Paper Details
Object Detection In Railway Line Using Artificial Intelligence Techniques
Authors
K.Ramya, R. Sivaranjani
Abstract
Object detection in railway lines is a critical domain in the railway industry, aiming to enhance safety, operational efficiency, and the overall reliability of rail transportation. Various technologies and methods can be employed for object detection in railway lines, including but not limited to computer vision, LiDAR, radar, thermal imaging, and sensor networks. Machine learning and deep learning algorithms can be used for image and data analysis to classify and track objects such as trains, maintenance equipment, trespassers, or obstructions. Additionally, sensors and detectors can be strategically placed along the railway lines to capture critical data. This project delves into the advancements and challenges associated with object detection systems along railway lines. And aims to provide a holistic view of object detection in railway environments. It covers a wide range of topics, including the types of objects detected, the methods and technologies employed, real-world applications, and the future prospects of the field. Central to this system is the acquisition of data, primarily through high-resolution images and videos. These data sources originate from a variety of locations, including fixed cameras positioned along the railway tracks and cameras mounted on locomotives. This multi-source data collection is a crucial foundation for real-time monitoring and analysis, enabling the system to respond promptly to detected objects or potential obstacles. By combining data from multiple sources, the system provides a more comprehensive and accurate understanding of the railway environment, ensuring both safety and efficiency are prioritized.
Keywords
Citation
Object Detection In Railway Line Using Artificial Intelligence Techniques. K.Ramya, R. Sivaranjani. 2024. IJIRCT, Volume 10, Issue 4. Pages 1-3. https://www.ijirct.org/viewPaper.php?paperId=2408050