NFR deploys AI surveillance to protect elephants from train collisions

  • Industry News
  • Sep 12,23
Following a highly successful pilot project in the Chalsa-Hasimara section of the Dooars region and the Lanka-Hawaipur section under Lumding Division NFR has decided to gradually extend the system to all other elephant corridors under its jurisdiction.
NFR deploys AI surveillance to protect elephants from train collisions

The Northeast Frontier Railway (NFR) has implemented an Artificial Intelligence-driven surveillance system within elephant corridors to prevent train-related elephant fatalities. Covering north-eastern states, seven districts of West Bengal, and five districts in northern Bihar, NFR recently entered into a Memorandum of Understanding (MoU) with RailTel Corporation of India Ltd for the installation of an Intrusion Detection System (IDS) aimed at averting train-elephant collisions and facilitating disaster mitigation efforts.

Sabyasachi De, NFR Chief Public Relations Officer, highlighted the Railway's commitment to preventing and detecting the movement of wild animals, particularly elephants, near the tracks. The installation of IDS in crucial sections is one of these proactive measures.

Following a highly successful pilot project in the Chalsa-Hasimara section of the Dooars region under Alipurduar Division in West Bengal and the Lanka-Hawaipur section under Lumding Division in Assam, NFR has decided to gradually extend the system to all other elephant corridors under its jurisdiction.

This AI-based system utilises existing optical fibers as sensors to detect wildlife movements at various locations, promptly alerting control offices, station masters, gatekeepers, and train operators. It operates using a fiber optic-based acoustic system that relies on the dialysis scattering phenomenon to detect the real-time presence of elephants on the tracks. The AI software can monitor unusual movements over a span of 60 km.

In addition to its primary function of elephant detection, the IDS also aids in identifying rail fractures, unauthorised trespassing on tracks, and alerts regarding disaster mitigation, such as unapproved excavation near railway tracks or landslides near tracks.

The IDS system has already proven highly effective in saving the lives of numerous elephants that approach railway tracks. The number of elephant corridors has increased from 11 in 2012 to 80 in recent years.

The system provides early detection of elephant movements, offering a 30-40 minute advance warning, allowing for real-time alarms to be issued to station masters, central control systems, and level crossing gates. This enhances rail transport mobility in the NFR region by permitting faster speeds on elephant corridors.

Other benefits of the IDS system include the identification of digging near the tracks, detecting fibre cuts in the monitored sections, and tracking train presence for level crossing gates when they are open.

Furthermore, this system facilitates timely clearance from the Ministry of Forest and Environment for new railway lines and projects that pass through wildlife sanctuaries or national parks.

India is home to approximately 27,312 elephants, with Assam harbouring 5,719 of them, making it the second-largest population of pachyderms in India, after Karnataka (6,049).

In the previous year, 21 elephants lost their lives due to train-related accidents, electrocution, and other mishaps, while eight have perished thus far this year. Between 2012 and 2022, a total of 30 elephants lost their lives in Assam and 55 in West Bengal due to train collisions.

Officials from Assam's Forest and Environment department reported that 71 elephants, including calves, perished in 2021, primarily due to train collisions, poisoning, electrocution, and accidents such as falling into ponds, ditches, and lightning strikes. In the same timeframe, 118 people lost their lives in the state due to human-elephant conflicts, with 73 casualties resulting from elephant attacks last year and 45 fatalities recorded so far this year, including many women.

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