基于无线图像传感器网络的农田远程监测系统

为了实时获取农田图像和视频信息,提出了基于无线图像传感器网络的农田远程监测系统。针对当前图像传感器节点存在的不足,基于CMOS图像传感器和S3C6410嵌入式处理器设计了低成本、高分辨率的无线图像传感器节点,并研究了基于驱动层和应用层协作的分辨率实时调整算法,使得节点具备10种不同的分辨率,最高分辨率可达500万像素,而且分辨率可根据用户需求实时调整,以满足用户对不同图像精度的需求。采用Wi Fi技术构建无线图像传感器网络,并通过4G网络远程传输图像和视频到服务器。在服务器端开发了基于Web的可视化农田信息管理软件,实现对采集的数据进行有效存储、管理和应用,并为用户提供网络服务。部署了该系统并进行了长时间的运行测试试验,试验结果表明:系统可稳定地运行,能够根据远程指令采集并传输不同分辨率的图像,采集并传输1幅126 KB左右的图像平均耗时为5.36 s,网络平均丢包率为1.67%,客户端开启视频监控平均时延为3.48 s,视频播放流畅。

Remote Monitoring System for Farmland Based on Wireless Image Sensor Network

A remote monitoring system for farmland based on wireless image sensor network was put forward in order to obtain the farmland image and video information in real time. Aiming at the shortcomings of the current image sensor nodes, a low-cost high-resolution wireless image sensor node was designed based on CMOS image sensor chip and S3C6410 embedded processor. To ensure the stability and reliability of the node, the powerful embedded Linux operating system was employed as the software development platform. And based on this platform, a modular designing method was adopted to program the software system of the node in C/C++ language. Especially, a resolution adjustment algorithm based on driver and application layer cooperation was studied, which made the node had 10 different resolutions and the highest resolution was up to 5 mega pixels. More importantly, the resolution can be adjusted in real time according to the requirements of users when it was working, which made the node can meet the needs of users for different image accuracies. A wireless image sensor network was constructed by utilizing WiFi technology as well as the images and videos captured by the nodes were remotely transmitted to the server through the 4G network. In order to prolong the life cycle of the node, a solar power supply system was designed. A visual farmland information management software Web based was developed in order to effectively store, manage and use the data captured by the nodes, and a convenient method was provided for a user to remotely access the acquisition networks and the data stored in the server. The system was deployed and tested for a long time. The test results showed that the system could work stably, as well as capture and transmit images with different resolutions according to the remote instruction. Moreover, the average time to capture and transmit one image with size of about 126KB was about 5.36s, and the average packet loss ratio of the network was about 1.67%. In the tests, the average delay for the client to open video monitoring was about 3.48s, and the video playing was smooth. Finally, the power supply system based on the solar energy could provide a stable power supply for the nodes in the long work. The tests validated that the remote monitoring system designed in this work can automatically capture images and videos of farmland in real time, transmit them to the server remotely, and satisfy the requirement of users for remote monitoring farmland.