物联网环境下的船载航行数据实时采集

Real time data acquisition of ship navigation data under the environment of Internet of things

相较于其他交通手段来说,船舶运行的距离更远,想要完成数据的实时采集十分困难。传统的船载航行数据采集只是注重采集的精准度和采集的数量,很少关注实时采集这一问题。基于物联网环境研究了一种新的数据实时采集方法,设计了数据采集架构图,通过多信道的方式共同将数据反馈给中心系统,有效提高采集效率。采集模块共分为5个,分别为计划数据采集模块、设备数据采集模块、环境数据采集模块、人员数据采集模块以及辅助数据采集模块。通过神经元网络算法编写采集流程,并给出流程图。为了检验该方法的工作性能,与传统方法设置了对比实验,由实验结果可知,该方法的采集效率极高,反馈速度快,工作延时低,实时性能好。

Compared with other means of transport, the distance between ships is far away, so it is very difficult to collect data in real time. Traditional ship borne data acquisition is just the accuracy and quantity of reinjection acquisition, and little attention is paid to real-time acquisition. Based on the Internet of things, a new real-time data acquisition method is studied, and the data acquisition architecture is designed. The data is fed into the central system by multi channel mode, and the acquisition efficiency is improved effectively. The acquisition module is divided into five modules, including the planned data acquisition module, the equipment data acquisition module, the environment data acquisition module, the personnel data acquisition module and the auxiliary data acquisition module. The collection process is compiled through neural network algorithm, and the flow chart is given. In order to test the performance of the method, a comparative experiment is set up with the traditional method. The experimental results show that the method has high efficiency, fast feedback speed, low work delay and good real-time performance.