Monitor seatbelt compliance with AI dashcam video enhancements

Seatbelt use is one of the simplest and most effective driving safety behaviors — and yet it’s one of the most consistently overlooked in commercial driving.

A Verizon Connect Data Science analysis of 70 million driver-facing videos found that about 7% of commercial drivers operate vehicles without fastening their seat belts.¹ Yet those unbelted drivers account for 64% of trucking driver fatalities.²

That gap between how often unsafe behavior occurs and how severely it affects outcomes is exactly where AI dashcam technology has become a critical safety tool.

Dashcams help fleets identify risky behavior in near real time and address hazards before they lead to a serious incident. Modern fleet seatbelt monitoring systems combine driver-facing video, machine learning and in-cab audio alerts to reinforce seatbelt compliance. They can also flag broader driver behavior patterns, including distraction, tailgating and fatigue, all of which shape collision risk.

How AI "sees" compliance: The technology behind the alerts

At the core of Verizon Connect’s AI fleet dashcam capability is its cloud AI video analytics engine. When a driving event is detected, both road-facing and driver-facing video clips are reviewed by cloud-based AI to assess severity and classify behaviors. The system applies event classifications — critical, major, moderate or minor — based on what the AI "sees" in the footage.

This automated classification helps fleet managers move beyond raw video toward actionable insight. Instead of manually reviewing hours of footage, managers can prioritize the events that matter most for safety and coaching.

And AI dashcam distracted driving detection extends well beyond seatbelts. Phone-to-ear use, food and drink, smoking and extended off-road glances can all be flagged by the AI, giving fleets a clearer picture of how attention shifts behind the wheel.

The system analyzes a wide range of behaviors, including:

Road-facing behaviors:

• Near miss: When a driver brakes or swerves to avoid a vehicle, person, animal and/or object, which is detected very close by.
• Collision: An impact occurred with a vehicle, person, animal and/or object or, alternatively, the driver lost control of the vehicle.
• Animal: An animal was involved in a near miss or collision.
• Tailgating: Driving dangerously close to the vehicle in front while traveling at least 25 mph.
• Rolling stop: Vehicle did not fully stop at a stop sign.
• Posted speed exceeded: Vehicle travels faster than the road's posted speed limit
• Traffic light violation: Driver failed to stop at a solid red traffic light while the vehicle was traveling over 9 mph.
• Adverse conditions: The road is covered by snow, ice or surface water.
• Pedestrian ahead: Vehicle was close to a pedestrian or cyclist while traveling 6-31 mph.
• Other vehicle cutoff: When another vehicle suddenly cuts into the driver's lane.

Driver-facing behaviors:

• Phone distraction: Driver held the shape of a cell phone (calling, texting, scrolling).
• Seat belt unfastened: Seat belt not fastened or worn incorrectly while traveling over 6 mph.
• Food in hand: Driver handled food or a beverage while the vehicle was traveling over 6 mph.
• Smoking: The driver held the shape of a cigarette close to their face.
• Tiredness: The driver repeatedly yawned and/or closed their eyes for a set time.

You can learn more about Verizon Connect’s s AI-powered dashcams detect unsafe driving behaviors and driving environment factors here.

Beyond daylight conditions, AI fleet cameras  are also designed to maintain detection performance in low-light environments. Infrared (IR) sensors help the camera identify seatbelt positioning and driver posture even at night or in dimly lit cabs, improving reliability compared to basic video-only systems. Extended view cameras can also add an additional layer of visibility by capturing views along a vehicle’s side, rear and into cargo areas.

Dashcams support fleets in more ways than one. See the top 3 ways integrated video boosts driver safety and protects fleets.

Help reduce risky driving with real-time intervention and post-trip coaching

One of the most meaningful differences between traditional dashcams and modern AI-powered dashcams is timing. Video review alone supports post-trip coaching. Real-time, audible, in-cab alerts change behavior in the moment.

When enabled, in-cab audio prompts that play a chime and announce a message, such as “Unfastened seatbelt,” can remind a driver to fasten their seat belt once the vehicle exceeds a defined speed threshold. Similar alerts can be configured when AI dashcams detect distracted driving, creating immediate feedback loops that reinforce safer habits without waiting for a supervisor to intervene later.

At the same time, fleet AI dashcam video provides critical context for coaching. Footage can show whether a driver briefly unbuckled to reach for paperwork or whether unfastened seatbelt use is a recurring behavior on long-haul routes. That context matters when managers are deciding how to coach fairly and effectively.

Verizon Connect’s anonymized, aggregated data highlights the behavioral impact of these real-time interventions. Across 30,000 vehicles in North America, enabling in-cab alerts correlated with substantial reductions in safety-critical events:¹

• Seat belt unfastened events decreased by 60%
• Phone calling events decreased by 60%
• Tailgating and fatigue-related events decreased by roughly 50%
• Distraction events decreased by about 30%

This blend of immediate intervention and contextual review supports both accountability and improvement.

AI dashcams can impact liability exposure and insurance costs

Unsafe driving behaviors carry human consequences first, but they also translate directly into business risk. The average nonfatal work-related crash costs employers roughly $75,000, while a fatal crash can exceed $750,000 in direct and indirect costs.³ Beyond the immediate financial impact, serious incidents expose fleets to long-term legal and reputational risk.

Fleet vehicle seatbelt monitoring systems and documented seatbelt compliance plays a growing role in how fleets demonstrate that safety expectations are not just written into policy, but actively enforced. While no technology can eliminate legal exposure, the ability to show that risky behaviors were identified, addressed and monitored over time can help demonstrate due diligence when incidents occur.

There is also a growing intersection between telematics data and insurance underwriting. Usage-based insurance models and telematics-informed programs increasingly consider verified driving behavior when evaluating fleet risk. Requirements vary by carrier and program, but fleets using AI-powered dashcams and fleet seatbelt monitoring systems often have stronger documentation to support underwriting reviews and risk conversations.

For safety leaders, the takeaway is less about discounts and more about defensibility. When an organization can point to consistent monitoring, real-time alerts and documented coaching, it shifts safety from a reactive posture to a managed system — a distinction that matters in both claims review and broader risk management.

Building a safety-first culture with AI evidence

Technology alone doesn’t create a safety culture but it can reinforce one. AI dashcams provide objective evidence that supports fair, consistent safety management across a fleet. When seatbelt compliance is treated as a weighted factor in driver safety scores, it signals that certain behaviors are non-negotiable.

Verizon Connect’s aggregated data shows that drivers with repeat risky driving events are nearly twice as likely to be involved in a crash.¹ Patterns such as repeated stop sign violations, overspeeding or phone distraction significantly increase collision likelihood. When these insights are paired with coaching workflows, safety programs can intervene earlier — before patterns escalate into incidents. This kind of data is the backbone of an effective fleet safety program.

Over time, this approach helps normalize safety expectations. Drivers see that seatbelt use, attention and adherence to policy are monitored consistently, not selectively. Managers gain clearer insight into where coaching will have the greatest impact. And organizations move closer to a proactive safety culture grounded in evidence, not assumptions.

To learn about how fleet AI dashcams can help protect your drivers, your fleet and your bottomline, set up a demo today.

Sources

¹ Verizon Connect anonymized aggregated customer data

² U.S. Department of Transportation Federal Motor Carrier Safety Administration, Findings from the Fatality Analysis Reporting System

³ Network of Employers for Traffic Safety, Cost of Motor Vehicle Crashes to Employers