NF Railways to use AI to prevent train-elephant collision

 - Sakshi Post

Guwahati, March 22 (IANS) Northeast Frontier Railway (NFR) has signed a Memorandum of Understanding (MoU) with RailTel Corporation of India Ltd, for installation of AI-based Intrusion Detection System (IDS), to avert train-elephant collisions on railway tracks, officials said.

Sabyasachi De, CPRO of NFR, told IANS, "We have been taking many initiatives to prevent and detect movement of wild animals, especially elephants, approaching the tracks. Installation of IDS in important sections is one such of them."

The MoU was signed on Monday in presence of NFR General Manager Anshul Gupta and other dignitaries in Maligaon in Guwahati.

"After the success of the pilot project on IDS that was undertaken in the Chalsa- Hasimara section of the Dooars area under Alipurduar division in West Bengal and Lanka-Hawaipur section under Lumding division in Assam, it has now been decided to install the system gradually in all other elephant corridors spread over NF Railway," the Railway officer said.

An official statement said that the system is based on Artificial Intelligence (AI) and existing optical fibres will be used as sensors to identify movements of wild animals at locations and alert control offices, station masters, gateman and loco pilots.

It uses a fibre optic-based acoustic system working on the principle of dialysis scattering phenomenon to sense the real-time presence of elephants on the railway track.

"The AI-based software can monitor unusual movements up to a stretch of 60 km. In addition to it, the IDS will also help in detecting rail fracture, trespassing on railway track and alert about disaster mitigation due to unauthorised digging near railway tracks, landslides near tracks etc.," the statement added.

The Railway officer also said that the pilot project has already been successful in saving the lives of many elephants approaching railway tracks from being hit by trains.

Disclaimer: This story has not been edited by the Sakshi Post team and is auto-generated from syndicated feed.

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