Case study: Hawaii DOT saves nearly $1 million per year in maintenance costs via streamlined condition monitoring

Some maintenance advancements really hit home. Roadway management is a constant challenge for transportation agencies, not to mention a potential source of frustration for motorists traversing the roads, highways, bridges, or tunnels. 

The Hawaii Department of Transportation (HDOT) implemented an innovative road condition management and asset inventory solution to efficiently identify and analyze issues so its teams could reduce costs, better prioritize and address maintenance and repairs, and help keep the roadways safe and clean.

The Blyncsy solution by Bentley Systems, an infrastructure engineering software company, improves HDOT’s stewardship of its critical transportation assets with perpetual real-time visibility into the state of the roads. It crowdsources image collection and automatically detects issues and generates reports on road conditions. 

HDOT, working in conjunction with the University of Hawaii College of Engineering, recently invited everyday drivers to become part of the solution. Its Eyes on the Road program makes 1,000 high-resolution dash cameras available free of charge to approved state residents to record the roads they travel on normally each day, enabling maintenance crews to respond more swiftly to issues. 

The unique road maintenance challenge faced by Hawaii's DOT

To ensure safe and clean road networks and reduce traffic fatalities, state and local DOTs have long relied on periodic time-consuming inspection, analysis, and planning processes for conditions such as potholes and pavement cracks, damaged guardrails, large debris and obstacles, overgrown vegetation, faded striping, barrel and cone placement, and sign inventory. Motorists, cyclists, and pedestrians rarely report roadway issues, but when they do, errors or duplicate reporting may occur.

Hawaii’s road maintenance challenge is rather unique. Many roads are decades old, and the island state’s geography and location expose roadways to salty air, torrential rain and flooding, and the potential for hurricanes, volcanic activity, and mudslides. To keep up, HDOT conducted weekly manual roadway surveys and expanded expensive traffic camera coverage.

In 2022, the State of Hawaii and HDOT sought to determine how much of its monitoring process for 1,013 miles of roadway across Hawaii, Maui, Kauai, and Oahu, could be replaced or automated with comprehensive, crowdsourced dashcam imagery and advanced machine learning models. In addition to accurately detecting diverse conditions and hazards, the solution also needed to incorporate PASER, the Pavement Surface Evaluation and Rating system.

Automated damage inspection tool deployed by Hawaii drivers is key to achieving more proactive road maintenance

HDOT chose Blyncsy, part of Bentley’s Asset Analytics portfolio, for its real-time road condition management and asset inventory capabilities powered by machine vision, crowdsourced data, and AI analytics. 

Increasing situational awareness with machine vision and automating road assessment processes greatly reduces the amount, cost, and environmental impact of manual work. For agencies, the platform’s scalable roadway data and AI analytics enable smarter decision making, lower costs, greater stakeholder trust, and clearer budget justification. 

First, Blyncsy captured an array of high-resolution roadway imagery across Hawaii’s four main islands via dashcams. HDOT then began using the solution’s machine learning algorithms to analyze the imagery and identify common and uncommon issues. Using the results, the team eliminated duplicate reports, verified the true condition of the roads and whether fixes were performed in the correct location, and reported the data to different divisions of the organization in their preferred formats. The accumulated information helped to determine how to prioritize and allocate resources for repairs and maintenance.

By January 2026, HDOT was ready to expand its crowdsourcing capability from primarily fleet vehicles to hundreds of privately-owned vehicles across the Hawaiian Islands. Boosting the volume of data collected would enhance visibility and machine learning analytics.

For the Eyes on the Road program participants, their dashcam imagery is uploaded automatically to the cloud through a cellular connection and then analyzed anonymously by AI and machine learning software, enabling HDOT to be alerted to roadway issues in near real time. Helping to spot road problems early—before they become safety hazards—enables prompt prioritization and maintenance based on data-driven decisions. 

Moving away from reactive maintenance is imperative. Roadway and striping preventive maintenance are crucial to extending the useful life of roads. Proactive attention to issues such as guardrail damage, debris on the road, and vegetation encroachment lowers the cost and scope of repair work while reducing risk and keeping drivers safe. With Blyncsy providing data on road conditions, PASER scores, and paint line conditions on a weekly basis, HDOT can monitor changes and degradation over the lifespan of the project. 

Hawaii DOT maximizes safety and achieves maintenance savings of nearly $1 million per year

Blyncsy software and the Eyes on the Road program greatly reduced HDOT’s need for manual roadway inspections while enabling safer roads and a significant return on investment. With real-time, crowdsourced dashcam imagery and automated roadway assessments driving data-based decisions, the agency is efficiently prioritizing and planning maintenance and repairs.

HDOT is reaping considerable benefits:

• 95% reduction in manual roadway surveys 
• 96% potential savings compared to manual or LiDAR-based inspections
• 97% possible savings with roadway preservation vs. reconstruction
• 23,286 pounds of carbon emissions saved per work vehicle per year by avoiding manual inspections

An estimated $940,000 per year in efficiency savings is gained by detecting more issues faster with the upgraded inspection process. Specific points of value include:

• $250,000 saved annually by slashing manual inspection hours, mileage costs, and vehicle maintenance costs 
• $320,000 saved annually by avoiding manual cataloging and entry of an average of 930 issues found per week 
• $300,000 saved annually by accelerating paint line visibility analysis and PASER scoring

“The operational insights generated allow transportation leaders to make smarter, fiscally responsible decisions founded on objective data rather than subjective assessments,” explains Mark Pittman, senior director, Transportation AI at Bentley Systems. “This shift enables them to prioritize maintenance where it is most needed, address minor issues before they escalate into dangerous and expensive hazards, and ultimately maximize the impact of every taxpayer dollar.”