Mole Robot (MolBot): Development of Pipe Damage Detector Robot.
To get an improved image or to obtain any useful information from it, image processing is a method of implementing any operations on an image. In the method of classifying and detection of images, this process mainly contributes to the innovation of technology. The implementation of image processing in robots had been used in earlier but with different uses. Using FPV Camera 720p OIN in the projects lets it transmits live video streaming to any device attached to it. This paper shows the robustness of image processing as it detects defects on pipes. Covering the inner external part of the pipe, the robot can pass through inside the pipe. With the accuracy of 67%, the project will be tested in different pipes and drainages for the application.
Alon, A. S., Venal, M. C. A., Militante, S. V., Hernandez, M. D., & Acla, H. B. (2020). Lyco-frequency: A development of lycopersicon esculentum fruit classification for tomato catsup production using frequency sensing effect. International Journal of Advanced Trends in Computer Science and Engineering, 9(4), 4690–4695. https://doi.org/10.30534/ijatcse/2020/72942020
Anaya, J. J., Talavera, E., Jiménez, F., Serradilla, F., & Naranjo, J. E. (2015). Ad Hoc Networks Vehicle to Vehicle GeoNetworking using Wireless Sensor Networks. 27, 133–146. https://doi.org/10.1016/j.adhoc.2014.12.003
Cui, S., Zhao, L., Wang, Y., Dong, Q., Ma, J., Wang, Y., Zhao, W., & Ma, X. (2018). Using Naive Bayes Classifier to predict osteonecrosis of the femoral head with cannulated screw fixation. Injury, 49(10), 1865–1870. https://doi.org/10.1016/j.injury.2018.07.025
Hernandez, M. D., Fajardo, A. C., & Medina, R. P. (2019). A Hybrid Convolutional Neural Network-Gradient Boosted Classifier for Vehicle Classification. IJRTE Journal, 2, 213–216. https://doi.org/10.35940/ijrte.B1016.078219
Hernandez, M. D., Fajardo, A. C., Medina, R. P., Hernandez, J. T., & Dellosa, R. M. (2019). Implementation of data augmentation in convolutional neural network and gradient boosted classifier for vehicle classification. International Journal of Scientific and Technology Research, 8(12), 185–189.
Ibrahim, O., Elgendy, H., & Elshafee, A. M. (2011). Speed Detection Camera System using Image Processing Techniques on Video Streams. 3(6).
Lu, J., & Lu, Z. (2019). Multi Object detetction method based on Yolo and ResNet Hybrid Networks. 0–5.
Ma, H., Liu, Y., Ren, Y., & Yu, J. (2020). Detection of collapsed buildings in post-earthquake remote sensing images based on the improved YOLOv3. Remote Sensing, 12(1). https://doi.org/10.3390/RS12010044
Mohamad, S. (2017). fully autonomous pipeline cleaning robot.
Zhao, K., He, T., Wu, S., Wang, S., Dai, B., Yang, Q., & Lei, Y. (2019). Research on video classification method of key pollution sources based on deep learning. Journal of Visual Communication and Image Representation, 59, 283–291. https://doi.org/10.1016/j.jvcir.2019.01.015
Copyright (c) 2020 Journal La Multiapp
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.