India's National Highways Authority (NHAI) operates more than 1,200 toll plazas that collectively process over 20 million FASTag transactions per day, yet each plaza historically ran Toll Management Systems from a dozen different vendors, each with its own data model and reporting format. There was no single view of equipment health, lane uptime, or revenue trends; boom barrier failures, RFID scanner malfunctions, and ANPR camera outages often went undetected for hours, and the first signal of trouble was typically a public complaint rather than a system alert. ANPR feeds generated terabytes of footage daily with no automated processing, and 100% ETC lane uptime mandates plus scheme-based operator compensation needed auditable compliance records the existing infrastructure could not produce.
Auriga IT architected and delivered a modular, cloud-native platform called the Toll Monitoring Control Center (TMCC), unifying IoT monitoring, data engineering, video analytics, and business intelligence into a single operational backbone for the national highway network. The platform was extended with a rules-based compensation management system that turns government scheme policy into automated, formula-based payout calculations for toll plaza operators across the country.
Industrial-grade IoT devices were deployed at every plaza to monitor boom barriers, RFID readers, CPUs, and ANPR cameras, with each device sending a continuous health ping to the cloud. A threshold-based alert system fires when any device exceeds three minutes of downtime, triggering escalation before a complaint reaches the helpdesk and shifting maintenance from reactive to proactive across all 1,200+ plazas. The architecture is vendor-agnostic: regardless of which TMS vendor deployed a given plaza, its data arrives in a unified format through a single distributed data lake.
The platform's streaming backbone runs Apache Kafka and Spark Streaming pipelines that process over 20 million transactions per day with deduplication, anomaly detection, and archival, supported by containerized microservices on Kubernetes with autoscaling, load balancing, and role-based access control across AWS, Azure, and GCP. ANPR camera and lane surveillance feeds connect to GPU-enabled pipelines running YOLO and SSD deep learning models for vehicle classification, counting, and anomaly detection, handling more than 10TB of video data daily without human review. A custom BI layer built with Power BI, Tableau, and bespoke UI frameworks delivers role-specific dashboards covering toll performance, equipment uptime, traffic volume, and revenue trends, with forecasting algorithms predicting equipment failure risk, peak congestion windows, and revenue anomalies. The platform powers a centralized Command and Control Center running around the clock, with automated alert and escalation workflows tied to service SLAs that reduce both Mean Time to Detect and Mean Time to Resolve across the network.
The compensation management system reads scheme usage data from the TMCC data lake, applies eligibility rules defined by the Government, runs a formula-based calculation accounting for vehicle class, trip category, applicable fare, and qualifying journey count, and generates verified compensation outputs with no manual reconciliation required. The formula calculates against the incremental impact of scheme usage rather than total traffic volume, so operators are compensated only for scheme-attributable revenue displacement. Every output is traceable to the underlying trip data, eligibility decision, and formula applied, creating a full audit trail from scheme event to compensation figure across hundreds of plazas.
The same architectural pattern - cloud-native data platform, IoT monitoring, streaming ingestion, video intelligence, and a rules engine that encodes policy directly into computation - applies to ports, railways, utilities, and urban transport operators, since the underlying problem of unifying fragmented vendor systems into real-time visibility and audit-ready compliance is common across national infrastructure operators worldwide.