# PSCA Intensifies Crackdown on Fake Number Plates > Source: > Published: 2026-06-06 18:21:43.050565+00:00 Photo: techjuice.pk · rights & takedowns The Punjab Safe Cities Authority (PSCA) used its AI-powered Safe City surveillance network to identify and trace more than 170 suspicious vehicles with fake, cloned, or tampered number plates over the past month, according to a PSCA spokesperson reported by Dawn, ProPakistani, TechJuice and others. The authority says its automated alert system detects suspicious or unregistered plates in real time and relays data to nearby police units for prompt action. PSCA sources quoted in local coverage warned that altering or using fake number plates is a criminal offence that may lead to FIR registration, vehicle impoundment, and other legal proceedings, and urged citizens to use only original, legally registered plates. What happened Punjab Safe Cities Authority (PSCA) has identified and traced more than 170 vehicles using fake, cloned, or tampered number plates during the past month, according to a PSCA spokesperson quoted in Dawn, ProPakistani, TechJuice, the Daily Independent, and MinuteMirror. The reporting says PSCAs Safe City network uses AI-enabled cameras and an automated alert mechanism to detect suspicious, altered, or unregistered number plates when they appear within camera range. Per the coverage, the system then shares alerts with nearby police units and virtual patrolling officers for follow-up. Local reports also cite PSCA warnings that using fake or tampered plates can result in FIR registration and other legal proceedings; the spokesperson told Dawn, "Citizens are advised to ensure use of original and legally registered number plates on their vehicles and avoid any unauthorised modifications," and that PSCA maintains a "zero-tolerance policy" on such offences. Technical details Editorial analysis: the public reporting focuses on an operational description rather than technical specifications. The sources do not publish model names, vendor details, accuracy figures, or the false-positive/false-negative rates of the plate-recognition system. Coverage describes an "automated alert system" and "AI-powered cameras" but does not provide implementation details such as the use of optical character recognition (OCR), multi-angle image aggregation, or cross-referencing with registration databases. For practitioners, that absence leaves open questions about detection thresholds, how plate-image quality or occlusion are handled, and what human review workflows are in place. Context and significance reporting illustrates a broader pattern where municipal "safe city" initiatives deploy computer-vision systems for automated plate recognition and real-time enforcement. Such deployments can scale monitoring across large road networks and reduce manual screening workload. At the same time, comparable systems internationally raise operational and governance considerations: accuracy under varied lighting and weather, potential for false matches against registration lists, data retention and access controls, and oversight mechanisms for police use of automated alerts. What to watch For observers: look for follow-up reporting or official statements that disclose technical performance metrics (detection accuracy, false-positive rates), integration details with vehicle registration databases, and legal or privacy frameworks governing camera footage and automated alerts. Also monitor local police records for enforcement outcomes stemming from alerts, such as counts of FIRs or impoundments tied to automated detections, which will clarify how the technology affects on-the-ground policing. If PSCA or partner agencies publish procurement or technical documents, those will be the primary sources to evaluate system limitations and bias risks. Bottom line PSCAs public reporting, echoed across multiple local outlets, documents a province-scale use of AI-enabled plate detection that produced over 170 flagged vehicles in a month. The coverage provides operational claims and legal warnings but does not supply technical validation or governance details necessary for assessing system reliability and civil-rights implications. Scoring Rationale Local but notable deployment of AI-driven license-plate recognition that affects law enforcement workflows and raises operational and governance questions relevant to practitioners. Coverage is operational, not technical, so impact is meaningful but regionally constrained. Practice interview problems based on real data 1,500+ SQL & Python problems across 15 industry datasets — the exact type of data you work with. Try 250 free problems