Delhi Police used a facial recognition system to identify individuals with criminal records loitering near the Jantar Mantar protest site [1].
The deployment of this technology at a known site for public assembly signals an increasing reliance on biometric surveillance to monitor political gatherings. It raises questions about the scale of police monitoring and the intersection of public protest and law enforcement data.
Police sources said the system flagged around 400 people with criminal records between July 20 and July 24, 2026 [1]. However, other police sources said over 2,500 people with criminal records were identified through the facial recognition system at the site [2].
Authorities said the goal of the surveillance was to identify wanted criminals, absconders, and history-sheeters. The police also sought to find individuals categorized as "Bad Characters" who might infiltrate the protest to disturb law and order [2].
The Jantar Mantar site in Delhi is a frequent location for demonstrations. The use of the facial recognition system allows the police to cross-reference real-time imagery against existing criminal databases to detect known offenders in crowds [1], [2].
This operation occurred over a five-day window in July 2024 [1]. The discrepancy in the reported numbers, ranging from 400 to over 2,500 individuals, highlights varying accounts from police sources regarding the system's reach during the period [1], [2].
“Delhi Police used a facial recognition system to identify individuals with criminal records loitering near the Jantar Mantar protest site.”
The use of facial recognition systems (FRS) at Jantar Mantar demonstrates a shift toward proactive biometric surveillance in India's capital. By targeting 'history-sheeters' and 'Bad Characters' within protest crowds, the Delhi Police are integrating real-time surveillance with criminal databases to preemptively manage law and order. The wide gap in reported identification numbers suggests either a rapidly expanding database of flagged individuals or inconsistencies in how the police are reporting the efficacy of the technology.
