Indian Railways has introduced a new Artificial
Intelligence (AI)-based system to improve freight train security and make the
inspection of freight wagons faster and more reliable. The Northeast Frontier
Railway (NFR), in collaboration with IIT Guwahati, has developed Project
DRISHTI, an AI-powered solution designed to monitor freight wagon doors, locks
and seals.
According to Kapinjal Kishore Sharma, Chief
Public Relations Officer (CPRO) of NFR, Project DRISHTI uses AI, high-speed
cameras, intelligent lighting and secure networking to inspect freight wagons
as trains pass through designated monitoring points.
The technology is designed to identify wagon
numbers and check the condition of their doors, locks and seals. It can help
detect whether a seal or lock is intact or whether a possible irregularity
needs attention.
As a freight train passes through a monitoring
point, cameras capture images of the wagons. The AI-based system then analyses
the images to check key details, including the condition of wagon doors, locks
and seals. The inspection findings can also be recorded digitally, allowing
railway staff to identify and respond to possible issues more quickly.
Freight trains carry essential commodities and
support industries, agriculture and supply chains across the country. For
Northeast Frontier Railway, freight transportation is particularly important
because difficult geographical and environmental conditions can make road
transportation challenging.
Ensuring that wagon doors are properly closed
and securely sealed is therefore an important part of protecting consignments
during transit. Earlier, checking freight wagon doors, locks and seals was
largely a manual process. This could be difficult and time-consuming,
particularly at night or during adverse weather conditions. Project DRISHTI has
been designed to reduce dependence on manual inspection by using technology to
carry out checks more quickly and consistently.
The AI-based monitoring system is expected to
support frontline railway personnel, including RPF and commercial staff. By
providing faster information about possible problems with wagon doors, locks or
seals, the system can help staff take timely action and reduce delays in
freight operations.
“The technology-enabled monitoring is expected
to help safeguard consignments, reduce delays and facilitate the work of
frontline railway personnel, including RPF and commercial staff. By enabling
faster identification of possible irregularities, the system is expected to
strengthen freight monitoring while reducing the dependence on manual
inspection alone,” Sharma said.