NEW DELHI: Stepping up efforts to address the problem of passengers struggling to book confirmed tickets, the Indian Railway Catering and Tourism Corporation (IRCTC) has deactivated more than three crore suspicious user IDs and placed another six crore under verification to prevent misuse. The railways' catering and ticketing arm has also expanded its AI-based kitchen monitoring system across its network to tackle complaints about food hygiene and quality.
Crackdown on Suspicious Users
Officials stated that 501 complaints have been lodged on the National Cyber Crime Portal pertaining to 4.18 lakh suspicious PNRs. IRCTC has also taken action against fraudulent digital identities by blocking 13,343 suspicious email domains during the year. These measures aim to curb the practice of touts and unauthorized agents booking tickets in bulk, which often leaves genuine passengers struggling to secure confirmed reservations.
AI-Enabled Kitchen Monitoring
More than 800 kitchens are now being monitored through 2,394 AI-enabled cameras that detect nine types of issues primarily responsible for unhygienic food in trains. These include head cap compliance, transparent gloves detection, mopping, wiping, rodents, flies, and cockroaches. A senior IRCTC official noted that the AI-enabled cameras can detect objects as small as an ant (7-8 mm). IRCTC served about 60 crore meals in 2025-26.
The official added that the surveillance is being expanded as more kitchens are added to the network. The cameras, supported by AI tools, quickly identify unhygienic practices and send alerts. Any issue flagged is sent to the concerned kitchen manager and escalates if not resolved. Action is taken against the responsible person within two hours, and the error is rectified, according to the official supervising the IRCTC war room.
Common Violations and Challenges
Failure to wear head caps is the most common hygiene-related violation detected by the AI system in kitchens. On average, the system generates around 350 alerts or error tickets daily. Officials noted that the most difficult period is during seasonal weather changes when food quality can be affected, and the maximum number of complaints is received during this time. While the AI system generates around 350 tickets a day, the effective error rate is about 10%.
