分辨率实时可调的无线图像传感器节点设计与试验

针对目前用于农业图像获取的图像传感器节点分辨率偏低、分辨率固定不可调的现状,设计并实现一种分辨率实时可调的无线图像传感器节点。节点的硬件平台由ARM处理器S3C6410和CMOS图像传感器OV5642组成,并集成了Wi Fi模块和4 G模块。设计了太阳能供电系统为节点供电。采用嵌入式Linux搭建节点的软件平台,设计了基于驱动层和应用层协作、多线程并发的分辨率实时调整算法,并在应用层实现了分辨率实时调整、图像采集、图像压缩和无线传输等功能。为了验证节点的性能,将节点部署在农田进行了长时间的测试试验。测试结果表明,节点具有7种不同的分辨率,最高可达500万像素,更重要的是它在工作过程中可接收远程用户的指令,实时调整分辨率,进而采集不同精度的农作物图像,并远程传输到服务器端。试验表明所设计的节点可满足用户获取不同精度农业图像的需求。

Design and experiment of wireless image sensor node with real-time adjustable resolution

Abstract: In order to overcome the problems of low and non-adjustable resolution existing in wireless images sensor nodes applied in agricultural images acquisition at present, a wireless image sensor node with real-time adjustable resolution was designed and realized in this paper. The node was composed of an image acquisition module, a processor module, a wireless communication module and a power module. The node needed to not only capture, compress, and transmit image data, but also perform multiple task schedules and network protocols, so a powerful ARM (advanced RISC machines) processor S3C6410 was chosen as the processor module of the node. Considering the cost and power consumption, a CMOS (complementary metal oxide semiconductor) type image sensor chip was chosen to design the image acquisition module of the node. The design of image acquisition module included image sensor PCB (printed circuit board) design, chip pin interface design, appropriate lens selection, and development of the sensor chip driver. In order to monitor a larger area of the crop and remotely transmit crop images, the node integrated a WiFi (wireless fidelity) or 4G (the 4th generation) module. A solar power supply system was designed to make the node work stably in the field for a long time. To ensure the stability and reliability of the node, the powerful embedded Linux operating system was employed as the software development platform, and a modular designing method was adopted to program the software system of the node in C/C++ language based on this platform. In order to realize real-time adjustment of the resolution, an algorithm of resolution real-time adjustment based on driver layer and application layer collaboration and multi-thread concurrence was proposed, and all the functions of resolution real-time adjustment of image acquisition, image compression and image transmission were realized in the application layer of software system. In order to verify the performance of the node designed, a series of tests were conducted in Cencun experimental base of South China Agricultural University and Guangdong Dongsheng Farm (Panyu) from April to September in 2016. In the tests, 7 nodes were deployed in the farmland to form an acquisition and transmission network based on WiFi and 4G technologies. To ensure the nodes work stably in the field, where the climate was changeable and the infrastructure was absent, the nodes were encapsulated in a waterproof spherical shield, and a solar panel plus rechargeable batteries was used to supply power for them. The nodes were tested from the aspects of multi-resolution capability, real-time adjustment capability, image acquisition and transmission performance (transmission time and packet loss rate), and the availability of node energy. The test results indicated that the node had 7 different resolutions and its highest resolution was up to a pixel of 5 M, and more importantly, it could adjust its resolution in real time under the control of a remote user, then capture images with different resolution, and finally transmit them to the remote server. The time consumed to capture, compress and transmit 4 images with different resolution of 640×480, 1280×1024, 2048×1536, and 2592×1944 was 4.67, 8.77, 15.38 and 22.74 s respectively, and the average transmission packet loss ratio of 4 images was less than 1%. The tests validate the node designed in this work can capture crop images with different resolution in real time and transmit them remotely, and satisfy the requirement of different users for different crop image precision.