News & Analysis
Sensor Fusion Goes Open-Source
Group to provide common algorithms
AUSTIN, Texas – Analog Devices, Freescale, PNI Sensor Corp., and the MEMS Industry Group formed the Accelerated Innovation Community, a group dedicated to providing open-source algorithms for sensors. AIC also plans to announce an I/O standard for sensors in collaboration with the MIPI Alliance.
Engineers shouldn't have "to reinvent the wheel on common algorithms every time they want to add or change functionality in their product," said Karen Lightman, executive director of the MEMS Industry Group (MIG). "Access to an open-source library of introductory algorithms fundamentally changes the development paradigm."
Freescale was an early catalyst of AIC and has added open-source algorithms such as a C source library for 3-, 6- and 9-axis sensor fusion. Sensor fusion is a basic building block for sensor data analytics and for motion tracking, said Freescale's Ian Chen.
"It's all about bringing the relevant data together from multiple sensors to provide a bigger picture of what's going on in a system," Steve Whalley, chief strategy officer at MIG and a former director of sensors at Intel, told EE Times. AIC aims to let engineers "focus their own real differentiating capabilities on the more complex algorithms that are needed for today's products above and beyond the introductory algorithms in the AIC."
The key challenge in sensor fusion is effectively separating signal, motion, and noise, Chen said. AIC's algorithms aim to take redundant data from different sensors that observe the same event to distinguish between noise and signals, then compute more accurate information.
"Sensor fusion encompasses a variety of techniques which leverage the inherent strengths and monitoring that these individual sensors do to achieve more accurate results than the individual components could achieve by themselves," Chen told EE Times.
Engineers shouldn't have "to reinvent the wheel on common algorithms every time they want to add or change functionality in their product," said Karen Lightman, executive director of the MEMS Industry Group (MIG). "Access to an open-source library of introductory algorithms fundamentally changes the development paradigm."
Freescale was an early catalyst of AIC and has added open-source algorithms such as a C source library for 3-, 6- and 9-axis sensor fusion. Sensor fusion is a basic building block for sensor data analytics and for motion tracking, said Freescale's Ian Chen.
"It's all about bringing the relevant data together from multiple sensors to provide a bigger picture of what's going on in a system," Steve Whalley, chief strategy officer at MIG and a former director of sensors at Intel, told EE Times. AIC aims to let engineers "focus their own real differentiating capabilities on the more complex algorithms that are needed for today's products above and beyond the introductory algorithms in the AIC."
The key challenge in sensor fusion is effectively separating signal, motion, and noise, Chen said. AIC's algorithms aim to take redundant data from different sensors that observe the same event to distinguish between noise and signals, then compute more accurate information.
"Sensor fusion encompasses a variety of techniques which leverage the inherent strengths and monitoring that these individual sensors do to achieve more accurate results than the individual components could achieve by themselves," Chen told EE Times.
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