Rail operator using AI to keep deer off tracks during Xmas

Upon detection of a deer, the system triggers a series of sound and light alarms. These alarms are designed to guide the deer away from the tracks, while an AI-enabled camera follows its movement until it is safely away.

Conventional deer deterrent methods on railways, such as train-mounted whistles and extensive fencing, have been found either unreliable or costly.

The tech behind this however, could stand to reduce such costs – including staffing. This is because Vision AI operates primarily through the processing and interpretation of visual data. Utilising advanced algorithms and machine learning techniques, it can analyse images and videos to identify, classify, and track objects or subjects within its field of view. This technology is akin to giving computers a form of sight, enabling them to understand and interact with the visual world around them.

AI is already being implemented in livestock management, breeding, and health monitoring, with AI devices on animals providing real-time data for informed decision-making, with examples stretching for dairy farming to meat farming.

Since its implementation in May, the Adds system has effectively deterred an average of 50 deer each week, according to LNER. In the same period, approximately eight deer-train collisions were anticipated in the test area, but only one such incident occurred.

Plans are underway to extend this system to other high-risk sections of the East Coast Main Line, which runs from London King's Cross to Edinburgh.

Danny Gonzalez, LNER's Chief Digital and Innovation Officer told of the effectiveness of this initial deployment, highlighting its ability to save time, reduce stress, and most importantly, protect deer.

The scheme, a collaborative effort between LNER and Network Rail, has been championed by route engineer Jo Priestly, who believes Adds will not only safeguard deer but also minimise passenger travel disruptions and delays.