Revolutionizing Road Safety: How Blyncsy Uses AI To Leverage Dashcam Footage

Posted on by Mark Pittman

By accessing over a million commercial dashcams, Blyncsy, a part of Bentley Systems, uses movement intelligence to improve mobility and transportation, uses artificial intelligence (AI) vision to pinpoint roadway issues, extrapolate pain points and alert local officials with the most efficient solution to the problem.

Infrastructure Pain Points

State and Local Governments rely on manual inspections to maintain roadways. These are incredibly expensive, as Light Detection and Ranging (LiDAR) systems cost 200 dollars or more per mile to operate. These fact-finding missions are both labor-intensive and time-consuming.

Information collected to make informed decisions on roadway maintenance is often coming from multiple sources. Fragmented and sometimes outdated data makes informed analysis difficult to obtain. Government officials need to be able to take these data points and interpret their value to suit modern needs, such as the wear of heavier electric vehicles and extreme weather on roadways, the use of autonomous vehicles and population increase in urban areas.

How AI-Vision Works

Blyncsy’s AI-Vision collects images from commercial dashcams currently on roadways around the country. The journey from raw footage to data analysis takes place in three steps:

Upload and Validate: Images are collected and validated by examining meta details such as direction information, date and time stamps and heading information.
Segment: AI-Vision breaks down the image and groups like objects together.
Mask: Blyncsy highlights the segments that are valuable to the relative Government agency and provides near real-time insights.

Bentley Systems purchases the footage from partnering dashcam providers and makes the data available to State and Local officials that allow them to make informed and cost-effective decisions to improve their infrastructure. Proactive maintenance applications allow agencies to combine disparate data points to demonstrate how they interact with each other. For example, Blyncsy’s AI-Vision can identify a crosswalk in an image, then analyze the condition of the crosswalk paint and surrounding streetlights. This comprehensive analysis can help agencies quickly determine which intersections are not safe for pedestrians, and subsequently where they should be focusing maintenance efforts.

Blyncsy’s Capabilities

With the dashcams passively capturing and uploading every detail of the roads their drivers travel, Blyncsy’s practical applications are as numerous as the elements they capture.

Safety Critical Assets: From guardrail detection and damage to paint line degradation, the AI-Vision can capture and evaluate the extent of the damage, determine whether the damage is severe enough to require immediate repair. Hawaii is the first to utilize this technology state-wide to detect vegetation encroachment and guardrail damage. As a result, the Hawaii Department of Transportation (HIDOT) can prioritize resolving the most critical safety issues.
Roadway Detection: Similarly, AI-Vision can detect roadway conditions, including recognizing potholes and pavement cracking and issuing a Pavement Surface Evaluation and Rating (PASER) score, where ratings can indicate good or poor pavement condition.
Sign Inventory: Blyncsy can identify how each sign it captures is categorized according to their Manual on Uniform Traffic Control Devices (MUTCD) Classification. From there, it can assess damage and even recognize whether a sign is missing. They can also perform Optical Character Recognition (OCR) on signs to read the text.

These are only a few of the numerous ways Blyncsy’s AI-Vision technology can make roadway and infrastructure maintenance more efficient and cost-effective.

Watch Blyncsy CEO Mark Pittman discuss the capabilities of AI-Vision and how it can help optimize your infrastructure maintenance systems.

To learn more about Blyncsy (a Bentley company) or Bentley, or to schedule a demo, contact Bentley@carahsoft.com or call (703) 673-3570.

Carahsoft Technology Corp. is The Trusted Government IT Solutions Provider, supporting Public Sector organizations across Federal, State and Local Government agencies and Education and Healthcare markets. As the Master Government Aggregator for our vendor partners, including Blyncsy, we deliver solutions for Geospatial, Cybersecurity, MultiCloud, DevSecOps, Artificial Intelligence, Customer Experience and Engagement, Open Source and more. Working with resellers, systems integrators and consultants, our sales and marketing teams provide industry leading IT products, services and training through hundreds of contract vehicles. Explore the Carahsoft Blog to learn more about the latest trends in Government technology markets and solutions, as well as Carahsoft’s ecosystem of partner thought-leaders.

From Insights to Intervention: Building Safer Roads with Smarter Data

Posted on by Mark Pittman

Safety threats do not always wait for the next inspection or make themselves obvious. A missing stop sign, a tilted guardrail or debris from a recent storm can pose real dangers long before a complaint is filed or a crash occurs. Near real-time visual data from crowd-sourced dashcam imagery allows agencies to detect these issues earlier, reducing the risk of collisions, confusion and liability.

This is not just about reacting to problems. It is about gaining continuous visibility across your road network. When you can see more, sooner, you prevent more and protect everyone who uses your roads.

Enable a Proactive Maintenance Culture

Proactive maintenance reduces risk by keeping infrastructure from reaching a failure point. It starts with awareness. With timely insights into pavement wear, fading striping or damaged safety features, you can fix problems before they become safety hazards.

Using this approach minimizes emergencies and reduces the need to send crews into high-risk, high-traffic situations. Over time, it is not just about saving money, it is about making safer and more intelligent decisions every day.

Do Not Let Blind Spots Become Risk Zones

Not every mile of the roadway gets equal attention. Areas that are not high-traffic or complaint-heavy can still hide dangerous issues, especially if they go uninspected for long periods.

Imagery from vehicles already on the road helps reveal what is often missed. It fills in the gaps between formal inspections, surfacing problems in places crews do not regularly visit.

Safety should not depend on luck or public reports. Every segment of your road network deserves consistent visibility.

Speed Recovery After Disasters

When a storm or crisis hits, minutes matter. Near real-time, image-based insights give agencies a fast way to assess damage and identify dangerous conditions, often before crews can access the scene.

Improved visibility enables quicker, more targeted responses. Agencies can clear routes, mark danger zones and stabilize infrastructure faster, protecting both the public and their crews.

The sooner you know what you are facing, the sooner you can act.

Awareness That Improves Safety Outcomes—Not Just Oversight

Effective safety programs do not rely on complaints, scheduled inspections or guesswork. They rely on data that reflects what is happening on the ground—frequently, consistently and with the scale to match the entire network.

Whether identifying early signs of pavement failure or responding to extreme weather events, increased awareness drives better outcomes: fewer emergencies, smarter spending and safer roads for all.

To learn how better information leads to safer roads, view Blyncsy’s portfolio.

More Coverage, Less Overhead: Rethinking Road Inspection Costs with AI-Driven Insights

Posted on by Mark Pittman

Trying to make your maintenance dollars go further without cutting corners on insight, safety or service?

If so, you’re not alone. With budgets often stretched and infrastructure demands growing, many agencies are reexamining how to get the most value out of every maintenance dollar. That’s why many are rethinking expensive, labor-intensive field inspections and turning to smarter, more cost-effective alternatives.

AI-analyzed dashcam imagery from commercial and fleet vehicles gives teams near real-time, visual insights into road conditions without the typical overhead. By using what’s already on the road, agencies can cut spending while getting even better data on pavement conditions, signage, lane markings and hazards.

Smarter Inspections. Real Savings.

Manual inspections can cost anywhere from $100 to $200 per mile, depending on the method and crew required. When you factor in vehicle costs, staffing, scheduling and delays, those expenses scale fast, especially for agencies managing thousands of miles.

AI-powered visual intelligence can reduce up to 90% of the manual inspections traditionally required for roadway condition assessment. That’s a considerable savings in time and money. In Hawaii, automated analysis of guardrails, striping and debris saved the state DOT over $900,000 by eliminating unnecessary field visits and allowing more strategic deployment of maintenance dollars.

With continuous AI-driven assessments, inspections shift from rigid schedules to condition-based decision-making. This allows agencies to focus their limited resources where the data shows they’re actually needed, maximizing impact while minimizing waste.

Lower Operational Strain, Lower Spend

Reducing fieldwork doesn’t just save time, it cuts expenses across the board. Fewer field deployments mean lower fuel costs, less vehicle wear and fewer overtime hours.

Instead of organizing additional field inspections, agencies can rely on regularly updated insights coming from existing vehicle networks. This reduces the need to expand teams or invest in specialized equipment to keep up with inspections. It also supports a safer inspection process by reducing risk exposure for field crews.

Better visibility leads to more accurate budgeting. Instead of flying blind—or relying on complaints—you can plan maintenance with precision, stretch your resources and avoid surprise repairs that blow up budgets.

Faster Recovery, Lower Emergency Costs

Storms, floods, and other disruptions can incur urgent, unexpected expenses. But quick, AI-enabled visual assessments can help reduce emergency costs.

Agencies can assess road damage without dispatching field teams immediately, saving time and protecting crews. Infrastructure inspections are evolving to include tools like Google Street View, providing a reliable “before” snapshot. Combined with dashcam imagery for the “after,” agencies can clearly analyze damage and document changes over time. That early insight supports faster funding requests and avoids the cost of blanket response measures that may not be necessary.

With centralized, visual data that’s easy to share, teams can streamline contractor coordination, skip redundant inspections and focus their limited funds where they’ll have the most impact.

Rewriting the Cost Equation

Road inspections don’t have to drain your budget. With AI-analyzed dashcam data, agencies are expanding visibility across their networks while significantly cutting costs.

The real value lies in shifting from reactive to efficient, insight-driven decision-making. From daily maintenance to emergency recovery, this model is helping public teams rethink how, and how much, they spend on inspections.

For any agency trying to do more with the same—or even less—budget, it’s time to rethink how inspections are conducted.

Watch the on-demand webinar to see how agencies are using AI-driven insights to reduce inspection costs while improving road safety.

The End of Manual Inspections? How AI and Dashcam Imagery Are Redefining Roadway Management

Posted on by Mark Pittman

Years ago, as I waited at a traffic light, I wondered why infrastructure maintenance still leaned so heavily on manual inspections and reporting. That question sparked an idea: What if roads could tell us when something was wrong?

Today, that vision has become a reality. Dashcam imagery—passively captured from vehicles already on the road—is now powering automated AI models that detect issues like fading lane paint, damaged signs, and debris. Looking ahead, the integration of expansive imagery sources, such as Google Street View, promises to further enhance this capability, offering broader and more detailed coverage. It’s a shift from scheduled inspections to constant awareness, from sending crews out to bringing insight in.

Automation with Real Impact

Traditional inspections are resource intensive. They usually involve deploying extra staff and specialized equipment, and scheduling work during off-hours to avoid disrupting traffic. AI-driven visual intelligence of dashcam footage can reduce the number of manual surveys required by more than 90%, saving considerable time and money.

Take Fort Worth. Dashcam imagery gave the city a fresh look at lane striping and sign visibility, but from the driver’s perspective, not an aerial map. It’s how people experience the road daily, and it’s the same view automated vehicles rely on to safely navigate.

Instead of waiting months for a full inspection cycle, cities can spot and act on issues within days. Enabling faster response and more strategic use of limited resources.

Smarter Operations. Less Fieldwork.

While field checks are still common for most agencies, the model is shifting. With dashcam footage collected by vehicles already in motion and analyzed automatically, teams can now monitor more of the network without constantly dispatching field crews.

In Alaska, for example, dashcam data is used to monitor remote routes that are difficult and sometimes dangerous for crews to inspect in person. This kind of visibility can be a game changer for regions with tough geography or tight budgets.

Instead of following a fixed schedule or responding to complaints, agencies can now rely on AI-driven alerts to flag when conditions change. It’s a shift from routine patrols to focused action, and it means fewer trips to the field, less fuel, and better outcomes with the same (or smaller) team.

Compliance without the Complexity

Staying compliant with FHWA, MUTCD, and other federal standards typically requires a lot of paperwork. However, with AI-based monitoring, those checks can happen automatically in the background. Retroreflectivity, sign placement, and line clarity are continuously reviewed and documented.

Each data point is visual, time-stamped, and ready for audits, grant applications, or internal reviews. Even better, it’s easy to share. Operations, maintenance, and planning teams can stay aligned without sifting through emails or outdated spreadsheets.

A New Model for Infrastructure

The future of road operations isn’t about more inspections. It’s about smarter ones. Or, in many cases, none at all. When roads can essentially report their condition using dashcam footage and AI, agencies don’t have to guess or wait. They already know what’s happening.

And this is only the beginning. As capabilities such as historical imagery access and visual change detection over time emerge with Google Street View and become integrated, transportation teams will gain even deeper insight into how their infrastructure evolves. These images will empower agencies to identify long-term patterns, track degradation over time, and intervene before minor issues escalate into costly repairs.

For public teams expected to cover more ground with fewer resources, this isn’t just about saving time. It’s about working in a more intelligent, sustainable way, built for the demands of today’s infrastructure and ready for tomorrow’s.

Ready to stop checking and start knowing?