Sensor Platforms, ARM team on open source mobile sensor hub framework. April 7, 2013. Working with ARM Ltd., Sensor Platforms has released an open source software framework for implementing sensor hubs in ARM CPU based mobile phones, wearables, and the things to which they may be connected
ARM Endorses Open-Source Sensor Platform San Francisco, Calif. April 7, 2014 — Sensor algorithm software company Sensor Platforms Inc. (SPI) is getting into the open-source movement by transforming its internal sensor platform into an open-source platform for sensor hubs. SPI’s Open Sensor Platform (OSP) is aimed at simplifying sensor hubs and data collection, and ARM is on board with the plan.
Sensor Platforms and ARM Introduce Open Source Software To Enable Sensor Hub Implementations SAN JOSE, CA, April 7, 2014 – Sensor Platforms together with ARM announce the introduction of the world’s first open source software for sensor hub applications. The software, called Open Sensor Platform (OSP), will simplify the integration of sensors across multiple applications, and provide a flexible framework for more sophisticated interpretation and analysis of sensor data.
Pedestrian Dead Reckoning Enables Indoor Navigation Without WiFi– Dec 16, 2013. Just as in-vehicle navigation systems have already revolutionized finding street addresses, pedestrian navigation systems aim to revolutionize finding in-door locations. To actualize a whole range of pedestrian navigation applications, Sensor Platforms in San Jose, Calif. — the software specialists licensing motion algorithms — has added Pedestrian Dead Reckoning (PDR) to its FreeMotion Library of algorithms. Sensor Platforms’ PDR system uses 10-axis sensor fusion on the data from micro-electro-mechanical system (MEMS) sensors — accelerometers, gyroscopes, magnetometers and barometric pressure sensors (for altitude) — to calculate the distance traveled by a user as well as the user’s direction (bearing), working from the last known waypoint as read off a global position systems (GPS) chip. By calibrating to the user’s context, Sensor Platforms claims its PDR solution provides accuracy within a few percent of the distance traveled from the last known waypoint.
Enabling low-power sensor context on mobile devices – July 22, 2013 Making mobile platforms context-aware is a hot topic in today’s information-rich world. Using the sensors available on these platforms, one can infer the context of the device, its user, and its environment. This can enable new useful applications that make smart devices smarter. It is common to utilize machine learning to determine the underlying meaning in the large amount of sensor data being generated all around us. However, traditional machine learning methods (such as neural networks, polynomial regression, and support vector machines) do not directly lend themselves to application in a power-conscious mobile environment. The necessary techniques for ensuring effective implementation of sensor context are discussed.
Challenges for Indoor Positioning on a Smartphone – April 18, 2013 Indoor positioning using pedestrian dead reckoning (PDR) has received much academic and commercial interest over the years. But indoor positioning on a smartphone needs to allow for natural movement, providing reasonable results independent of how the phone is carried.
Beyond sensor fusion, Making smartphones smarter – December 17, 2012 Sensor fusion is now integrated into most smartphones and tablets, enabling many mobile apps. But consumers want more: they want their mobile devices to be even smarter without having to learn any new interfaces themselves. This article provides an overview of a new class of sensor applications that go beyond sensor fusion, using sensor data to interpret user contexts and thus open new possibilities for smart electronics.
What do smartphone sensors sense all day? – December 16, 2012. Data indicates that people typically only interact with their phone 6% of their waking day but sensors are available 100% of the time. This is the first of a few articles exposing the data that motivated our context awareness architecture.
A Case for Smart Sensors – December 14, 2012. Over the last few years, while sensors in smartphones have gotten smaller, now consume less power, and feature better performance, they haven’t gotten much smarter; while the performance of individual sensors has increased, their functionality has not expanded. What happened?
Algorithmic software library now enables context aware applications – December 6, 2012. By better understanding user contexts and intent, Sensor Platforms’ FreeMotion Library of algorithmic software now enables context aware applications on mobile devices to proactively engage with the user, and not merely interact with that user.
Improved context-awareness for mobile phones – December 4, 2012. A new version of its FreeMotion software library with features that improve the context awareness of mobile devices, making them smarter and less power-hungry.
Taking Context Awareness to the Next Level – December 4, 2012. Sensor Platforms’ FreeMotion Library of algorithmic software, working with sensor fusion, promises to enable context-aware applications on mobile devices to proactively engage with the user.
Software library uses sensor fusion for context-aware apps – December 3, 2012. Sensor Platforms has announced support for context-aware applications on mobile devices through its FreeMotion software library.
Context is king – November 21, 2012. Context is king, or at least will be as a world increasingly stitched together by sensors matures.
Comparing the effectiveness of sensors in mobile operating systems – October 8, 2012. Examines the differences among iOS, Android and Windows 8 in how they include sensors, in form and substance, and highlights a few different architectural decisions they made
Making sense from sensor fusion data – September, 2012. Discusses trade off in sensor fusion implementation on application processor and in sensor hubs.
System architecture + anthropology = Better sensor algorithms – Aug 8, 2012. Sensors in smart devices, evolving from pure metrological instruments to context-aware user assistance devices. Key points include sensor fusion with data input and algorithms, and power consumption control.
Understanding Virtual Sensors: From Sensor Fusion To Context-Aware Applications – July 10, 2012. Smart phones and tablets are far from ideal sensing platforms. Their manufacturers need to keep the product compact and inexpensive, which can compromise sensor reliability.
Sensor Fusion Or Sensor Confusion? – June 28, 2012. Explaining the role and need for sensor fusion in consumer electronics, featuring Sensor Platforms’ and Freescale.
The Future of Context-Interactive Devices. – May 11, 2012. Context awareness has become a hot topic in mobile devices. The idea seems self-evident: design these devices to be smart enough to adapt themselves to their users.
FreeMotion Provides Sensor Fusion For SmartPhone –May 2, 2012. Sensor Platforms’ FreeMotion Library is designed to improve the use of sensor suites like those found on smartphones using algorithms and heuristics to deliver improved results on position, attidude and movement. It can also provide virtual peripherals like a virtual gyroscope using sensor fusion.
Sensors in Smartphones: Beyond Landscape and Portrait Screen Orientation –April 9, 2012. Analysts project the smartphone and tablet industry will soon consume over $2 billion of sensors annually. Yet, for all that, the top mobile apps rarely involve sensors.
Sensor Platforms Introduces FreeMotion Library, SDK –March 27, 2012. Library algorithms use data from sensors in mobile devices to interpret users’ contexts and intents
MEMS’ new battleground: Hardware-agnostic sensor fusion? – March 26, 2012. Lead story about the introduction and benefits of our FreeMotion™ Library.”In sum, just designing a number of MEMS sensors into one’s system is hardly enough to improve a system …
Configuring mobile device sensors to ensure optimal performance – Feb. 6, 2012. Any developer who regularly uses sensors soon notices that the Android platform is not optimized for real-time sensor data acquisition. The article addresses the challenge to effectively combine and use data from a variety of sensors to infer higher-level information..
Sensors Expand Functions in Mobile Services – Dec. 12, 2011.Sensors can make mobile apps into smart companions but creativity is currently stifled by a few surmountable hurdles.