Adaptive traffic control uses real-time data from sensors and cameras to continuously optimize signal timings. Instead of fixed-time schedules, the AI engine dynamically adjusts green-light durations based on actual vehicle density, queue lengths, and pedestrian demand—ensuring maximum throughput and minimal delays.

Yes. Our TMS integrates ANPR for automated traffic enforcement—detecting red-light violations, speeding, and unauthorized lane usage. ANPR data also supports toll collection, stolen vehicle tracking, and origin-destination studies for urban planning.

By using real-time data to adjust signal timings, provide dynamic route guidance, and proactively manage incidents. Our system balances traffic across alternative routes, reduces peak-hour bottlenecks, and improves intersection throughput by up to 30%.

Absolutely. Our Emergency Vehicle Priority (EVP) feature detects approaching ambulances, fire trucks, and police cars via GPS or strobe sensors. It preemptively clears their path by turning lights green along their route, reducing emergency response times significantly.

AI powers predictive traffic analytics, anomaly detection, pattern recognition, and dynamic optimization. It processes massive datasets to forecast traffic surges, detect accidents automatically, and recommend optimal control strategies—transforming reactive management into proactive planning.

Yes. Our TMS supports open standards (NTCIP, DATEX II, TLS) and legacy protocols. We can integrate with existing signal controllers, VMS boards, CCTV systems, and SCADA systems without requiring a complete overhaul, protecting your prior investments.

Cost varies based on scale—number of intersections, sensors, cameras, software modules, and deployment model (cloud vs on-premise). We offer flexible solutions from single-corridor pilots to city-wide rollouts. Contact us for a tailored quote based on your specific requirements.

Yes. We prioritize data security and privacy. Traffic data is anonymized for analytics, with strict access controls, encryption, and compliance with data protection regulations (GDPR, local laws). Video feeds are processed securely, and only aggregated, non-identifiable data is used for reporting.

Yes. Our system includes public transport priority modules that detect approaching buses and give them green extensions or early greens. This reduces transit delays, improves schedule adherence, and encourages sustainable mobility choices.

We offer both cloud-based and on-premise deployment. Cloud enables centralized management across multiple cities, automatic updates, and lower IT overhead. On-premise is preferred for low-latency critical operations and data sovereignty requirements. Hybrid options are also available.

Our TMS uses AI video analytics to detect stopped vehicles, wrong-way driving, debris, and accidents. It also integrates with vehicle sensors (speed, GPS) and crowd-sourced Waze data to validate incidents. Operators receive instant alerts with live video confirmation for rapid dispatch.

Yes. Advanced sensors and AI detect pedestrians and cyclists at crosswalks, adjusting signal phases to ensure safe crossing. The system can also integrate with smart crosswalk lighting and countdown timers to enhance safety for non-motorized road users.

Common sensors include radar-based vehicle detectors, inductive loops, infrared cameras, LiDAR, thermal cameras, and pneumatic tubes. Our platform is sensor-agnostic, allowing you to leverage existing sensors or choose the best mix for your environment and budget.

Deployment timelines vary: a pilot with 5-10 intersections can be operational in 4-6 weeks. City-wide rollouts (50+ intersections) typically take 6-12 months, including site surveys, hardware installation, software configuration, integration, and operator training. We provide phased implementation to minimize disruptions.