Information System for Railway Inspection using Drone and Image Processing

Abstract

Train is the main mode of transportation that we often use, the train itself can be used as a tool for shipping goods and mobilizing passengers, this transportation is very unique and has its own path in the form of steel strings across from hundreds of kilometers, railroad bearing structures currently exist which uses concrete and wood, the railroad is very vital and is an important supporting facility. The process of railroad monitoring is complex and complicated, takes a long time, the previous method is simple and conventional by tracing the railroad tracks manually or using a geometric gauge mounted direl or also known as railpod, railpod will follow the rails and will provide report if there is a train track that is damaged, broken or shifted, this research will create an image-based monitoring system using drones as a track monitor, another way is to take pictures using satellite data that will provide clear information about road conditions before being passed by the train, the railroad data processing system by using image processing can display visual responses up to cm in size, the response appears if there is a shift in the path then the system directly provides data in the form of location and shifting paths on the main computer, this system is more c eTat in checking and analyzing train track data with high accuracy and precision up to 90%, in addition to imagery from satellite images can use drones, drones themselves are very easy in maintenance and use and are able to cut production costs and even workplace accidents in the field workers themselves can be avoided because the drone is able to reach the track and railroad that is difficult for example through the tunnel or the railroad track along the hills and densely populated.

The development of RBL-STEM learning materials to promote the students analytical thinking skills in solving convolutional neural network problems

“…CNNs have been applied in the transportation industry to detect damage on railway sleepers. Trains are a crucial mode of mass transportation, and infrastructure maintenance is necessary to prevent accidents [10]. Digital technology can be utilized in railway safety through the detection and classification of railway sleepers based on the characteristics of the data set processed in the CNN application.…”

Railway Security System Design by Image Processing and Deep Learning Unmanned Aerial Vehicle

“…Today, it is frequently preferred in military, health, commercial, scientific studies, and civil aviation studies. In addition, more efficient systems can be designed by integrating deep learning and image processing techniques into unmanned aerial vehicles [12]. Deep learning is based on the principle that a set of pictures, video, or audio data is analyzed with certain algorithms to give an estimated value as output.…”