and temperature),and such a system would be arranged within the water,together with underwater cameras,to provide a constant stream of data for processing.Additionally,information from a second network of local meteorological sensors(such as temperature,humidity,wind direction,wind speed,barometric pressure,rainfall and illumination)will be gathered,and when combined with the underwater data,a complete data monitoring network will be formed based on the internet of things technology.2)Intelligent control network of farming center:Aquaculture equipment mainly includes aerators,feeders,and so on,with management approaches to these being low-tech,not optimized and wasteful currently.Through real-time analysis of water quality data,the growth cycle of aquatic crops,and their active morphological data can be fed into a learning model,which will determine the optimum oxygen content at any given moment and allow real-time precise control of the aerator.Furthermore,predicting the hunger time of the aquatic species wil
作者
刘雨青
李佳佳
曹守启
邢博闻
Liu Yuqing;Li Jiajia;Cao Shouqi;Xing Bowen(College of Engineering,Shanghai Ocean University,Shanghai 201306,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2018年第16期205-213,共9页
Transactions of the Chinese Society of Agricultural Engineering
基金
上海市科技兴农重点攻关项目(201314-2)
上海市青年科技英才扬帆计划资助(18YF1409900)
上海市科委2017年度"创新行动计划"地方院校能力建设项目"海洋环境监测用电浮标系统关键技术研究及应用示范"(17050502000)
关键词
养殖
监测
传感器
物联网
嵌入式单片机
无线通信
PLC
服务器
aquaculture
monitoring
sensors
internet of things
embedded micro-controller
wireless communication
PLC
server
