Frequently Asked Questions

ANPR (Automatic Number Plate Recognition) is a camera-based technology that detects, captures and converts vehicle licence plates into text for real-time or stored use. ANPR cameras are used by law enforcement, ITS, parking and tolling operators to identify vehicles of interest and automate processes.

An ANPR camera captures images of vehicle registration plates, applies recognition algorithms to extract plate text, and outputs structured metadata (plate, timestamp, lane, confidence, image snippet) that systems use for enforcement, access, analytics and automation.

Accuracy depends on camera optics, illumination, image quality, environmental conditions and the recognition algorithm. Modern ANPR cameras with deep-learning (like MAV’s AiAccurate™) deliver very high recognition rates in daytime and low-light conditions, and include confidence scores and contextual checks to reduce false positives.

ANPR is the overall technology/process of plate recognition (software + logic). An ANPR camera is the physical device that captures images and may also run recognition at the edge. MAV offers both edge ANPR (AiQ), mobile ANPR (MAV Mobile) and a specialised EV-bay ANPR system (BayIQ).

Yes. Edge-based ANPR cameras like MAV AiQ process plates on-device for ultra-low latency and reduced bandwidth. They can buffer events and forward data when networks are available, or integrate with local servers when required.

PlatePath™ links sequential captures into a single vehicle event, preserving continuity across cameras and lanes so operators get consistent journeys, multi-camera tracking and improved evidence integrity.

GhostPlate™ is MAV’s anti-tamper/evasion detection that flags manipulated, obscured or synthetic plates. It helps maintain trust in ANPR evidence by reducing deliberate evasion and plate fraud.

BayIQ uses high-accuracy ANPR to read every vehicle plate at the bay, applies AI rules to check EV authorization and charging session status, detects overstays beyond charging completion, and can automatically trigger enforcement workflows or penalty systems.

BayIQ supports multiple bays per unit (scalable configurations) — typical deployments support up to 20 bays per unit depending on site layout and camera coverage, with API integration available for enforcement and charging platforms.

Yes. MAV provides APIs and integration options (edge metadata output, REST/JSON, SDKs, ONVIF/RTSP where applicable) so ANPR camera events, images and metadata feed traffic management, access control, payment and back-office systems. Many ANPR integrations use standard API approaches for real-time data exchange.

Yes. ANPR camera events can trigger real-time enforcement workflows (notifications, barrier control, ticketing, penalty issuance) through integrated back-office systems or third-party enforcement platforms.

MAV devices support flexible connectivity (5G/LTE, Wi-Fi and wired Ethernet) to suit temporary/mobile and permanent deployments. BayIQ includes built-in cellular/Wi-Fi options for rapid deployment and remote management

ANPR systems process personal data (vehicle registration numbers). Operators should follow data-protection guidance, perform Data Protection Impact Assessments (DPIAs), apply retention policies, secure transmission and storage, and restrict access to authorised users. Authoritative guidance outlines organisational responsibilities for ANPR use.

Retain only what’s required for the stated purpose, apply role-based access controls, log access, anonymise where possible, and publish clear privacy notices. Consult local data-protection authorities and follow documented DPIA procedures before deployment.

Yes. MAV’s portfolio is tuned for different environments — BayIQ for bay/slow-speed sites, AiQ for embedded edge deployments and BayIQ/Mobile variants for multi-lane or fast moving traffic when configured with the correct optics and mounting. PlatePath™ also improves continuity across lanes and upstream/downstream cameras.

Yes. MAV ANPR cameras use IR/illumination, robust optics and AI recognition models to maintain high performance in low light, rain and varied weather. Performance varies with mounting, illumination and vehicle speed; MAV can advise on the optimal camera model and mounting for site conditions.

MAV supports REST/JSON APIs, common ONVIF metadata profiles where applicable, and SDK options for bespoke integrations. These tools allow ANPR camera metadata, images and events to be consumed by parking, ITS, enforcement and analytics systems.

Request a site survey and proof-of-performance trial: provide expected lane speeds, lighting, mounting positions and plate types. MAV offers demonstration units and captures sample performance metrics (recognition rate, confidence scores, false positives) to validate the ANPR camera for your environment.

MAV delivers full documentation (installation guides, API docs, configuration manuals), remote diagnostic tools, and configurable support plans (SLA tiers).

Yes. MAV Mobile is built for rapid, tactical deployment on vehicles, trailers and temporary structures, with mobile-optimised imaging, ruggedised hardware and high-speed capture capabilities.

By automating plate capture, evidence collection, access control and enforcement workflows, ANPR cameras reduce manual labour, improve bay availability and recover lost revenue (tolling/charging) — resulting in lower operating cost per event and improved ROI.

Many ANPR camera deployments can be upgraded (firmware, AI models) and some existing camera frames retrofitted with ANPR-capable modules, depending on ageing optics and processing capability. MAV can advise retrofit vs replacement based on site performance goals.

Scale by standardising on device models/configurations, centralising event ingestion and storage, using PlatePath™ for cross-camera continuity and applying consistent retention/privacy policies. Cloud or hybrid architectures with API-based integrations simplify large-scale deployments.

Key factors: recognition accuracy (especially with confidence scoring), anti-evasion features (e.g., GhostPlate™), integration APIs, edge processing vs server models, environmental suitability, support/SLA and proven deployments in similar ITS environments.

BayIQ is designed for rapid roll-out with browser-based setup, remote management tools and cellular/Wi-Fi connectivity options—making it suitable for fast deployments and field trials with minimal local infrastructure.

BayIQ can send events to penalty systems, access/barrier controllers, parking management platforms and enforcement back-offices to trigger tickets, warnings or barrier interlocks according to operator rules.

ANPR camera images and associated metadata are commonly used as evidence when systems follow good-practice deployment, maintain chain-of-custody, retain original images and logs, and adhere to privacy and data-protection rules. Features like PlatePath™ and GhostPlate™ increase evidential robustness.

ANPR-driven EV bay monitoring (BayIQ) prevents non-EV usage and overstays, increases bay turnover, and provides usage analytics to guide infrastructure investment—helping more drivers access chargers and improving charging utilisation.

MAV provides commissioning services, onsite/remote training, configuration workshops, and post-installation tuning to ensure ANPR camera performance meets operational KPIs.

Contact MAV sales or technical teams via the website to request a site survey, trial unit or technical datasheet.