Google Glass Enterprise Edition 2 gets FCC nod, might launch soon

Google takes yet another go at the AR wearable tech.

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Google seems to be planning to launch a new version of its not so popular Google Glass. The new pair of glasses will be called Google Glass Enterprise Edition 2 and will support augmented reality applications.

Google Glass Enterprise Edition 2 gets FCC nod, might launch soon

 

The glasses are said to have passed the FCC certification. There isn't a lot of information about the new device available in the documentation, likely due to agreements on confidentiality.

According to Android Headlines, the device will come with a 3.08Wh 800mAh-rated battery, and will also have support for dual-band Wi-Fi 802.11 a/b/g/n/ac, although only 802.11 a/b/n/ac appear to have been tested. It is also said to feature Bluetooth 5.0 connectivity.

The new pair of glasses is based on the original Enterprise Edition that was released in 2017 after a long test phase. The product, however, failed to impress the users and received an underwhelming response. The privacy concerns were also one reason for the low sales number of the product. They were also heftily priced at around $1,500 until the company finally introduced the first Enterprise-specific version.

Since the new version of the Google Glass is described as an Enterprise Edition in the FCC documentation, so there's no chance that the device will be available for general consumers. However, the listing does indicate that Google is still poised to develop AR-based products.

Besides, Google has also been awarded a new patent that uses eye-tracking cameras and AI to read facial expressions through eye imagery. The system will analyze how a person's face looks while they put a certain expression. It will then compare that data with the normal look of the user's eyes to create a unique profile of that particular facial expression.

Two of the AI researchers from Google have also developed an AI program for text classification. What's surprising is that the system works offline. The Ai can run on low-end devices and has achieved 86.7% accuracy on a simple data set, while 83.1% when the data is more complex.

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