Ridy Uses Machine-Vision Analytics on Drowsy and Distracted Drivers
References: indiegogo & producthunt
Drowsy driving has always been a danger on the roads, and with the rise of mobile technology, distracted driving has joined the list of road-bound threats as well; Ridy is a tool that helps to mitigate those dangers. The dashboard gadget uses machine vision and artificial intelligence to recognize when users are drowsy or distracted, giving them alerts to keep them focused or awake.
Ridy's mission began through unfortunate circumstances: the founder got into a car accident while driving after a long, tiring day at work. The evidence isn't only anecdotal, though. Shift workers, professional drivers, and people on long trips are susceptible to accidents because of their driving condition, and everyone has felt the urge to check their phone while operating a vehicle. Ridy is an unobtrusive way to help resist those risks and keep everyone on the road safer.
Ridy's mission began through unfortunate circumstances: the founder got into a car accident while driving after a long, tiring day at work. The evidence isn't only anecdotal, though. Shift workers, professional drivers, and people on long trips are susceptible to accidents because of their driving condition, and everyone has felt the urge to check their phone while operating a vehicle. Ridy is an unobtrusive way to help resist those risks and keep everyone on the road safer.
Trend Themes
1. Drowsy Driving Detection - Developing advanced technologies that use machine vision and artificial intelligence to detect signs of drowsy driving and provide timely alerts.
2. Distracted Driving Prevention - Creating innovative solutions that utilize machine vision and AI to identify distracted driving behaviors and deliver real-time notifications to drivers.
3. Road Safety Enhancement - Implementing tools and devices that leverage machine vision and AI algorithms to improve overall road safety by addressing the dangers of drowsy and distracted driving.
Industry Implications
1. Automotive Technology - Exploring opportunities in the automotive industry to integrate machine vision and AI technologies into vehicles to detect and prevent drowsy and distracted driving.
2. Transportation and Logistics - Integrating machine vision and AI systems into commercial vehicles to help monitor driver attentiveness, reduce accidents, and enhance transportation safety.
3. Employee Wellness - Developing wearable devices and technology solutions that use machine vision and AI to promote driver safety by detecting signs of drowsiness and distraction in professional drivers.
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