Research Projects
Building Safe spaces: UAV-based inspections of leaves on the rail lines using Artificial Intelligence
Building Safe spaces: UAV-based inspections of leaves on the rail lines using Artificial Intelligence
The railway environment needs to be inspected continuously for serving the communities with the goal of putting the safety of the passengers and freight as first and foremost. Railway inspections include monitoring critical railway infrastructures such as leaves on the rail lines for low adhesion. Sustained and periodic monitoring of leaves on the rail lines is a necessity for avoiding catastrophic failures such as derailments thus, leading to delays, loss of life and property. Alongside, leaves on the rail lines causing low adhesion lead to circuit issues and station overruns thus costing the economy.
Therefore, Unmanned Aerial Vehicles (UAVs) (drones) integrated with deep learning techniques play an important role in this day and age in the context of facilitating automated identification, monitoring and cleaning purposes of leaves on rail lines in railway environment as they save cost, time, provide reliability, and good coverage.
These operations also manage to attract researchers/ stakeholders such as UK railways, EU railways and Indian rail companies thus, estimating saving millions of lives and money during rail journeys.
CfACTs is a Marie Sklodowska-Curie Action (MSCA) COFUND research centre, co-led by Prof Jian Chang and Prof Jian J Zhang, of the Bournemouth University’s National Centre for Computer Animation (BU NCCA); CfACTs runs from October 2020 to September 2025.
