Fairy Devices Inc. Tokyo, Japan, November 11th, 2021 – Fairy Devices today announced that the company has been named a CES® 2022 Innovation Awards Honoree for LINKLET™ by three categories: Wearable Technology, Streaming, Digital Imaging/Photography. This year’s CES Innovation Awards program received a record high number of over 1,800 submissions. The announcement was made ahead of CES 2022, the world’s most influential technology event, happening Jan. 5-8 in Las Vegas, NV and digitally.
LINKLET is an LTE-embedded wearable device with super-wide-angle camera. Wearing this hands-free device, users can enjoy one-to-many communication via Teams/Zoom, livestreaming first-person view, and have real-time feedback from 100+ audience on their shoulder. LINKLET has been developed as a part of THINKLET solution that utilizes the device for remote support from experts/advisors in field work.
LINKLET’s special features:
- Lightweight, shoulder-mounted design that does not block the wearer’s hands and does not interfere with work
- Simple usability for connection to Zoom/Microsoft Teams with high stability, security and operability
- 4K wide-angle camera to deliver detailed first-person view video
- With Wi-Fi and 4G LTE, always connected to the Internet for remote support and livestreaming
- USB Type-C port for various connections with external devices
- Dustproof and waterproof equivalent to IP54 for use outdoors
Find more about Fairy Devices: URL: https://fairydevices.jp/
Fairy Devices Inc. has developed applications of machine learning technologies, mainly speech technologies, to actual workplaces through its own VUI and VPA technologies, speech recognition/speech translation technologies, and cloud infrastructure as well as edge devices that utilize these technologies aiming to “provide a heart-warmer technology to be a help to users”. In addition, our integrated business solutions, developed from most recently researched applications, support digital transformation of various industries from device to cloud by implementing various data analysis generated by field workers.