SYRACUSE, N.Y. — Fleet safety technology has advanced far beyond GPS tracking and accident recording. 

Today’s camera and telematics systems can help businesses, including commercial laundry operations, identify unsafe driving behaviors, improve routes, deliver immediate driver alerts, create measurable safety scores, and build training programs around the situations drivers actually encounter.

However, installing the technology is only the beginning.

The greatest value comes from consistently reviewing the information, acting on it and making fleet safety a priority throughout the organization. 

When ownership, management, supervisors and drivers all understand how the technology is being used, fleet data becomes more than information on a dashboard — it becomes the foundation of a proactive safety program.

Forward-facing and driver-facing cameras are often viewed primarily as tools for investigating accidents. Video can certainly provide valuable evidence after a loss, but the technology’s preventive capabilities may be even more important.

Modern camera systems can use artificial intelligence to identify behaviors such as:

• Distracted driving
• Cellphone use
• Following too closely
• Speeding
• Failure to wear a seat belt
• Harsh braking or acceleration
• Unsafe lane changes
• Signs of fatigue or drowsiness
• Incomplete stops
• Other high-risk driving patterns

When these behaviors are detected, many systems can issue an immediate in-cab alert. This allows the laundry route driver to correct the behavior before it contributes to an accident.

That immediate feedback is one of the biggest advantages of AI-enabled fleet technology. Instead of waiting for a supervisor to review an event days later — or waiting until an accident occurs — the system can intervene while the driver is still behind the wheel.

The camera also gives managers the context surrounding an alert. A harsh-braking event, for example, does not automatically mean the driver did something wrong. The driver may have reacted properly to another vehicle entering the lane. Reviewing the footage allows management to distinguish between unsafe behavior and effective defensive driving.

This context helps create a fairer and more credible safety program. Drivers are more likely to accept coaching when they know management is reviewing the complete event rather than disciplining them based solely on a data point.

Telematics systems collect information about how laundry vehicles and drivers perform throughout the day. Depending on the system, management may be able to monitor:

• Vehicle speed
• Braking and acceleration
• Following distance
• Seat-belt usage
• Idling
• Vehicle location
• Route efficiency
• Hours behind the wheel
• Fuel consumption
• Vehicle maintenance indicators
• Recurring high-risk locations

This information allows fleet managers to move away from assumptions and make decisions based on what is actually occurring in the operation.

For example, repeated harsh-braking events may initially appear to be a driver-performance issue. However, the data may show that the events are concentrated at a particular intersection, delivery location, or congested portion of a route. Management can then determine whether the driver needs additional training, the route should be adjusted, or a specific location requires additional precautions.

The goal is not simply to collect more data. The goal is to turn that data into practical changes that reduce exposure.

Route optimization is often discussed as an efficiency tool, but it can also play an important role in laundry fleet safety.

The fastest route is not always the safest route. While a particular route may save several minutes, it could expose a driver to more difficult left-hand turns, congested intersections, low-clearance areas, construction zones, narrow streets, or challenging customer locations.

Telematics data can help management evaluate:

• Where accidents and near misses are occurring
• Which routes generate the most speeding or braking alerts
• Whether schedules create pressure to rush
• Which delivery locations present backing challenges
• Where traffic congestion increases risk
• Whether drivers are spending excessive time behind the wheel
• Whether weather or seasonal conditions require route adjustments

Management can use this information to modify routes, change delivery windows, provide location-specific instructions or assign certain routes to drivers with the appropriate experience.

Route optimization should balance productivity with safety. If a schedule cannot be completed without speeding, rushing, or taking unnecessary risks, the schedule itself may be contributing to the company’s exposure.

AI alerts help identify individual driving events, while laundry driver safety scores can reveal broader performance trends over time.

These scores may consider factors such as speeding, following distance, distracted driving, harsh braking, acceleration, seat-belt usage and other behaviors. Fleet managers can use them to identify:

• Drivers who need immediate coaching
• Behaviors occurring across the entire fleet
• Routes or locations producing repeated alerts
• Drivers who are improving
• Strong performers for recognition
• Training topics requiring companywide attention

Scores should not be used without context. A single number does not tell the entire story, and different routes may expose drivers to different operating conditions. Management should review the underlying events, video, routes and trends before reaching a conclusion.

The most effective programs establish clear expectations for how alerts and scores will be handled. This should include when coaching is required, how improvement will be measured, what happens after repeated violations and how positive performance will be recognized.

Drivers should understand what is being measured and why. Transparency helps position the program as a safety and development initiative rather than simply a form of surveillance.

Traditional driver training often relies on general reminders: slow down, avoid distractions, maintain following distance and drive defensively. These messages are important, but they can become repetitive and easy to disregard.

Camera and telematics data make training specific and relevant.

Instead of speaking generally about following distance, a laundry delivery manager can review an actual event from one of the company’s routes. The discussion can address what the driver encountered, when the risk developed and what could have been done differently.

Training can be built around real examples involving:

• A difficult intersection
• A preventable backing event
• Sudden braking in congested traffic
• A close-following alert
• A distracted-driving event
• Speeding on a familiar route
• A near miss at a customer location
• Driving during adverse weather
• A successful defensive-driving response

Real scenarios make safety discussions more relatable because drivers recognize the roads, customers, equipment and challenges involved. The training is no longer theoretical — it directly reflects their working environment.

This approach can also reveal operational issues that would otherwise remain hidden. An event may show that a driver needs coaching, but it could also expose an unrealistic delivery schedule, a poorly designed route, inadequate customer-site instructions, or a recurring vehicle-maintenance problem.

Short, frequent training sessions built around recent fleet events may have more impact than relying solely on an annual safety meeting. Each session should be documented, including the topic, date, attendees, event reviewed, and any corrective action taken.

Technology does not create a safety culture by itself. Management determines whether the information produces meaningful improvement.

A strong program begins with ownership and senior leadership establishing clear expectations. Supervisors must then apply those expectations consistently, and drivers must receive timely feedback that is fair, specific, and focused on improvement.

Management’s responsibilities should include:

• Reviewing fleetwide alerts and performance trend
• Establishing thresholds for coaching and corrective action
• Evaluating routes and schedules that may contribute to unsafe behavior
• Participating in safety meetings
• Holding supervisors accountable for completing driver coaching
• Recognizing drivers who improve or consistently perform well
• Applying policies consistently throughout the organization
• Documenting training and corrective actions
• Measuring whether the program is producing better results

The same data should be used at every level of the organization, but for different purposes.

Ownership can review overall fleet trends and determine whether the company’s investment is improving performance. Safety managers can identify recurring behaviors and develop training. 

Supervisors can coach individual drivers. Dispatchers can evaluate routes and scheduling pressures. Drivers can understand their performance and track their improvement.

This creates a true top-down approach in which safety is supported by leadership and reinforced throughout daily operations.

Camera alerts and driver scores should not be used only to identify problems. They can also help recognize safe laundry route drivers who may otherwise receive little feedback.

A driver who consistently maintains safe following distances, avoids distractions, wears a seat belt, controls speed and responds defensively deserves recognition. Companies may consider using measurable performance data to support:

• Cash bonuses
• Gift cards
• Additional paid time off
• Preferred routes or schedules
• Quarterly safety awards
• Companywide recognition
• Driver-retention incentives

Rewards should be based on safe driving behaviors and documented improvement — not simply the absence of reported accidents. Focusing only on accident-free performance could unintentionally discourage drivers from reporting minor incidents or near misses.

A balanced program combines coaching, accountability and recognition. This makes it clear that the company is using technology to develop and protect its drivers, not merely to discipline them.

When an accident does occur, cameras and telematics can provide critical information about what happened immediately before, during, and after the event.

Video footage, vehicle speed, braking activity, location data, and other records may help:

• Establish the sequence of events
• Demonstrate that the driver responded appropriately
• Defend against inaccurate allegations
• Identify third-party responsibility
• Accelerate the claim investigation
• Reduce uncertainty surrounding disputed claims
• Preserve evidence for the insurance carrier or legal counsel
• Identify training opportunities following the loss

Companies should have procedures for promptly preserving video and telematics records after an accident, complaint, near miss, or reported incident. If footage is not saved before the system’s retention period expires, valuable evidence may be lost.

The technology can also help management conduct a meaningful post-accident review. Rather than focusing only on whether the driver was at fault, the company can determine whether routing, scheduling, training, supervision, or operating procedures contributed to the event.

Insurance carriers increasingly want evidence that fleet technology is being actively managed. Simply listing a camera or telematics provider on an application does not demonstrate that the system is producing meaningful change.

A strong insurance submission may include:

• The percentage of vehicles equipped with cameras and telematics
• Forward-facing and driver-facing camera capabilities
• AI alerts monitored by management
• Driver-safety score trends
• Improvements in speeding, distraction, or following-distance events
• Examples of data-driven training
• Coaching and corrective-action procedures
• Route-optimization practices
• Safety meeting records
• Driver recognition and incentive programs
• Procedures for preserving video after an accident
• Management’s involvement in reviewing fleet performance
• Corrective actions taken following prior losses

This documentation helps the broker explain how the company is reducing its exposure. It can also give underwriters a clearer picture of the operation than loss history alone.

Technology cannot guarantee lower premiums, but measurable improvement can strengthen the company’s position in the insurance marketplace. It gives the broker credible evidence to pursue greater carrier interest, improved terms, and more sustainable long-term insurance costs.

The value of fleet technology is not measured by how many cameras are installed or how much data is collected. It is measured by what the company does with the information.

The strongest programs use cameras and telematics to detect risk early, alert laundry drivers in real time, optimize routes, create meaningful performance scores, deliver targeted training, recognize improvement, and respond more effectively when an accident occurs.

Most importantly, the information must flow throughout the organization. Ownership must support the program, managers must review the data, supervisors must coach consistently, dispatchers must consider the effect of routes and schedules, and drivers must understand how their performance contributes to the company’s safety goals.

When real fleet data drives real operational decisions, safety becomes more than a written policy. It becomes a measurable, ongoing management process that can reduce claims, protect drivers, strengthen accountability, and improve the company’s insurance results.