TrafficIQ converts roadway video into verified autonomous-vehicle observations, multimodal trajectories, and decision-ready analytics—inside a privacy-preserving confidential-cloud architecture.
AVSense is a camera-to-confidential-cloud platform designed for transportation agencies, researchers, and mobility programs that need auditable insight without a costly roadside AI appliance at every location.
Deploy a simple, infrastructure-friendly camera node. AVSense works independently of existing CCTV feeds and keeps field hardware focused on capture, encryption, and resilient transport.
Encrypted video enters an attested Trusted Execution Environment for filtering, clip extraction, redaction, and policy-controlled retention.
Vision-language models identify AVs and behaviors while object tracking converts motion into metric trajectories, speeds, and event records.
Each layer has a clear job, a defined trust boundary, and a measurable output.
Pole-mounted video with synchronized timestamps and calibrated views.
RoadsideEncrypted transport over fiber or managed cellular with store-and-forward resilience.
In transitAn attested TEE minimizes raw video, selects candidate windows, and applies privacy controls.
Protected boundaryAV recognition, behavior classification, multimodal tracking, and trajectory generation.
Cloud analyticsDashboards, event records, trajectories, APIs, and research-ready files.
Agency + researchDesigned to evolve. The pilot architecture centralizes filtering in a shared confidential cloud. At network scale, the same portable service can move to a protected on-site compact computer when bandwidth or operating economics favor local processing.
Identify known AV fleet vehicles from visible platform and sensor characteristics, with confidence scores and review workflows.
Classify vehicles, transit, freight, pedestrians, cyclists, and micromobility in the same roadway context.
Measure turning movements, lane changes, stop compliance, acceleration profiles, queues, conflicts, and defined safety events.
Generate object tracks, speeds, accelerations, lane context, and calibrated trajectories for independent analysis.
Export object-, event-, trajectory-, and interval-level data with timestamps, spatial references, confidence values, and metadata.
Add cameras and tenant configuration—not a ruggedized AI computer at every site. Shared cloud services expand as coverage grows.
TrafficIQ places privacy-sensitive filtering inside confidential compute. Raw imagery is decrypted only inside an approved, attested workload, then minimized before downstream analytics and data sharing.
Monitor AV operations, understand mixed-traffic effects, and support evidence-based policy and public communication.
Access documented, machine-readable datasets for independent validation, safety analysis, and longitudinal research.
Evaluate corridors, intersections, curb activity, and emerging automated-vehicle services with a common analytics layer.
Add privacy-preserving video intelligence to existing traffic-management and data platforms through open interfaces.
TrafficIQ Solutions, PLLC brings traffic engineering, intelligent transportation systems, computer vision, explainable AI, cryptography, and data governance into one deployment-focused team.
We build practical systems that help agencies observe emerging mobility, evaluate behavior, protect sensitive data, and make decisions that can stand up to technical and public scrutiny.
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