One Llama Danger Listening App Can Save Many From A Hazardous Walk.

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One Llama Danger Listening App Can Save Many From A Hazardous Walk.

Headphones can be a quite a life savor for many people out there, whether its used to simply listen to music or an audio book, or even using it shut out the world from all its noisy sounds. The one trouble of this tho is being able to pay attention to you surrounding while listen to our headphones. Taking a walk down a busy street and wandering into the street with cars passing by can lead to some serious trouble for headphone users if they hear the oncoming vehicles.

A Machine Learning Company.

Well thanks to One Llama, a recent startup that has dubbed themselves as, “a machine learning company, there just might be a away to avoid all of that gruesome traffic while listening to headphones. The startup has developed a technology that can mimic a likeness to that of the human ear so that any smartphone and wearable device can monitor the nearby sounds and warn the users of any approaching dangers. Yes, even when said user is heavily into their favorite music.

One Llama

Goals and Ideals.

One Llama has mentioned that the public will be getting its first look at this new world changing technology in a soon to be released application by the company. While the app won’t include the entire tech in its completion, the New York based startup still hopes it will get enough attention from various developers for smartphones, smart watches, smart glasses, etc. The kind of companies that will give them some sort of capital in exchange for the use of their software on their devices. The startup wishes to create a standard feature for all smart devices that will contain some sort of tech that will have a way for people to avoid any hazardous situation.

Now it's easier than ever to add Audio Intelligence to your Wearable Device

Work In Progress.

One Llama will currently only be made available for Android devices only. The app works by running silently in the background, constantly scanning for any dangers through sounds like sirens, screams, ambulance sirens, tire squeals and much more. The application will have a common amount of hazardous sounds savings its memory bank on its first day.

 

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About Author

Kevin is passionate about startups and loves to write about them. Previously Kevin ran a design studio. Now he loves to write about tech and startups.

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