LIS2DW12, the latest accelerometer from ST Microelectronics, allows engineers to create highly functional IoT and wearable applications that simultaneously leverage the compact design so popular on the market today.
Today’s electronics are only becoming smaller, sleeker and – contrary to the nature of electrical circuits – more capable. In a market where designers can’t afford to limit functionality even as the products they create become thinner and more compact, ST Microelectronics delivers their new accelerometer LIS2DW12, a solution built especially to help them address that challenge.
LISDW12 is a unique, small-form solution from ST Microelectronics offering users valuable flexibility in designing their products. With this accelerometer, you can turn on or off a special Low Noise feature, and you also have the option of choosing between a high-performance mode, four low-power modes and nine different output data rates. Therefore, engineers are able to pinpoint where they need to be to strike a perfect balance between power consumption and signal integrity.
LISDW12 (like its predecessor LIS2DS12) is incredibly compact with dimensions of 2 mm x 2 mm x 0.7 mm, and it has user-selectable full-scale ranges to measure acceleration, an operating temperature of -40ºC to +85ºC, a 16-bit data output, and 10,000 g high-shock survivability.
The accelerometer offers a current consumption of 50 nA in power-down mode as well as a draw of only 0.38 µA at 1.6 Hz in Low Power Mode 1 and Low Noise OFF, which is a huge benefit to engineers wanting to improve application battery life. LIS2DW12 has a 32-level FIFO and allows the stystem to store data from the sensors until the host MCU wakes up. It’s a great solution for IoT and wearable technologies, which often need to wake up for a number of reasons.
Shop LISDW12 at Arrow.com and get started creating solutions that can more precisely distinguish between periods of user activity and inactivity as well as incorporate features like double-tap detection, free-fall recognition and portrait/landscape detection.
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