N.F. Railway to Conduct Airborne ‘LiDAR’ Survey on Lumding-Badarpur Hill Section
The Northeast Frontier Railway (N.F. Railway) has announced plans to carry out an Airborne Electromagnetic Lidar Survey in the critical sections of the Lumding-Silchar Hill area. This cutting-edge survey will take place during and after the monsoon season, aiming to provide a detailed analysis of the geological and soil conditions in the region, thereby enhancing safety and stability along this crucial railway corridor.
The survey will cover the stretch between Lumding and Badarpur, specifically from kilometer 45 to kilometer 125. The tender for the survey has been awarded to M/S Garudauav Soft Solutions Private Limited, a Noida-based company specializing in advanced surveying technologies. The survey will incorporate a combination of airborne ground surface assessments and subsurface electromagnetic studies, powered by an AI-driven digital twin monitoring system.
Using non-invasive sensors such as LiDAR, optical photogrammetry, infrared mapping, and ground-penetrating radar, the survey aims to monitor the dynamic geophysical landscape and subterranean environment. This comprehensive approach will help identify and analyze potential failure or critical areas that could pose risks such as landslides or slips. The collected data will be processed and analyzed using sophisticated AI software to ensure precise and actionable insights, informed the NF Rail through a press statement.
LiDAR technology, known for its ability to produce highly detailed and accurate elevation data, will play a central role in this survey. By using airborne or terrestrial LiDAR scanners, the team will capture detailed topographical information of the railway tracks, surrounding terrain, and relevant structures. This data is crucial for planning, designing, and maintaining railway infrastructure.
N.F. Railway officials emphasize the importance of such surveys in enhancing the safety, efficiency, and reliability of railway operations. By leveraging advanced technologies and AI-driven analysis, the railway aims to proactively address potential issues, thereby minimizing disruptions and ensuring a safer travel experience for passengers.
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