M A R C H 2 0 1 4

Wireless Gesture Recognition System

High-Accuracy MEMS Sensors

Andrew Pease, President & CEO of QuickLogic

SENSOR HUB PLATFORMS

QuickLogic:VERSATILE, LOW-POWER

SENSOR TECHNOLOGY

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CONTENTS

4 TECH ARTICLEUnderstanding Precision for MEMS Pressure Sensors

3

8COVER INTERVIEW

Interview with Andrew Pease President & CEO of QuickLogic14

20 FEATURED ARTICLEEnabling an Always-on Experience

UNDERSTANDING ACCURACYAND PRECISION FOR MEMSPRESSURE SENSORS

PRESSURE POINT:

In most applications, accuracy is one of the more critical specifications that a

product needs to meet. However, accuracy is also one of the more, if

not the most, confusing parameter for any product including MEMS pressure sensors. This application tip provides

system designers with insight to deal with the numerous sources

of confusion.

ACCURACY VERSUS PRECISION

Figure 1. The relationship between accuracy and precision.

Figure 2. A target provides an informative image of the difference between accuracy and precision.

“Some industries, such as automotive or aerospace specify how

accuracy should be measured to simplify

this process.”

Accuracy and precision are frequently used interchangeably, especially in promotional literature for sensor products. Two figures identify the obvious differences between the two specifications. Figure 1 shows the statistical distribution for precision versus the proximity to an actual, target or reference value for accuracy. A more precise sensor has a narrower distribution and a more accurate sensor is closer to the actual value. Alternatively, Figure 2 shows how precision and accuracy can increase or decrease independently.

Precision and resolution are also frequently abused parameters. Unlike precision, resolution is the smallest measurement a sensor can reliably indicate, which is typically important in identifying input changes at low signal levels from noise in the application. An analog to digital converter (ADC) that quantizes the smooth output of an analog sensor for use in a digital control application has increased resolution as the number of bits increases.

Figure 3. The visual difference between accuracy and resolution and an ideal sensor. High resolution and high

accuracy occur in the upper right hand corner.

ALLSEE: AN ALWAYS-ON, WIRELESS GESTURE

RECOGNITION SOLUTIONImagine turning off the lights in your apartment with the swipe

of a hand from anywhere in your home, or lowering the volume of your phone’s music by lowering your hand. Imagine no longer—

AllSee is here. Developed by a dedicated team at the University of Washington, AllSee is a wireless, gesture-recognition solution that

uses significantly low amount of power for operation. Utilizing existing wireless signals through TVs and wireless routers, AllSee is able to

harvest power and gesture information from the changes in the wireless frequencies as a result of gesture commands.

Most gesture-recognition devices available today are limited to being in the line-of-sight of whatever device the user wants to interact with. Shyam Gollakota and a team of University of Washington engineers saw this limitation and decided to pursue a new alternative. Gollakota and his team developed WiSee–a gesture recognition software interface that seamlessly integrates with existing household or office devices. “What we proved with WiSee was that with

the proper software, you can actually enable gesture recognition, even if you are in a completely different room,” Gollakota told EEWeb. One of the biggest benefits of the WiSee interface is that it requires no additional sensor hardware—the device could simply detect Doppler shifts created by the user to determine the user’s command.

After receiving conservable recognition and awards for their work with WiSee, the University of Washington team addressed the remaining constraints to their original invention. The team began to focus on enabling the same technology with power-constrained devices. As of June of last year, the team began working towards that goal with the introduction of their new gadget, AllSee.

THE BEGINNINGS

By Paul Karazuba, QuickLogic

The future of sensors in mobile devices is truly exciting; not just the near-term future applications, but what lies beyond.

FEATURED ARTICLEAlways-on, Wireless Gesture Recognition

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TECH ARTICLE

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SENSOR TECHNOLOGY

UNDERSTANDING ACCURACYAND PRECISION FOR MEMSPRESSURE SENSORS

PRESSURE POINT:

In most applications, accuracy is one of the more critical specifications that a

product needs to meet. However, accuracy is also one of the more, if

not the most, confusing parameter for any product including MEMS pressure sensors. This application tip provides

system designers with insight to deal with the numerous sources

of confusion.

ACCURACY VERSUS PRECISION

Figure 1. The relationship between accuracy and precision.

Figure 2. A target provides an informative image of the difference between accuracy and precision.

“Some industries, such as automotive or aerospace specify how

accuracy should be measured to simplify

this process.”

Accuracy and precision are frequently used interchangeably, especially in promotional literature for sensor products. Two figures identify the obvious differences between the two specifications. Figure 1 shows the statistical distribution for precision versus the proximity to an actual, target or reference value for accuracy. A more precise sensor has a narrower distribution and a more accurate sensor is closer to the actual value. Alternatively, Figure 2 shows how precision and accuracy can increase or decrease independently.

Precision and resolution are also frequently abused parameters. Unlike precision, resolution is the smallest measurement a sensor can reliably indicate, which is typically important in identifying input changes at low signal levels from noise in the application. An analog to digital converter (ADC) that quantizes the smooth output of an analog sensor for use in a digital control application has increased resolution as the number of bits increases.

Figure 3. The visual difference between accuracy and resolution and an ideal sensor. High resolution and high

accuracy occur in the upper right hand corner.

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TECH ARTICLE

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SENSOR TECHNOLOGY

The first step toward comparing any pressure sensor data is using the same output specification of mm of mercury (Hg), kilopascals (kPA), bar, inches of water, etc. Typically, most MEMS pressure sensor measurements are made at a fixed voltage and room temperature. The two primary approaches for specifying accuracy are total error band and error budget.

SPECIFYING ACCURACY

When a company compares its own products with claims of twice the accuracy for one model or family over another, the comparison should be accurate. However, there are many accepted formats for measuring and specifying accuracy, so comparing the accuracy of one company’s product verses another company’s product is much more difficult. Some industries, such as automotive or aerospace specify how accuracy should be measured to simplify this process.

Accuracy is usually specified in terms of inaccuracy or error. In general, sources of error include: zero error, span error, pressure-non-linearity, thermal effect on zero, thermal effect on span, thermal hysteresis, pressure hysteresis, and non-repeatability. Other system considerations that can affect accuracy include response time, ratiometricity, long term stability or stability over life, and more.

Figure 4. The temperature error factor can increase the allowed sensor error by a value such as ±3 times at the temperature limits.

“Other factors that influence accuracy

are the characteristics shape of the curve of

the sensing technology and operating point of

the application.”

Figure 5. The error budget provides max and min tolerances around a typical level.

Total Error Band (TEB) accuracy specifies the maximum deviation of the output values within limits defined by the sensor’s underlying technology. In some instances, an error band multiplier increases the allowed inaccuracy at extremes such as increasing the temperature error at low and high temperatures as shown in Figure 4. The error band may also increase at pressure or other upper or lower limits.

TOTAL ERROR BAND

ERROR BUDGET

OBTAINING THE REQUIRED ACCURACY

Error Budget accuracy can consist of linearity, temperature and pressure hysteresis, the temperature coefficient of span, and the temperature coefficient of offset. Figure 5 shows a typical error budget plot. The transfer function can be provided with ±error values, and the limits may have a curved shape at upper or lower limits as well.

Other factors that influence accuracy are the characteristics shape of the curve of the sensing technology and operating point of the application. For example, an endpoint specification may not be appropriate for an application that normally operates in the mid-range of full scale. There several different approaches to specify sensor accuracy. Two common techniques have been discussed. The supplier’s choice of an accuracy specification usually involves the technology used for the sensor, choice of test equipment, ease of testing (frequently to address cost objectives) and/or a targeted volume market segment such as industrial, automotive, medical, consumer, etc. The challenge for the user when comparing products from different suppliers is to fully research each supplier’s methodology for specifying accuracy and then choose the approach and sensor that best meets the application requirements.

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TECH ARTICLE

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SENSOR TECHNOLOGY

ALLSEE: AN ALWAYS-ON, WIRELESS GESTURE

RECOGNITION SOLUTIONImagine turning off the lights in your apartment with the swipe

of a hand from anywhere in your home, or lowering the volume of your phone’s music by lowering your hand. Imagine no longer—

AllSee is here. Developed by a dedicated team at the University of Washington, AllSee is a wireless, gesture-recognition solution that

uses significantly low amount of power for operation. Utilizing existing wireless signals through TVs and wireless routers, AllSee is able to

harvest power and gesture information from the changes in the wireless frequencies as a result of gesture commands.

Most gesture-recognition devices available today are limited to being in the line-of-sight of whatever device the user wants to interact with. Shyam Gollakota and a team of University of Washington engineers saw this limitation and decided to pursue a new alternative. Gollakota and his team developed WiSee–a gesture recognition software interface that seamlessly integrates with existing household or office devices. “What we proved with WiSee was that with

the proper software, you can actually enable gesture recognition, even if you are in a completely different room,” Gollakota told EEWeb. One of the biggest benefits of the WiSee interface is that it requires no additional sensor hardware—the device could simply detect Doppler shifts created by the user to determine the user’s command.

After receiving conservable recognition and awards for their work with WiSee, the University of Washington team addressed the remaining constraints to their original invention. The team began to focus on enabling the same technology with power-constrained devices. As of June of last year, the team began working towards that goal with the introduction of their new gadget, AllSee.

THE BEGINNINGS

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TECH ARTICLE

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SENSOR TECHNOLOGY

To achieve a completely wireless, low power consumption device, the AllSee team knew it couldn’t rely on typical radio solutions due to high power consumption and computational expensive functions. With AllSee, the team developed a small sensor that can be implemented in an array of mobile devices that can extract and classify unique gesture information. By leveraging pre-existing wireless signals, the AllSee sensor can remain in always-on mode without the need for battery or power consumption. The sensor can harvest its necessary energy from these wireless transmissions.

AllSee sensor can determine a rich set of hand gestures by determining disturbances in ambient TV and wireless signals. These disturbances can not only extract information on particular gesture, but the distance of the user from the device as well. Another huge advantage of this technology is that gestures can be detected through bags, purses, and pockets.

BATTERY-FREE GESTURE RECOGNITION

“What we proved with WiSee was that with the proper software, you can actually enable gesture recognition, even if you are in a completely different room.”

THE FUTURE OF ALLSEEWe are talking to a lot of mobile phone companies that are interested in this technology,” Gollakota told EEWeb. He went on to provide an example that piqued the interest of these mobile phone providers; imagine being in a meeting and your phone begins to ring in your bag—you’d have to dig through it, find it, and silence it. “With our technology,” Gollakota said, “you would be able to swipe your hand in the air, and the phone would shut off.”

With the Internet of Things being one of the most talked about trends in the tech industry,

AllSee could fit nicely in the development of these new interconnected devices. Because AllSee integrates with wireless devices, it could enable smart sensing devices to be controlled not through your phone, but through gesture recognition. Nest Thermostats, wireless home audio systems, and smart lighting apparatuses could all potentially be controlled through AllSee’s rich set of unique hand gestures. Health monitoring systems could also benefit greatly from AllSee’s always-on capability, allowing data accumulation for an extended period of time. “We are now demonstrating that with this low-power device, you can still extract a great deal of crucial information,” Gollakota explained.

While still in the prototyping stage of development, AllSee is proving to be a viable solution for wireless gesture recognition technology, performing at a 97% accuracy rating. With current gesture recognition technology already implemented in devices like the Samsung Galaxy S4, it’s only a matter of time before this more efficient, powerful solution becomes ubiquitous in future smart device development.

“Nest Thermostats, wireless home audio systems, and smart lighting apparatuses could all potentially be controlled through AllSee’s rich set of unique hand gestures.”

“

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TECH ARTICLE

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SENSOR TECHNOLOGY

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COVER INTERVIEW

1514

SENSOR TECHNOLOGY

President & CEO of QuickLogic

QuickLogic is a programmable logic company that specializes in customizable semiconductor products for mobile devices. Their ultra-low-power sensor hub platform–the ArcticLink 3 S1–enables always-on sensing capabilities for new ecosystem technologies. The benefits of these solutions for the handset market ranges from extended battery life to improved sensor experiences.

EEWeb spoke with Andrew Pease, the president and CEO of QuickLogic, about the company’s customer-specific products, some new applications the company is targeting, and how they stand apart from the competition.

Interview withAndrew Pease

SENSOR HUB PLATFORMSVERSATILE, LOW-POWER

COVER INTERVIEWSENSOR TECHNOLOGY

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Could you give us a background on QuickLogic?

QuickLogic is a 25-year-old programmable logic company. When I joined them a little over seven years ago, we decided to take our programmable logic architecture, which was previously geared towards the general FPGA space—including communication, instrumentation, military, and so on—and go after the mobile space. Our sense was that the emerging mobile industry had the same needs as the communications industry: very quick time-to-market with hardware differentiation.

We started retooling QuickLogic by creating a variant of our one-time programmable architecture that was geared toward ultra-low-power and cost rather than performance and density. While we were making those changes, we also saw that, unlike the communications space, there were no classical FPGA engineers at our targeted customers in the mobile space. For instance, Cisco probably has thousands of engineers that know how to write Verilog or VHDL, and

who are able to implement designs with FPGAs. When you go into the mobile space and talk to engineers there about FPGAs, there is no one for that. We had to learn to change our positioning and approach in order to be successful.

What is the origin of the term “CSSP?”

We began to realize that we shouldn’t call this an FPGA. Instead, we should call it something much more appropriate for the type of solution we had and the business model we were going after. What we then came up with is this notion of a Customer Specific Standard Product, or “CSSP.” This means the silicon platform we have can be the same “standard” platform regardless of what we put in it. We can use the same piece of silicon with many customers, but we are in fact customizing with intellectual property using our programmable logic. Once we program it, it actually looks, behaves, and acts like an ASIC, which is one of the things that made us think that this would be a good play in the mobile market.

For the first couple of years, particularly with our first engagements with companies like Hewlett-Packard and Garmin, we were selling it like a product. However, what we really needed was a solution sale, so we expanded our engineering efforts to add software content to our offering. When we deliver a solution to a customer, we not only program the logic, but we also provide the drivers that make it work in the system. CSSPs are a companion device that will sit next to an application or baseband processor, so providing the drivers was an integral part of making this a really quick time-to-market solution.

What types of applications are QuickLogic targeting?

Within the mobile space, we are focused on applications where we can enhance the end user experience. In particular, we are focused on smartphones, tablets, wearables and mobile enterprise. When we look at subsystems in these types of devices, we always ask ourselves how we can improve battery life, enable more accurate sensor-related applications, enhance display viewability, and enable more comprehensive connectivity.

I will give you one specific example of that – through the use of our programmable logic, we were able to increase the standby time of one of our customer’s handset products from one week to one month. From my perspective, that’s just the tip of the iceberg in what we can offer to others.

Tell us about the peripheral I/O and what kind of sensors may be involved in that?

We’ve always had a Chief Technical Officer. When I joined QuickLogic, our CTO was also our VP of Engineering. What I observed is that people tend to pursue tasks that get you the quick results, and engineers are no different than anybody else. When you go for the quick result, you are not innovating. Four years ago, I told our CTO that he is in charge of innovation. We let him build a team of high-level software and hardware architects, and a very high level strategic marketing person. Their charter is to develop a real roadmap, finding areas where programmable logic in the mobile industry can make a difference—areas where we can deliver an application solution that can enhance the end user experience.

We conducted very in-depth market research to examine if sensors could be the next key area for us. We spent nine months going out and doing unbiased market research, and we found out that our technology could uniquely solve a major customer problem, enabling sensors to be continuously on and monitored 24-7. In addition, we found we could do so at less than 2% battery life. With our solution, we have been able to demonstrate that we provide an always-on, ultra-low-power sensor hub that addresses this notion of context awareness.

“ We’re not a product company; we’re a solutions company. While our programmable logic products enable very low power hardware, we believe it takes an entire ecosystem to be successful in the mobile market.”

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How do you differentiate yourself from your competitors?

We announced our always-on context aware sensor hub, called the ArcticLink 3 S1, in October of 2013. Fundamentally, it is based on our brand new, ultra-low-power, in-system reprogrammable logic.

The core technology behind ArcticLink 3 S1 is that we have a flexible fusion engine that was architected from the ground up to handle the repetitive computations associated with always-on sensing at extremely low power. When we embarked on this path, we heard very clearly from the sensor ecosystem– smartphone OEMs, MEMS sensor vendors and sensor algorithm companies–that true always-on sensing would only be deployed by OEMs if they were able to do it at less than 2% increase of the battery life.

Achieving that target is no trivial problem. Conventional wisdom is to run everything in software on a microcontroller. Well, that is like using a sledgehammer to drive in a tack. We rethought the entire architecture in order to run algorithms in more purpose-built hardware rather than running them in software. In doing so, we were able to meet that 2% threshold power number.

I always say we’re not a product company; we’re a solutions company. While our crown jewels – programmable logic – enable very low power hardware, we believe it takes an entire ecosystem to be successful in the mobile market. We work with several sensor guys to make sure that the sensor manager can interface seamlessly with any type of sensor. On the algorithm side, we partnered with a company called Sensors Platform, Inc., which has developed world class context awareness algorithms. They do this by monitoring accelerometer data, so it will know if you’re holding your phone, if it’s in your pocket, when it’s on the table, or if you’re walking, sitting, standing, etc.—those kinds of context awareness scenarios are thought to be the fundamental building blocks of the next possible killer apps. Application developers want to have that knowledge so they can write these clever algorithms that everybody wants to have.

For instance, you could have an algorithm that monitors your teenage kid while he or she is in the car. If they are in the passenger seat, then it’s ok to text, but if he’s in the driver seat, then the phone is disabled. Our whole goal is to develop an entire ecosystem, and that has been a real focus area for us in the last four years. We are making sure that we have close relationships with the application processor companies like Qualcomm, Broadcom, Marvell, Intel, you name it.

What is the culture at QuickLogic?

You’ve actually hit on my very favorite topics. If you look at my background, I am not a technologist; I’ve mostly been in sales my entire career. I went to the Naval Academy, and if you think of our service academies, what they do is to train leaders, so I view myself as more of a leader. The reason why I came into the semiconductor industry is because of a man named Jerry Sanders at AMD. He coined a phrase that I have repeated ever since I heard it, which is, “people first, profits and products will follow.” I have always believed that if you get the right people and you motivate them properly, then the profits and the products will fall into place, and that is how we do things here at QuickLogic. We have a very non-political culture; we have a pretty amazing human development person who keeps us on our toes. We have core values that include integrity, collaboration, openness, and innovation. Those are our four core values, and we actually spend quite a bit of time reinforcing these values.

I think that the QuickLogic culture is wonderful. Every six weeks we hold a communication meeting, and at the very end of it we have a recognition session to acknowledge employee anniversaries. There is not a communication meeting that goes by where we won’t recognize people that have been here for 10-20 years. If you think of the changes that QuickLogic has been through over the last twelve years, that’s quite impressive. As Sun Tzu said, your greatest strength can become your greatest weakness and we can’t allow people to be complacent. That’s where leadership comes in to play—keep the edge up but keep the focus on people.

What excites you the most about the future of your company and the products that you have?

What excites me the most is that we have recently added a robust, new, in-system, reconfigurable logic technology to go along with our existing non-volatile programmable logic technology. With this new capability, we can actually solve very different problems across the mobile industry for hardware differentiation. What I am most excited about is that we are finding, after three years of putting together road maps, that now we have really great applications solutions with well-defined end user benefits. These benefits are focused on people who use smartphones. The fact that we now have solutions that address the general smartphone market means the opportunity there for us is enormous. We’ve done a great job at looking at the industry, aligning ourselves tactically, and positioning us strategically where we need to be in order to effectively pursue that opportunity. I’m really proud of what we’ve been able to accomplish as a team. ■

“I have always believed that if you get the right

people and you motivate them properly, then the

profits and the products will fall into place, and

that is how we do things here at QuickLogic.”

“ Our whole goal is to develop an entire ecosystem, and that has been a real focus area for us in the last four years.”

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By Paul Karazuba, QuickLogic

The future of sensors in mobile devices is truly exciting; not just the near-term future applications, but what lies beyond.

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NDOOR navigation and fitness are some of today’s hot sensor applications. With indoor navigation, users can track their movements and locations within hard-to-navigate locations such as shopping malls and airports. Fitness data can be used by everyone to judge their physical activity, which hopefully encourages us all to do just a bit more for ourselves.

The challenge for manufacturers is to implement these “always-on” applications (and many more like them) without consuming too much power. Consumers don’t want to have to remember to manually turn on sensors when starting a run, and they don’t want to have to pause before entering a building to enable indoor navigation. We want our devices to adjust to our activity, not the other way around. The only way to do this is to leave the sensor subsystem on 100% of the time. While being ‘always-on’ is technically possible with all current implementations of sensor subsystems (Application Processors or Microcontrollers), it is not practical due to power consumption. In a smartphone, an application processor-based sensor system may consume 8% of device battery life just on sensor management; a microcontroller 4%. On wearables, this percentage grows dramatically due to smaller

capacity batteries. QuickLogic has introduced a new approach to sensor management. Rather than process sensor data and run context algorithms on multi-purpose, non-optimized devices, the company built a sensor hub from the ground up, without the overhead associated with those multi-purpose devices. The core of QuickLogic's ArcticLink® 3 S1 sensor hub is designed to process sensor data in the most power-efficient way possible, with all the capabilities OEMs and consumers require for always-on context awareness. The net result is a sensor subsystem, with all required processing and sensor management capabilities that consumes nearly 1% of battery life—well within the OEM threshold for implementation of always-on sensor subsystems, and a level comfortable to consumers.

So what does this enable? Frankly, the possibilities are endless.

Indoor navigation is great—it’s a fantastic first step. But let’s go further—and consider indoor location, the fusion of indoor navigation with data, and take a look at what we could be seeing in four to five years. Imagine you are traveling in an unfamiliar place, and as you walk through a shopping center, you start to get hungry. You pass by a restaurant, stop and view the menu, and then decide that it’s not for you. You walk a few hundred feet up, and do the same at the next restaurant, and again decide it isn’t for you. Your phone, using indoor navigation, knows exactly where you are. Your location data (provided you’ve opted-in for such services) knows that you’ve stopped in two specific locations and paused, and that those locations are restaurants—your phone now knows that you are hungry. The restaurant app on your phone activates, and sends you a message that there is a local franchise of a chain restaurant you rated very high a few weeks ago located one floor up from where you are, and then provides step-by-step directions. It also confirms that there is a table available (and offers to reserve it for you),

then offers you a 15% off coupon, and finally asks if you would like to order your favorite drink prior to arrival.

Fitness applications today are good—but they are going to be a lot better. Current applications track your steps, and some even provide an estimated calorie burn. In a few years, you’re not only going to get accurate calorie burn measurements from your device, but also overall health information. The sensor sub-system will track not only your steps, but will also be able to track your contexts (running, walking), as well as elevation changes. This allows your device to differentiate between 1000 walking steps on a gentle slope, or 1000 running steps up the side of a steep hill—quite different caloric burn rates. Your phone or wearable will also have a heart rate monitor, sensing your pulse as you go about your day, understanding how strenuous your activities are and tying those to calorie burns as well. There are even some who say that soon, wearable devices will become powerful tools for you and your doctor as they measure your heart rate, respiration, and blood pressure constantly, and can even act as emergency transponders for the sick or elderly.

Those two applications just scratch the surface. The pressure, temperature, and humidity sensors that will soon appear in almost all

smartphones can be purposed, with an always-on sensor hub, to act as weather stations. Imagine the possibilities of weather forecasters and disaster preparedness officials having access to millions of localized weather stations in event of tornados or other significant weather events. Speaking of disasters, in the event of a building collapse or earthquake, data gathered from smartphones or wearable sensors (in this case, accelerometers, magnetometers, gyroscopes, and pressure sensors) could provide the current, or last-known, location of a trapped person to an accuracy of 18 inches or so, speeding recovery efforts and minimizing risk to rescuers. Even advertisers can get in on the game, tracking (at a macro level) consumer reaction to different advertisements in public places, using data provided by on-board magnetometers and positioning data to determine how many consumers viewed a specific advertisement, and for how long. All of these are very exciting, but require an always-on sensor subsystem to be truly useful and convenient.

The future of sensors is very exciting, especially with always-on context awareness enabled by ultra-low power sensor hubs like the QuickLogic ArcticLink S1.

IWe want our devices to adjust to our activity, not the other way around.

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