A few months ago, Qualcomm announced the new Snapdragon Wear 3100 SoC for the next-gen smartwatches, and it promised better battery life. To leverage that claim, Fossil has now announced the Sport Smartwatch powered by the Snapdragon Wear 3100 platform. This is the first smartwatch to launch with the new SoC, and it claims to offer all-day battery life. The Fossil Sport Smartwatch dons a round dial, an interchangeable silicone strap, and comes in varied colour options for users.
The Fossil Sport Smartwatch runs on the latest Wear OS platform, and is touted to be swimproof as well. It is priced at $255 (roughly Rs. 18,500) for the silicone and leather strap, and $275 (roughly Rs. 20,000) for the stainless steel strap. It comes in six different colour options – gray, pink, red, blue, green, and black. The smarwatch is available in two dial sizes – 41mm and 43mm – and offers 28 interchangeable silicone straps as well (they come in 18mm and 22mm sizes). The Fossil Sport Smartwatch is already available online and at partnered retail stores in the US.
The new Fossil Sport Smartwatch comes with a swimproof design, supports Google Pay, GPS to track all kinds of activity, and heart rate sensing as well. It supports customisable dials and several watch faces to match users’ preferences. Connectivity options include Bluetooth version 4.1 and Wi-Fi 802.11 b/g/n. The wearable is compatible with Android and iOS smartphones, specifically with Android OS 4.4 Kit Kat and above (excluding Go edition) or iOS 9.3 and above.
As mentioned, Fossil notes that the wearable can last for up to a day, and when in low power mode, the battery can extend up to two days as well. Because of the new Wear OS platform, the Fossil Sport smartwatch also comes with Google Assistant for voice assistance as well.
To recall, Qualcomm launched the Snapdragon Wer 3100 SoC in September this year. consists of quad-core A7 processors, an integrated DSP, and an ultra-low power co-processor QCC1110. This co-processor is very tiny, is optimised for ultra-low power operation, and also integrates a deep learning engine for custom workloads, such as keyword detection, and is extensible over time.