Understanding Machine Vision & What It Can Do for Your Fleet

May 25, 2020

Road accidents and fatalities can be expensive for businesses. Fleets should want to reduce, or eliminate them entirely. Machine vision technology promises an exciting future where drivers spend more time on the road and less time in repair bays.

Machine vision cameras are already present among some large fleets, tracking their drivers every move for risky behavior. In this article we will outline the consequences of road accidents and fatalities for businesses, what machine vision is and how it can help reduce collisions, the benefits to machine vision software, and the future of machine vision systems.

How Distracted Driving Hurts your Fleet

All industries experience incidents of distracted driving, but fleets are especially susceptible to it. Distracted driving is also prevalent in both private and commercial vehicles. A brief moment of distracted driving can have tremendous consequences. Fleets spend a significant amount of time and resources trying to cut down on distracted driving amongst their workforce.

The National Highway Traffic Safety Administration (NHTSA) defines distracted driving as “any activity that diverts attention from driving... — anything that takes your attention away from the task of safe driving.” Some examples of distracted driving include adjusting the vehicle’s stereo, entertainment or navigation system, talking to people in the vehicle, eating or drinking, and talking or texting on a phone.

There are three main types of distracted driving: visual distractions, manual distractions, and cognitive distractions. Visual distractions involve the driver taking his or her focus and eyes off the road. Manual distractions are those that make the driver remove their hands from the wheel. Cognitive distractions take the driver’s attention away from driving. These categories of distractions are not mutually exclusive. Drivers who take part in one distracted driving behavior are more likely to also engage in other high-risk behaviors simultaneously. 

Statistics on distracted driving are alarming, to say the least. The NHTSA found that 3,166 people were killed by distracted driving in 2017. Using a cell phone was reported as the lethal distraction in 14% of those crashes.

The United States Department of Transportation Federal Motor Carrier Safety Administration (FMCSA) noted that for commercial fleets, distracted driving is the second leading driver-related cause of fatal accidents. In a different report, the FMCSA found that for medium and heavy truck collisions, businesses pay an average of $200,000 per vehicular incident and $3.6 million per fatality.

What is Machine Vision?

At its essence, machine vision is a technology that analyzes video and image data to make predictions. Machine vision can be used on a basic level to detect objects in videos or pictures—cell phones, coffee cups, or cigarettes, etc. It can also be used to detect whether a vehicle has a passenger or not.

Machine vision systems need to be trained in order to operate. This is done by feeding thousands of videos or pictures through the system. These pictures and videos are tagged manually by humans in order to teach the machine vision software what objects each contains. Machine vision systems learn through this training to identify objects on their own for uncategorized images and videos. 

At an advanced level, machine vision systems can be trained to better understand what they “see” (or don’t see) in images and videos presented to them. Often this process is completed with the assistance of artificial intelligence (AI) to make predictions or calculate risk.

Machine Vision Systems

Machine vision systems are only as intelligent as the data used to train them (fed via the machine vision camera). In order to create accurate models that can deal with all of the divergent situations that come up in real life, machine vision software needs to be fed millions of unique images that represent all imaginable situations. Good machine vision software has been trained by multiple years of driving data from different vehicle and road types, and all-weather conditions.

There are a number of components that make up machine vision systems. There is the machine vision camera, which captures data. The machine vision lens is connected to a computer. And the software is used to crunch the data and make predictions or generate analysis.

The Benefits of Machine Vision Cameras

The overwhelming majority of miles driven by commercial fleets in the United States are safe and incident-free. However, it only takes a moment to generate risk when driving by eating for five or ten minutes, taking a brief phone call, or smoking a cigarette for example. This is where machine vision cameras come in. Being able to recognize these serious moments that generate risk is the key to reducing road accidents.

Finding risk-generating moments amongst the countless hours fleet drivers spend behind the wheel and accurately categorizing them as risky behavior is a daunting challenge, but machine vision systems are up for it. Machine vision cameras can sift through colossal piles of data generated by your fleet’s onboard video cameras to find the short (but critical) moments that generate risk amongst your drivers. Having a machine vision lens in your fleet’s vehicles can prevent expensive accidents and fatalities.

Putting a machine vision lens inside your fleet’s vehicles allows management and drivers to receive alerts when drivers exhibit dangerous or risky behavior. Machine vision software provides instant alerts if a driver is exhibiting signs of distraction or fatigue. It will also help catch when drivers forget to buckle up or are smoking on the job. You can even incorporate facial recognition to machine vision software to ensure only authorized personnel can operate the vehicle.

The Future of Machine Vision

Machine vision systems can interpret fleet drivers’ behavior in real-time. The technology is in its early years but has enormous potential for fleets. The machine vision technology sector is growing rapidly. According to a report by Grand View Research, the global market for machine vision systems is expected to read $18.24 billion (USD) by 2025. 

In its current state, machine vision can help your fleet reduce its accidents and casualties. Machine vision cameras installed inside vehicles can detect risk-generating behavior and alert drivers and managers.


Learn more about technology that can go to work for your fleet. Find out what Azuga Fleet™ can do to boost your team’s productivity, decrease fuel costs, and improve driver safety.

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Understanding Machine Vision & What It Can Do for Your Fleet

May 25, 2020

Road accidents and fatalities can be expensive for businesses. Fleets should want to reduce, or eliminate them entirely. Machine vision technology promises an exciting future where drivers spend more time on the road and less time in repair bays.

Machine vision cameras are already present among some large fleets, tracking their drivers every move for risky behavior. In this article we will outline the consequences of road accidents and fatalities for businesses, what machine vision is and how it can help reduce collisions, the benefits to machine vision software, and the future of machine vision systems.

How Distracted Driving Hurts your Fleet

All industries experience incidents of distracted driving, but fleets are especially susceptible to it. Distracted driving is also prevalent in both private and commercial vehicles. A brief moment of distracted driving can have tremendous consequences. Fleets spend a significant amount of time and resources trying to cut down on distracted driving amongst their workforce.

The National Highway Traffic Safety Administration (NHTSA) defines distracted driving as “any activity that diverts attention from driving... — anything that takes your attention away from the task of safe driving.” Some examples of distracted driving include adjusting the vehicle’s stereo, entertainment or navigation system, talking to people in the vehicle, eating or drinking, and talking or texting on a phone.

There are three main types of distracted driving: visual distractions, manual distractions, and cognitive distractions. Visual distractions involve the driver taking his or her focus and eyes off the road. Manual distractions are those that make the driver remove their hands from the wheel. Cognitive distractions take the driver’s attention away from driving. These categories of distractions are not mutually exclusive. Drivers who take part in one distracted driving behavior are more likely to also engage in other high-risk behaviors simultaneously. 

Statistics on distracted driving are alarming, to say the least. The NHTSA found that 3,166 people were killed by distracted driving in 2017. Using a cell phone was reported as the lethal distraction in 14% of those crashes.

The United States Department of Transportation Federal Motor Carrier Safety Administration (FMCSA) noted that for commercial fleets, distracted driving is the second leading driver-related cause of fatal accidents. In a different report, the FMCSA found that for medium and heavy truck collisions, businesses pay an average of $200,000 per vehicular incident and $3.6 million per fatality.

What is Machine Vision?

At its essence, machine vision is a technology that analyzes video and image data to make predictions. Machine vision can be used on a basic level to detect objects in videos or pictures—cell phones, coffee cups, or cigarettes, etc. It can also be used to detect whether a vehicle has a passenger or not.

Machine vision systems need to be trained in order to operate. This is done by feeding thousands of videos or pictures through the system. These pictures and videos are tagged manually by humans in order to teach the machine vision software what objects each contains. Machine vision systems learn through this training to identify objects on their own for uncategorized images and videos. 

At an advanced level, machine vision systems can be trained to better understand what they “see” (or don’t see) in images and videos presented to them. Often this process is completed with the assistance of artificial intelligence (AI) to make predictions or calculate risk.

Machine Vision Systems

Machine vision systems are only as intelligent as the data used to train them (fed via the machine vision camera). In order to create accurate models that can deal with all of the divergent situations that come up in real life, machine vision software needs to be fed millions of unique images that represent all imaginable situations. Good machine vision software has been trained by multiple years of driving data from different vehicle and road types, and all-weather conditions.

There are a number of components that make up machine vision systems. There is the machine vision camera, which captures data. The machine vision lens is connected to a computer. And the software is used to crunch the data and make predictions or generate analysis.

The Benefits of Machine Vision Cameras

The overwhelming majority of miles driven by commercial fleets in the United States are safe and incident-free. However, it only takes a moment to generate risk when driving by eating for five or ten minutes, taking a brief phone call, or smoking a cigarette for example. This is where machine vision cameras come in. Being able to recognize these serious moments that generate risk is the key to reducing road accidents.

Finding risk-generating moments amongst the countless hours fleet drivers spend behind the wheel and accurately categorizing them as risky behavior is a daunting challenge, but machine vision systems are up for it. Machine vision cameras can sift through colossal piles of data generated by your fleet’s onboard video cameras to find the short (but critical) moments that generate risk amongst your drivers. Having a machine vision lens in your fleet’s vehicles can prevent expensive accidents and fatalities.

Putting a machine vision lens inside your fleet’s vehicles allows management and drivers to receive alerts when drivers exhibit dangerous or risky behavior. Machine vision software provides instant alerts if a driver is exhibiting signs of distraction or fatigue. It will also help catch when drivers forget to buckle up or are smoking on the job. You can even incorporate facial recognition to machine vision software to ensure only authorized personnel can operate the vehicle.

The Future of Machine Vision

Machine vision systems can interpret fleet drivers’ behavior in real-time. The technology is in its early years but has enormous potential for fleets. The machine vision technology sector is growing rapidly. According to a report by Grand View Research, the global market for machine vision systems is expected to read $18.24 billion (USD) by 2025. 

In its current state, machine vision can help your fleet reduce its accidents and casualties. Machine vision cameras installed inside vehicles can detect risk-generating behavior and alert drivers and managers.


Learn more about technology that can go to work for your fleet. Find out what Azuga Fleet™ can do to boost your team’s productivity, decrease fuel costs, and improve driver safety.

Take a look at related posts.