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Machine Learning predicts truck accidents via ELD data
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Machine Learning breakthrough predicts truck accidents and fatigue from ELD data, improving fleet safety records

Recent advances in Machine Learning are enabling trucking fleets to predict each driver’s probability of getting in a fatigue-related accident on any upcoming shift—before the driver gets behind the wheel.
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Predicting fatigue with machine learning

Enjoy this great article about supporting safety with technology featuring Readi FMIS published by Paul Adair, WDC Staff Writer for Women Driving Change magazine.
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Newcrest’s Lihir mine deploys Readi site-wide for predictive fatigue management

Fatigue Science is proud to announce that Newcrest Mining Limited has deployed its Readi predictive fatigue management technology site-wide at its Lihir mine site in Papua New Guinea.
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Fatigue Science Wins Green Cross Safety Innovation Award

The National Safety Council announced Fatigue Science wins its prestigious Green Cross Award for Safety Innovation.
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Glencore Lomas Bayas implements Readi FMIS

Glencore's Compañía Minera Lomas Bayas (CMLB), a major producer of low-grade oxide copper ore, announced the implementation of Readi FMIS for predictive fatigue management throughout its site located in the Antofagasta Region.
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Fatigue Science launches Machine Learning engine providing world’s first workforce fatigue predictions without wearables

Fatigue Science is pleased to announce the commercial launch of a breakthrough technology advance in its fatigue management platform. For the first time ever, customers can now obtain validated, personalized fatigue predictions for operators in their workforce, without requiring the use of wearables.
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Supervisor App Upgrade: Offline Mode and Hotspots View for shift supervisors

Fatigue Science announces Offline Mode and Hotspots View for shift supervisors, enabling proactive fatigue intervention in underground and remote environments.