Graduate School of Integrated Science and Technology, Shizuoka University, Hamamatsu 432-8011, Japan.
Department of Information Science, Aichi Institute of Technology, Toyota 470-0392, Japan.
Sensors (Basel). 2023 Jan 10;23(2):793. doi: 10.3390/s23020793.
To reduce the cost of inspecting old sewer pipes, we have been developing a low-cost sewer inspection system that uses drifting wireless cameras to record videos of the interior of a sewer pipe while drifting. The video's data are transmitted to access points placed in utility holes and further transmitted to a video server where each video frame is linked to its capturing position so that users can identify the damaged areas. However, in small-diameter sewer pipes, locating drifting nodes over the full extent of the pipeline using Wi-Fi-based localization is difficult due to the limited reach of radio waves. In addition, there is the unavailability of a GNSS signal. We propose a function to link each video frame to a position based on linear interpolation using landmarks detected by the camera and image processing. Experiments for testing the accuracy of the localization in an underground sewer pipe showed that all utility holes were successfully detected as landmarks, and the maximum location estimation accuracy was less than 11.5% of the maximum interval of landmarks.
为了降低检测旧污水管道的成本,我们一直在开发一种低成本的污水检测系统,该系统使用漂流无线摄像头在漂流时记录污水管道内部的视频。视频数据被传输到放置在公共设施井中的接入点,并进一步传输到视频服务器,在该服务器中,每个视频帧都与它的捕获位置相关联,以便用户可以识别损坏区域。然而,在小直径的污水管道中,由于无线电波的有限范围,使用基于 Wi-Fi 的定位来定位整个管道上的漂流节点是困难的。此外,还没有 GNSS 信号。我们提出了一种使用摄像头检测到的地标和图像处理进行线性插值将每个视频帧与位置相关联的功能。在地下污水管道中测试定位准确性的实验表明,所有公共设施井都成功地被检测为地标,最大位置估计精度小于地标最大间隔的 11.5%。