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Blyncsy by Bentley Systems For Safer Roadway Operations

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Author:Michael Johnson
Michael Johnson
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By putting automation and computer vision to work across Hawaii, the platform applies AI so transportation officials can rapidly find road wear, rank repair work, and protect travelers.

How the Blyncsy Solution Uses AI to Help the Hawaii Department of Transportation

As part of a campus‑backed road initiative, the state agency has brought in Blyncsy from Bentley Systems to support Eyes on the Road. According to the infrastructure engineering software company, the agency—working with the University of Hawaii—is deploying this analytics solution to elevate roadway safety statewide.

Roadway Maintenance and Asset Inventory From Dash-Cam Imagery

Under the Eyes on the Road project, one thousand no‑cost, high‑resolution dashboard cameras are offered to residents for installation in their vehicles to enhance public safety on streets. While people go about daily trips, the devices continuously capture video and, through a cellular link, send footage to the cloud. Residents continue their usual commutes, and the technology operates in the background. From that community‑sourced stream, overgrown vegetation, guardrail impacts, debris in lanes or along shoulders, and related hazards are flagged using AI and machine learning inside Bentley’s Blyncsy, with identities kept anonymous.

Actionable Insight for Roadway Management

Within Bentley Systems’ Asset Analytics family, Blyncsy turns dash‑cam imagery and other road visuals into actionable insights. By assessing the health of critical transportation assets, it supports asset inventory, smarter maintenance prioritization, and evidence‑based planning, and it can align with digital twin workflows. These insights help agencies allocate budgets where they matter most.

Spot Issues Faster and Prioritize Repairs to Keep Drivers Safe

During Eyes on the Road, detections move to the state transportation department almost in real‑time, giving crews at the Hawaii Department of Transportation the information needed to accelerate repair workflows. This near‑instant feedback loop reduces time to resolution. For drivers, cyclists, and people on foot, the transportation network becomes safer.

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