Hawaii Builds a Data Driven Road Network With Bentley Blyncsy
Across the global road sector, one challenge refuses to go away. Governments spend billions building and upgrading highways, yet most of that infrastructure is still managed with delayed, fragmented and often outdated information. Engineers inspect roads periodically, asset registers get updated months late, and safety hazards frequently remain invisible until someone reports a crash, a complaint or a maintenance failure.
In that context, Hawaii’s decision to use Bentley Systems’ Blyncsy platform as the analytical backbone of its Eyes on the Road programme marks a quiet but important shift in how road networks can be managed. Instead of relying on sporadic inspections or fixed roadside sensors, Hawaii is turning everyday drivers into a constantly moving, always-on data collection system. The implications stretch far beyond the islands, touching on asset management, safety, maintenance economics and even how transport authorities justify public investment.
Hawaii’s roads face a particularly unforgiving mix of challenges. Salt air corrodes steel barriers. Tropical vegetation grows quickly and pushes into shoulders and sightlines. Heavy rain accelerates erosion and pothole formation. Add steep gradients and winding coastal alignments, and even small defects can create serious safety risks. Yet like most transport agencies worldwide, Hawaii DOT has had to manage those assets with limited staff and budgets while traffic volumes keep climbing.
What Bentley’s Blyncsy introduces is not simply better software. It represents a shift from scheduled, reactive maintenance to a live, evidence-based understanding of what is actually happening on the network each day. For infrastructure owners, that difference matters.
Turning Dash Cameras Into Infrastructure Sensors
The Eyes on the Road programme is built around a simple but powerful idea. Hawaii DOT, in partnership with the University of Hawaii, has provided 1,000 high-resolution dash cameras to residents across the state. These cameras record video automatically as drivers go about their normal routines, capturing everything from urban arterials to rural mountain roads.
Those recordings are not stored locally or reviewed by people watching endless footage. Instead, they are uploaded through a cellular connection to the cloud, where Bentley’s Blyncsy software applies machine learning and AI analytics to detect issues across the road network. Crucially, all footage is processed anonymously, avoiding the privacy pitfalls that often accompany crowd-sourced data projects.
From the perspective of a transport agency, the cameras become moving sensors that see far more than any fixed CCTV or roadside detector ever could. They capture guardrail damage, debris on the carriageway, vegetation encroaching on sightlines, shoulder erosion and other safety hazards. Because drivers travel the same roads day after day, the system builds up a constantly refreshed picture of how assets are performing and deteriorating.
That flow of information is what makes the system powerful. Instead of waiting for a quarterly inspection or a citizen report, Hawaii DOT can see emerging problems as they happen. Small defects get flagged before they become major failures. Dangerous debris or fallen branches can be cleared before they cause collisions. For engineers and maintenance planners, that is a fundamental upgrade in situational awareness.
From Raw Video to Actionable Intelligence
Video alone does not fix roads. The real value lies in turning millions of images into data that maintenance teams can actually use. That is where Blyncsy sits inside Bentley’s Asset Analytics portfolio.
Blyncsy applies machine learning to identify and classify features in each frame of video. It can distinguish between intact and damaged guardrails, clear and obstructed shoulders, or safe and hazardous roadside vegetation. Each detected issue is geo-referenced and time stamped, creating a live map of asset condition across the network.
Within the Eyes on the Road programme, that information is delivered to Hawaii DOT in near real time. Maintenance crews do not receive vague complaints or blurry photos. They get precise locations and asset types, allowing them to dispatch teams quickly and efficiently. Over time, the data also reveals patterns, showing which areas deteriorate fastest and where investment delivers the biggest safety returns.
Hawaii DOT Director Ed Sniffen has been clear about what this means for day-to-day operations: “Our crews have been working with Blyncsy to refine the machine learning algorithms to amplify our efforts to efficiently maintain our transportation infrastructure. The Eyes on the Road program will give us the information we need to get to damaged facilities quickly.”
That refinement process is important. Machine learning models improve when they are trained with real world data from the specific environment they are operating in. Hawaii’s mix of volcanic rock, coastal highways and tropical vegetation presents a very different visual landscape from a Midwestern US interstate or a European motorway. By working directly with maintenance crews, the system learns to recognise what matters most on Hawaii’s roads.
Why Proactive Maintenance Changes the Economics
For transport agencies worldwide, maintenance is where budgets either stretch or break. According to the World Bank and OECD, deferred maintenance is one of the biggest drivers of long-term infrastructure costs. Small defects, if left untreated, turn into expensive rehabilitation projects.
Traditional road management often struggles to catch those defects early. Visual inspections are labour-intensive. Fixed sensors only monitor specific locations. Public reporting apps tend to skew toward urban areas and more vocal users.
By contrast, a crowd-sourced dash camera network delivers coverage that scales naturally with traffic. The more people drive, the more data the system receives. That creates a continuous stream of intelligence without the cost of installing thousands of roadside devices.
For Hawaii DOT, the financial logic is straightforward. Spotting a damaged guardrail quickly avoids the higher cost of replacing a completely destroyed section. Clearing vegetation before it blocks sightlines reduces accident risk and liability exposure. Identifying debris before it causes a crash saves not only lives but also legal and insurance costs.
Mark Pittman, senior director of Transportation AI at Bentley Systems, frames the value in operational terms: “Bentley’s goal is to give transportation agencies real-time visibility into the state of their roadways. By combining AI and machine learning analytics with dash cam imagery, we are helping Hawaii DOT move from reactive to proactive maintenance to reduce risk, lower costs, and save lives.”
That move from reactive to proactive is not just a slogan. It aligns with a global push toward asset management frameworks such as ISO 55000, which emphasise risk-based decision making and lifecycle optimisation. Data-driven maintenance is no longer a nice-to-have. For agencies facing ageing networks and climate stress, it is becoming essential.
How Hawaii Fits Into a Global Digital Shift
Hawaii’s experiment sits within a much larger transformation of transport infrastructure. Around the world, road agencies are investing in digital twins, connected vehicle data and AI-driven analytics to understand how their assets perform in real conditions.
In Europe, initiatives like the EU’s C-ITS corridors and national road digital twin programmes are aiming to combine traffic, weather and asset data into unified management platforms. In the United States, the Federal Highway Administration has been pushing for performance-based asset management since the MAP-21 legislation, requiring states to track and report on infrastructure condition.
What makes the Eyes on the Road programme stand out is its cost-effective use of existing behaviour. Drivers are already on the roads. Dash cameras are already common for insurance and safety. Blyncsy simply turns that everyday activity into structured infrastructure intelligence.
That model is particularly attractive for regions with challenging geography or limited budgets. Remote rural roads, island networks and developing economies often struggle to deploy traditional sensor networks. A camera-based approach, backed by cloud analytics, offers a scalable alternative that can grow as participation increases.
There are also implications for resilience and climate adaptation. Hawaii’s roads are exposed to heavy rainfall, landslides and coastal erosion. Being able to spot early signs of damage after storms or extreme weather events allows agencies to respond faster and plan long-term mitigation strategies based on evidence rather than guesswork.
Building Trust Through Anonymity and Partnership
Any system that uses citizen data must address privacy and trust. The Eyes on the Road programme does this by processing footage anonymously and focusing only on infrastructure, not people or vehicles.
The involvement of the University of Hawaii adds another layer of credibility. Academic partners bring independent oversight, research expertise and a public interest mandate that helps reassure participants. For transport authorities elsewhere considering similar models, that partnership approach is likely to be just as important as the technology itself.
The programme also creates a subtle but meaningful change in how citizens relate to their roads. Drivers are no longer just users of infrastructure. They become contributors to its upkeep. That can strengthen public support for maintenance funding and safety initiatives, especially when people see problems fixed quickly based on data they helped generate.
What It Signals for the Construction and Infrastructure Sector
For contractors, consultants and investors, Hawaii’s use of Blyncsy points to a future where road maintenance is driven by live data rather than periodic surveys. That changes how work is scoped, tendered and delivered.
Maintenance contracts can be based on measured asset condition rather than rough estimates. Performance-based contracting becomes more practical when both sides have access to the same objective data. Asset managers can prioritise capital spending with far greater confidence, reducing waste and improving safety outcomes.
It also creates new opportunities for technology providers and system integrators. Dash cameras, connectivity, cloud platforms and AI analytics become part of the core infrastructure toolkit. Companies that can integrate those elements into reliable, secure and compliant systems will find a growing market among transport agencies under pressure to do more with less.
Bentley’s positioning of Blyncsy within its broader Asset Analytics portfolio reflects that trend. Infrastructure owners are no longer looking for isolated tools. They want connected platforms that link design, construction, operations and maintenance into a single data environment.
A Data Driven Future for Safer Roads
Hawaii’s Eyes on the Road programme is not about flashy technology or futuristic promises. It is about using practical, available tools to solve real operational problems. By turning ordinary vehicles into mobile infrastructure sensors, Hawaii DOT has gained a level of visibility that many agencies can only dream of.
The broader lesson is clear. Roads are no longer static assets managed through paperwork and periodic inspections. They are dynamic systems that can be monitored, analysed and optimised in near real time. As AI and connectivity continue to spread through the transport sector, programmes like this are likely to become the norm rather than the exception.
For the global construction and infrastructure ecosystem, that shift changes everything from how projects are designed to how they are funded and maintained. Data, not just concrete and steel, is becoming the foundation of safer, more resilient road networks.
