Tired drivers are involved in 10-20% of all crashes, with one in eight drivers admitting to falling asleep at the wheel. Fatigue can be as dangerous as drink-driving, and police data shows it contributes to around 4% of fatal crashes in Britain. In the commercial transport sector, drivers are at even greater risk given long hours and unpredictable road conditions, which is why preventing drowsiness is a top priority for Samsara’s tens of thousands of customers.

That’s why today, I’m excited to share that our Drowsiness Detection feature is now generally available for all Samsara customers. Drowsiness Detection uses Samsara’s comprehensive AI models—trained on our industry-leading dataset with billions of minutes of video—to proactively detect when signs of drowsiness occur. Then, it triggers real-time in-cab audio alerts for drivers, while notifying managers via text or email to triage fatigue-related events in the moment. These insights can be viewed as aggregated reports within the Samsara Platform, allowing managers to analyse patterns of fatigue across their fleet, focus on driver coaching, and ultimately reduce drowsiness to improve road safety.

Real-world impact, powered by Samsara’s large-scale dataset.

While advancements in AI and machine learning have made proactive alerts possible, drowsiness remains an incredibly nuanced behaviour to train AI models to detect. It’s more than a single behaviour, like yawning or having your eyes closed. Furthermore, drowsiness can be less common than other risky driving behaviours, so accurate detection is dependent on our ability to sample high-quality examples at scale to train AI models. 

That’s where the scale of Samsara’s data sets our solution apart. We train our models on more than 180 billion minutes of video footage and 220 billion miles traveled within our platform, which makes it possible to provide high accuracy and impact for our customers.

Samsara’s comprehensive Drowsiness Detection is trained to consider several behaviours that indicate fatigue, in alignment with leading and clinically validated standards for defining drowsiness. These behaviours include: head nodding, slouching, prolonged eye closure, yawning, rubbing eyes, and more. Yawning alone is often not a sufficient detector of drowsiness. In fact, an analysis^* among early adopters of Samsara’s Drowsiness Detection found that approximately 77% of drowsy driving events were detected by behaviours other than yawning alone.

Protecting drivers and making roads safer.

We first announced Drowsiness Detection during our annual Beyond conference in June, which gathers more than 2,000 physical operations leaders across the industry. Since then, Samsara customers have already experienced meaningful impact.

For example, one of the largest oilfield services companies in the U.S. has seen a significant decrease in how often drivers are falling asleep during shifts since using Samsara’s Drowsiness Detection. According to their VP of Health Safety and Environment, “We used to have multiple drivers falling asleep at the wheel. Now, we've gone as long as 30 days without a single driver falling asleep due to these alerts.”

Learn more about Drowsiness Detection and other exciting new features from Samsara.

Drowsiness Detection is just one of many new features and products Samsara has recently released, fueled by our customer feedback loop and innovation engine. 

Check out our Autumn 2024 Product Quarterly Webinar to learn more about how you can harness the benefits of our latest features and product updates. We’ll cover ways to enhance driver safety using AI-powered features like Drowsiness Detection and Forward Collision Warnings, how our new Asset Tag and Powered Asset Gateway can enhance security for your fleet, and more. Don't miss out—register now to watch the webinar at your convenience.

^*Aggregated analysis of over 35,000 detections across a cohort of 50 customers since July, 2024.