Wang Yong, Wang Dianhong, Lu Qian, Luo Dapeng, Fang Wu
Faculty of Mechanical and Electronic Information, China University of Geosciences, Wuhan 430074, China.
Department of Geological Science and Engineering, Wuhan University of Engineering Sciences, Wuhan 430200, China.
Sensors (Basel). 2015 Jan 30;15(2):3116-37. doi: 10.3390/s150203116.
Aquatic debris monitoring is of great importance to human health, aquatic habitats and water transport. In this paper, we first introduce the prototype of an aquatic sensor node equipped with an embedded camera sensor. Based on this sensing platform, we propose a fast and accurate debris detection algorithm. Our method is specifically designed based on compressive sensing theory to give full consideration to the unique challenges in aquatic environments, such as waves, swaying reflections, and tight energy budget. To upload debris images, we use an efficient sparse recovery algorithm in which only a few linear measurements need to be transmitted for image reconstruction. Besides, we implement the host software and test the debris detection algorithm on realistically deployed aquatic sensor nodes. The experimental results demonstrate that our approach is reliable and feasible for debris detection using camera sensors in aquatic environments.
水生垃圾监测对人类健康、水生生境和水上运输至关重要。在本文中,我们首先介绍了配备嵌入式摄像头传感器的水生传感器节点原型。基于此传感平台,我们提出了一种快速准确的垃圾检测算法。我们的方法是基于压缩感知理论专门设计的,充分考虑了水生环境中的独特挑战,如波浪、摇曳的反射和紧张的能量预算。为了上传垃圾图像,我们使用了一种高效的稀疏恢复算法,其中只需要传输少量线性测量值用于图像重建。此外,我们实现了主机软件,并在实际部署的水生传感器节点上测试了垃圾检测算法。实验结果表明,我们的方法对于在水生环境中使用摄像头传感器进行垃圾检测是可靠且可行的。