NEW YORK – As more and more MEMS sensors are showing up in mobile devices, the focus of MEMS design has begun shifting from discrete MEMS components to MEMS sensor data integration.
How raw data from multiple sensors is “fused” and “interpreted” makes a noticeable difference in a system’s power consumption and apps performance, according to Ian Chen, executive vice president, Sensor Platforms, Inc., a San Jose, Calif.-based start-up.
Keeping that premise as the company mission, Sensor Platforms is rolling out Monday (March 26th) a library of software algorithms and middleware designed, according to company claims, “to interpret users’ contexts and intents” by using data from multiple sensors in mobile devices.
Commonly found MEMS sensors in today’s smart phones and tablets include accelerometers, magnetometers, gyroscopes and barometers.
The recently published EE Times Confidential’s MEMS Sector Database and Report calls the trend for integration of multiple MEMS sensors “the rise of sensor fusion revolution.”
The report points out that one unanswered question confronting today’s MEMS component suppliers and system designers is: “Who will determine the sensor architecture, where the processing will reside and the motherboard-level sensor fusion architecture?”
While some companies may integrate all these sensors in a single monolithic device and wrap everything in smart components (although not an easy feat), Sensor Platforms has chosen another approach: offer sensor fusion in software that’s hardware agnostic.
The company says that its single code-base software can be used across platforms. It can be run in its entirety on an apps processor, on a sensor hub, or spread over the system.
That gives one clear advantage to Sensor Platforms’ software-based sensor fusion, said Chen: flexibility. “Our software allows system designers to pick and choose different supply sources for each sensor. The flexibility in sourcing is critical since these sensors come at different price and performance points.”
Another advantage of Sensor Platforms’ software lies in the conservation of sensor power, according to the company.
Throwing more sensors into a mobile device is one thing. But how to minimize the associated power consumption is another.
Chen noted, “Up to 10mW is added in power consumption when sensors are in use.” Sensor Platforms’ software library, called “FreeMotion Library,” comes with a proprietary algorithm that can “turn off power hungry sensors, like the gyroscope, and emulate its function with lower power sensors when user movements are slow.” That translates into “dropping sensor power consumption by 90 percent,” he added.
Then, there is the issue of reliability. Although not broadly advertised, some smart phones’ compass calibration can be off by 90 degrees, according to Chen. “All sensors require frequent calibration to maintain their data quality,” he noted. Sensor Platforms’ FreeMotion Library is built on an architecture that supports reliable sampling, and ongoing cross-sensor calibration to assure reliable sensor information – both for application developers and end users, the company said.
In sum, just designing a number of MEMS sensors into one’s system is hardly enough to improve a system’s power consumption, flexibility in system designs, sensor data or reliability and apps’ performance.
Tony Massimini, chief of technology at Semico Research, noted: “Now with all this data, how do the system designers fully utilize it? We may be just scratching the surface.” Further, he acknowledged, “The industry is at an early stage. System designers, many new to MEMS, need software development tools.”
The need for SDK is not limited to systems designers. It extends to apps developers, who are trying to leverage motion data – collected by sensors in a mobile device – in their new apps.
Chen said Sensor Platforms is rolling out the FreeMotion library’s API, so the data produced by its sensor calibration and sensor fusion provides apps developers robust data with better accuracy. Further, Chen said that “apps need information and context about the user, not just the user’s location or changes in his motion or direction.” The FreeMotion software development kit offers “a foundation to extend the type of information that applications can gain from sensor data,” according to Sensor Platforms.
Sensor Platforms’ key competitors are likely to be MEMS sensor component suppliers, who are developing their own sensor fusion software.
Earlier this year, Freescale Semiconductor, for example, introduced its own sensor fusion algorithms called Xtrinsic for electronic compass. Electronic compass applications combine magnetometer-provided headings with corrections from inertial sensors that compensate for stray magnetic fields.
Freescale is offering its sensor fusion algorithms as a free download for its MEMS sensor users.
Meanwhile, STMicroelectronics last fall rolled out its own sensor fusion algorithms called iNEMO Engine Sensor Fusion Suite. According to ST, its iNEMO Engine can be combined with ST’s iNEMO Inertial Modules to create complete and customizable hardware/software multi-axis MEMS sensor solutions for enhanced motion and accurate heading recognition.
These MEMS sensor vendors use proprietary libraries to lock customers into their products, explained Sensor Platforms’ Chen, in contrast to his company’s hardware-independent sensor fusion software.
Semico’s Massimini, describing sensor fusion as “still at early stages,” expects “more innovation as it draws more attention.”
While the competitive landscape remains far from being defined, Massimini mentioned Movea as a potential competitor.
“Movea has been delivering solutions for several years while Sensor Platforms is a startup just hitting the market,” he said. Movea is offering motion-responsive software, firmware, and semiconductor IP for markets such as mobile and tablets, Interactive TV and sports and eHealth. Massimini noted, “Movea has developed a system that allows system developers to implement their algorithms using Movea IP blocks. Movea is working with a CAD vendor so the output of this tool can be used to design an ASIC.”