Friday, December 12, 2014


Please pass this idea on to QUIK…..
Randy Newman song… that a lot of people like…..”Leave your hat on”
QUIK, with its low power allows you to….
“leave the sensors on”
Leave them on “always on”
you get a better result.
Play it to the same tune, “Leave your sensors on”


QUIK has given crucial incremental info in the last cc.

It's simple step counter is among ( maybe the ) most accurate out there.

How is it possible they could do that?  They had NO KNOWN expertise?


Steven Johnson's Adjacent possible is the answer....

You use the bits and pieces that are on your desk.



QUIK has really low power, it does not by design shut senor subsystems down( the MCU's do that by design and are fatally flawed here), it's the opposite, they leave the sensors on, take the data in to the algo, they get a much better result.  This is DURABLE and they can do it over and OVER for every new algo they write.


The major investment in software this past yr. will leverage this concept for all it's worth......


 Does QUIK have the bits and pieces to make THE best SoC for the IoT?

Indoor location is just HUGE...

The step counter that is the most accurate  is ONE building block.

In elevator location?

Just one more building block to put into that HUGE application.


IT"S DONE NOW.

QUIK today is NOT QUIK of even 6 mo ago.





QUIK, can you help the Samsung ASAP? thanks in advance....they really do need you.

Consider, they have the size range, the pixel density, the multicore APs, the thinness CANNOT differentiate Xiaomi from Samsung.  How do you differentiate now?

Someone will go " Always on " & Context Aware"

What was THE BEST thing in the last cc that I learned the most from?

That the later to market than many step countesr may be THE most accurate one out there?

Why?

They had NO known expertise in this.  How could it best others?

Answer, is they used the bits and pieces that are on their bench, ie if you have really low power, do NOT dummy it down.  Leave the sensors on and take in their data as much as possible and fuse it and you simply get a better result.  QUIK can do this over and over.  They will leave the sensors on.  Not just the mic, all the sensors..........its a better device and someone will move on it.




1:28pm EST - US Markets are closed


If This Really Is Samsung's New Phone, Next Year Is Going To Be Rough


Business Insider


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AP Samsung Mobile CEO JK Shin with the Galaxy S5 flagship phone. Samsung has a challenging year coming up.
Its profits have been tanking throughout 2014, mostly because its high-end Galaxy smartphones aren't selling as well as they used to. Sales of its flagship Galaxy S5 phone did not meet company expectations.
A lot of Samsung's recent misfortunes can be tied to the rise of smaller Android phone manufacturers like Xiaomi and OnePlus. Those startups make Android phones that are just as good as Samsung's best phones but cost half as much.
Xiaomi's phones are so popular that the company is now the third-largest smartphone vendor in the world and the top vendor in China.
Samsung's challenge for next year will be to find a way to differentiate its Galaxy phones from the rest of the cheap, generic Android devices out there. That's part of the reason why Apple's iPhone sales continue to grow. The iPhone may be expensive, but it provides a unique experience.
Samsung can't say the same thing about its phones. Its hardware designs and additional software features to Android don't offer enough to justify spending an extra $300 or $400 over a Xiaomi device.
On Friday, the Android-watchers were buzzing about a new leak from Samsung on a Dutch website. Some think it's the next flagship Galaxy S6 phone. Others think it's another phone called the A7.
It looks like this:


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Toptienmobiel
Whether it's the next flagship phone from Samsung or not, we most likely have a peek at what at least one of Samsung's new 2015 devices will look like. (It's not a final version of the phone, and things could change, but it's probably very close to what the product will look like when it launches. It could also be a fake.)
Whatever this thing is, it doesn't look that much different from what we saw this year and the year before.
It's still mostly plastic. It probably has some metal around the edges like the new Galaxy Note 4, but it still looks like any other Samsung device.
If this really is a taste at what Samsung has planned for 2015, it could be another tough year for the company.
On the other hand, it's entirely possible Samsung has dreamed up some crazy-cool new software features for the new phone that'll make it stand out. It's a stretch to think that, but anything's possible.
And keep in mind, Samsung isn't totally hosed. It's a massive company that makes everything from washing machines to medical equipment. Even if its profitable mobile division is faltering, there's still plenty of opportunity to research the next big thing.
We've heard one aspect of that will be "the internet of things," which means appliances and other household stuff that you control over the internet. Plus, the smartwatch market is just getting started.
But in the near-term, Samsung needs to really wow the world with its 2015 smartphone lineup. Otherwise, it's going to be another tough year.

Lots to think about in this one....

http://www.semi.org/en/node/52496?id=sguna1214t&utm_source=MagnetMail&utm_medium=email&utm_term=klightman@memsindustrygroup.org&utm_content=SEMI%20Global%20Update-Americas%2C%20December%202014&utm_campaign=Equipment%20Spending%20Growth%2C%20MEMS%2C%20Flexible%20Electronics%2C%20Women%20in%20Tech%2C%20Top%20Innovators%2C%20Europe%20Invests


MEMS Executive Congress 2014

MEMS Executive Congress 2014

What’s next for MEMS?
By Paula Doe, SEMI
The proliferation of sensors into high volume consumer markets, and into the emerging Internet of Things, is driving the MEMS market to maturity, with a developed ecosystem to ease use and grow applications. But it is also bringing plenty of demands for new technologies, and changes in how companies will compete.
While the IoT may be all about sensors, it is not necessarily a bonanza for most traditional MEMS sensor makers. “The surprising winner turns to be optical MEMS for optical cross connect for the data center, where big growth is coming,” said Jérémie Bouchaud, IHS Director and Sr. Principal Analyst, MEMS & Sensors, at the recent MEMS Executive Congress held in Scottsdale Arizona from November 5-7.
The market for wearables will also see fast growth for the next five years, largely for smart watches, driving demand for motion sensors, health sensors, sensor hubs and software –but even in 2019 the market for sensors in wearables will remain <5% the size of the phone/tablet market, IHS predicts.  The greater IoT market may reach billions of other connected devices in the next decade, but sensor demand will be very fragmented and very commoditized. Smart homes may use 20 million sensors in 2018, but many other industrial applications will probably each use only 100,000 to 2-3 million sensors a year, Bouchaud noted.
And most of this sensor market will be non-MEMS sensors, some mature and some emerging, including light sensors, fingerprint sensors, pulse sensors, gas sensors, and thermal sensors, all requiring different and varied manufacturing technologies.  Much of the new sensor demand from automotive will be also be for non-MEMS radar and cameras, though they will also add MEMS for higher performance gyros, lidar and microbolometers, according to IHS. Expect major MEMS makers to diversify into more of these other types of sensors.
Non-MEMS sensors to drive further
Figure 1: Growth shifts to new types of sensors. (Source: IHS)
Yole Développement CEO Jean Christophe Eloy looked at how the value in the IoT would develop.  While the emerging IoT market is initially primarily a hardware market, with hardware sales climbing healthily for the next five years or so, it will quickly become primarily a software and services market.  In five to six years hardware sales will level off, and the majority of the value will shift to data processing and value added services.  This information service market will continue to soar, to account for 75% of the $400 Billion IoT market by 2024.  
IoT Technologies
Figure 2: Initial IoT growth will be from hardware, but most of value will eventually be software and services. (Source: Yole Développement)

Re-thinking the business models?
The IoT will bring big changes to the electronics industry, from new technologies to new business models, as well as new market leaders, suggested George Liu, TSMC Director of Corporate Development.  He of course also argued that the high volume and low costs required for connected objects would drive sensor production to high volume foundries, while demand for smart distributed processing wouldrequire more integration with CMOS and give the advantage to  CMOS makers. 
Liu projected these changes will mean a new set of companies will come out on top. Few leading system makers managed to successfully transition from the PC era to the mobile handset era, or from the mobile handset era to the smart phone era, as both the key technologies and the winning business models changed, and chip makers faced disruption as well. “For one thing, the business model changed from making everything in house to making nothing,” he noted. “The challenge is to focus on where one is most efficient.”
“The odds of Apple or Google being the dominant players in the next paradigm is zero,” concurred Chris Wasden, Executive Director, Sorenson Center for Discovery and Innovation at the University of Utah.
Lots of other things will have to change to enable the IoT as well. Liu projected that devices will need to operate at near threshold or even sub-threshold voltages, with “thinner” processing overhead, while the integration of more different functions will redefine the system-in-a-chip. Smaller and lower cost devices will require new materials and new architectures, new types of heterogeneous integration and wafer-level packaging, and an ecosystem of standard open platforms to ease development. TSMC’s own MEMS development kit has layout rules, but not yet behavioral rules, always the more challenging issue for these mechanical structures. “That’s the next big thing for us,” he asserted. “These huge gaps mean huge opportunities.” 
IDMs and systems companies still likely to dominate                    
Still, the wide variety, and sometimes tricky mechanics and low volumes, of many MEMS devices have been a challenge for the volume foundries.  The fabless MEMS model has seen only limited success so far and that’s unlikely to change drastically in the next decade either, countered Jean Christophe Eloy, CEO of Yole Développement. He pointed out that some 75% of the MEMS business is dominated by the four big IDMs who can drive costs down with volumes and diversified product lines. To date, only two fabless companies–InvenSense and Knowles—are among the top 30 MEMS suppliers.
Most of the rest of the top 30 are system makers with their own fabs, making their own MEMS devices to enable higher value system products of their own, which is likely to continue to remain a successful approach, as the opportunities for adding value increasingly come from software, processers, and systems.  “MEMS value has always been at the system level,” noted Eloy. 
GE’s recent introduction of an improved MEMS RF switch to significantly reduce the size and cost of its MRI systems is one compelling example of systems-level value of MEMS, as the little MEMS component has the potential to greatly extend the use of this high-contrast soft-tissue imaging technology.  Though the company sold off its general advanced sensors unit last year to connector maker Amphenol Corp., it is still making its unique RF switch using a special alloy in house in small volumes as a key enabler of its high value MRI systems. These imagers work by aligning the spin of hydrogen nuclei with a strong magnet, tipping them off axis with a strong RF pulse from an antenna, then measuring how they snap back into alignment with lots of localized antennas with low power RF switches close to the body.  “We’re now launching a new receive chain using MEMS RF switches,” reported Tim Nustad, GM and CTO, Global Magnetic Resonance, GE Healthcare. “Later we can see a flexible, light weight MRI blanket.”  
Opportunity for smaller, lower power, lower cost technologies
So far, MEMS makers have driven down the cost of devices by continually shrinking the size of the die.  But that may be about to change, as the mechanical moving structures have about reached the limit of how much smaller they can get and still produce the needed quality signal.  That’s opening the door for a new generation of devices using different sensing structures and different manufacturing processes.  For inertial sensors, options include bulk acoustic wave sensing from Qualtre, piezoresistive nanowires from Tronics and CEA/Leti, and even extrapolating gyroscope-like data with software from accelerometers and magnetometers. MCube’s virtual gyro with this approach, now in production with some design wins, claims to save 80% of the power and 50% of the cost of a conventional MEMS gyro.
Piezoelectric sensing, often with PZT films, is also drawing attention, with products in development for applications ranging from timing devices to microphones. Sand9 claims lower noise and lower power for its piezoelectric MEMS timing, now starting volume manufacturing for shipments in 1Q15.  It has also recently received a patent for a piezo microphone, while startup Vesper (formerly known as Baker-Calling and then Sonify) also reports working with a major customer for its piezoelectric MEMS microphone.
More open platforms ease development of new applications of established devices
Meanwhile, the maturing ecosystem of open development platforms across the value chain is helping to ease commercialization of new applications of existing MEMS devices. The two latest developments in this infrastructure are a standard interface to connect all kinds of different sensors to the controller, and an open library of basic sensor processing software. The MIPI Alliance brought together major users and suppliers—ranging across STMicroelectronics and InvenSense, to AMD and Intel, to Broadcom and Qualcomm, to Cadence and Mentor Graphics—to agree on an interface specification to make it easier for system designers to connect and manage a wide range of sensors from multiple suppliers while minimizing power consumption of the microcontroller.  A collaboration ofsensor makers and researchers are also making a selection of baseline algorithms available for open use to help more users speed development of new applications.  Offerings include Freescale’s inertial sensor fusion and PNI Sensors’ heart rate monitoring algorithms, along with other contributions from Analog Devices, Kionix, NIST, UC Berkeley and Carnegie Mellon to start. The material will be available through the MIG website.               
Plenty of companies have also introduced their own individual platforms to ease customer development tasks as well, ranging from MEMS foundries’ inertial sensor manufacturing platforms to processor makers’ development boards and kits. Recently STMicroelectronics also adding its sensor fusion and other software blocks to its development platform.
KegData is one example of a company making use of these platforms to easedevelopment of a solution for a niche problem – an automated system for telling pub owners how much beer is left in their kegs, using a Freescale pressure sensor and development tools. Currently the only way to know when a beer keg is empty is to go lift and weigh or shake it, a problem for efficiently managing expensive refrigerated inventory.  Adding a pressure sensor in the coupler on top of the keg allows the height of the beer to be measured by the differential pressure between the liquid and the gas above it. The sensor then sends the information to a hub controller that communicates with the internet, letting the pub manager know to order more, or even automatically placing the order directly with the distributor.  The startup’s business model is to give the system to distributors for free, but sell them the service of automating inventory management for their customers, saving them the significant expense of sending drivers around to check the inventory and take pre-orders.
More broadly, MEMS microphones are poised to continue to find a wide range of new applications. IHS’ Bouchaud  pointed out that cars will soon each be using 12-14 MEMS microphone units, to listen for changes in different conditions, while home security applications will use them to detect  security breaches from unusual patterns of sounds, from people in the house to dogs barking. Startup MoboSens says it converts its chemical water quality data into audio signals to feed it into the phone’s mic port for better quality.
Opportunities still for new types of MEMS devices
Growth will also continue to come from new MEMS devices that find additional ways to replace conventional mechanical parts with silicon.    Eloy noted that MEMS autofocus units may finally be the next breakout device, as they have started shipping in the last few weeks, and aim at shipping for products in 2015.  MEMS microspeakers are also making progress and could come soon. But ramping new devices to the high volumes demanded by consumer markets is particularly challenging. “The only way to enter the market is with new technology, but high volume consumer markets make entry very hard for new devices,” he said. “The market is saturated, wins depend on production costs, and not everyone can keep up…. The last significant new device was the MEMS microphone, and that was ten years ago”.
But innovative new MEMS technologies also continue to be developed for initial applications in higher margin industrial and biomedical fields. One interesting new platform is the MEMS spectrometer from VTT Technical Research Center of Finland.  This robust tunable interferometer essentially consists of an adjustable air gap between two mirrors, made of alternating ALD or LPCVD bands of materials with different defraction indexes, explained Anna Rissanen, VTT research team leader for MOEMS and bioMEMS instruments. The structure can be tuned by different voltages to filter particular bands of light, while a single-point detector, instead of the usual array, enables very small and low cost spectrometers or hyper spectral cameras. VTT spinout Spectral Engines is commercializing near-IR and mid-IR sensors aimed at detecting moisture, hydrocarbons and gases in industrial applications.  Other programs have developed sensors for environmental analysis by flyover by nano satellites and UAVs, sensors for monitoring fuel quality to optimize energy use and prevent engine damage, and sensors that can diagnose melanoma from a scan of the skin.

A nice read of the BIG pic that supports the conclusion that things will get interesting...



Mobile tech: Thinner and lighter is no longer the biggest selling point


ZDNet


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Image: James Kendrick/ZDNet Mobile technology has advanced so quickly it's easy to forget that the gadgetry and the tech that drives it has only been around a few years. A decade ago smartphones as we know them now didn't exist, tablets were giant, heavy slabs, and laptops didn't like straying very far from a power outlet.
In the early days of mobile tech, with everything being big and bulky, making a device that was thinner and lighter than the rest was a big deal. OEMs and mobile enthusiasts were quick to proclaim that gadget X was the "thinnest in the world" or a similar claim. This was a legitimate response, as such devices were pushing the envelope of the genre.
That's no longer the situation, with most smartphones, tablets, and laptops very mobile in nature. Most are extremely thin, very light, and have battery life rated in lots of hours or even days.

    That's why prospective customers no longer get excited about the gadget that is a millimeter thinner than the rest of the pack. The pack is already skinny enough to meet most everyone's needs. A little less girth won't improve the user experience, and just about everyone knows that.
    With the exception of the iPhone, that's why people don't upgrade their devices in droves. Samsung and other major players in the mobile space are seeing that over and over. That new flagship phone or tablet doesn't fly off the shelves as fast as expected.
    That's likely because it is just an incremental improvement over the last version, which is already super thin and extremely light. Mobile devices are already highly mobile, and that's good enough for most buyers of the technology.
    That's probably why Apple took the iPhone bigger. It couldn't simply make the iPhone any thinner and lighter. The bigger displays gave the company something to push aggressively, even though it makes the iPhones less portable, and the competition is already doing this. The strategy seems to be working, with significant iPhone sales reported.
    The previous generation of the iPad is as thin as can be, and this may be affecting sales of the newest model. The latest iPad Air 2 is even thinner, but it's doubtful the average iPad Air owner is rushing out to get the new one just for the size.
    In a world of highly portable mobile devices, the worth of a new device that is slightly more mobile is negligible. Buyers aren't out looking for the new gadget that is the thinnest or lightest. They are more often than not looking for the app or update that improves the user experience.

    So much is at stake here for all the players, its in the realm that QUIK is focusing on now, Will track along.  We can see how the phrases of always on, context aware, or apps that make use of context differentiate a device going forward.  This will be a LOT better than the pixel density competition of a few yrs ago..
    It's now more important how well a mobile device does what users need, and in a good way.



    Wednesday, December 10, 2014

    I don't spend too much time on the VX side of things, but QUIK did say they may have another tablet slot to carry $$ well info '15.

    The tablet wars continue with a new  player in 15

    will track along....


    November 28, 2014


    CES 2015 @ Samsung Tomorrow

    December 5, 2014 |  0 Comments | Tomorrow Works
    CES 2015 @ Samsung Tomorrow.
    -Coming Soon-

    Tuesday, December 9, 2014


    http://jbsystech.com/hardware-and-software-methodologies-challenge-the-iot/



    Is Hardware Really That Much Different From Software

    When can hardware be considered as software? Are software flows less complex? Why are hardware tools less up-to-date? Experts from ARM, Jama Software and Imec propose the answers.
    By John Blyler, Editorial Director
    HiResThe Internet-of-Things will bring hardware and software designers into closer collaboration than every before. Understanding the working differences between both technical domains in terms of design approaches and terminology will be the first step in harmonizing the relationships between these occasionally contentious camps. What are the these differences in hardware and software design approaches? To answer that question, I talked with the technical experts including Harmke De Groot, Program Director Ultra-Low Power Technologies at Imec; Jonathan Austin, Senior Software Engineer at ARM; and Eric Nguyen, Director of Business Intelligence at Jama Software; . What follows is a portion of their responses. — JB
    Blyler: The Internet-of-Things (IoT) will bring a greater mix of both HW and SW IP issues to systems developers. But hardware and software developers use the same words to mean different things. What do you see as the real differences between hardware and software IP?
    De Groot: Hardware IP, and with that I include very low level software, is usually optimized for different categories of devices, i.e. devices on small batteries or harvesters, medium size batteries like mobile phones and laptops and connected to the mains. Software IP, especially for the higher layers, i.e. middleware and up can easier be developed to scale and fit many platforms with less adaptation. However practice learns that scaling for IoT of software also has its limitations, for very resource limited devices special measures have to be taken. For example direct retrieval of data from the cloud and combining this with local sensor data by a very small sensor node is a partly unsolved challenge today. For mobiles, laptops and more performing devices there are reasonable solutions (though also not perfect yet) to retrieve cloud data and combine this with the sensor information from the device in real-time. For sensoric devices with more resource constraints working on smaller batteries this is not so easy, especially not with heterogeneous networking challenges. Sending data to the cloud (potentially via a gateway device as a mobile phone, laptop or special router) seems to work reasonably, but retrieving the right data from the cloud to combine with the sensor data of the small sensor node itself for real-time use is a challenge to be solved.
    Austin: Personally, I see two significant differences between the real differences between hardware and software design and tools:
    1. How hard it is to change something when you get it wrong? It is ‘really hard’ for hardware, and somewhere on spectrum from ‘really hard’ to ‘completely trivial’ in software.
    2. The tradeoffs around adding abstraction to help deal with complexity. Software is typically able to ‘absorb’ more of this overhead than hardware. Also, in software it is far easier to only optimize the fast path. In fact, there usually isn’t as much impact to an unoptimised slow path (as would be the case in hardware.)
    3. There are differences in the tool sets. This was an interesting part of an ongoing debate with my colleagues. We couldn’t quite get to the bottom of why it is so common for hardware projects to stick with really old tools for so long. Some possible ideas included:
    • The (hardware) flow is more complex, so getting something that works well takes longer, requires more investment and results in a higher cost to switch tools.
    • There’s far less competition in the hardware design space so things aren’t pushed as much. This point is compounded by the one above, but the two sort of play together to slow things down.
    • The tools are hardware to write and more complex to use. This was contentious, but I think on balance, some of the simplicity and elegance available in software comes because people solve some really touch physical issues in the hardware tools.
    So, this sort of thinking led me to an analogy of considering hardware to be very low level software. We could have a similar debate about javascript productivity versus C – and I think the arguments on either side would like quite similar to the software versus hardware arguments.
    Finally on tools, I think it might be significant that the tools for building hardware are *software* tools, and the tools for building software are *also* software tools. If a tool for building software (say a compiler) is broken, or poor in some way, the software engineer feels able to fix it. If a hardware tool is broken in some way, the hardware engineer is less likely to feel like it is easy to just switch tasks quickly and fix it. So that is I guess to say, software tools are build for software engineers by software engineers, and hardware tools are built by software engineers to be sold to companies, to be given to hardware engineers!
    Nguyen: One of the historical differences relates to the way integrated system companies organized their teams. As marketing requirements came in, the systems engineers in the hardware group would lay out the overall design. Most of the required features and functionality were very electrical and mechanical in nature, where software was limited to drivers and firmware for embedded electronics.
    Today, software plays a much bigger role than hardware and many large companies have difficulties incorporating this new mindset. Software teams move at a much faster pace than hardware. On the other hand, software teams have a hard time integrating with the tool sets, processes and methodologies of the hardware teams. From a management perspective, the “hardware first” paradigm has been flipped. Now it is a more of software driven design process where the main question is how much of the initial requirements can be accomplished in software. The hardware is then seen as the enabler for the overall (end-user) experience. For example, consider Google’s Nest Thermostat. It was designed as a software experience with the hardware brought in later.
    Blyler: Thank you.


    Commentary, I think this artice is very good as giving some understanding of the changes that we have seen at QUIK, with most of the allocation in the past yr in software.

    this snip

     adding abstraction to help deal with complexity. Software is typically able to ‘absorb’ more of this overhead than hardware. Also, in software it is far easier to only optimize the fast path. In fact, there usually isn’t as much impact to an unoptimised slow path (as would be the case in hardware.)

    consider that this is a good explanation for the S3,  It will deal with complexity and do just as the above says.

    Also good at showing it is complex stuff to get it all put together in the right fashion.





    headache material is here, but give it a try...

    http://chipdesignmag.com/sld/blog/2014/12/02/iot-cookbook-analog-and-digital-fusion-bus-recipe/





    IoT Cookbook: Analog and Digital Fusion Bus Recipe

    Experts from ARM, Mathworks, Cadence, Synopsys, Analog Devices, Atrenta, Hillcrest Labs and STMicroelectronics cook up ways to integrate analog with IoT buses.
    By John Blyler, Editorial Director
    Many embedded engineers approach the development of Internet-of-Things (IoT) devices like a cookbook. By following previous embedded recipes, they hope to create new and deliciously innovative applications. While the recipes may be similar, today’s IoT uses strong concentration of analog, sensors and wireless ingredients. How will these parts combine with the available high-end bus structures like ARM’s AMBA? To find out, “IoT Embedded Systems” talked with the head technical cooks including Paul Williamson, Senior Marketing Manager, ARM; Rob O’Reilly, Senior Member Technical Staff at Analog Devices; Mladen Nizic , Engineering Director, Mixed Signal Solution, Cadence; Ron Lowman, Strategic Marketing Manager for IoT, Synopsys; Corey Mathis, Industry Marketing Manager -  Communications, Electronics and Semiconductors, MathWorks; Daniel Chaitow, Marketing Manager, Hillcrest Labs; Bernard Murphy, CTO, Atrenta; and Sean Newton, Field Applications Engineering Manager, STMicroelectronics. What follows is a portion of their responses. — JB
    Key points:
    • System-level design is needed so that the bus interface can control the analog peripheral through a variety of modes and power-efficient scenarios.
    • One industry challenge is to sort the various sensor data streams in sequence, in types, and include the ability to do sample or rate conversion.
    • To ensure the correct sampling of analog sensor signals and the proper timing of all control and data signals, cycle accurate simulations must be performed.
    • Control system and sensor subsystems are needed to help reduce digital bus cycles by tightly integrating the necessary components.
    • Hardware design and software design have inherently different workflows, and as a result, use different design tools and methodologies.
    • For low-power IoT sensors, the analog-digital converter (ADC) power supply must be designed to minimize noise. Attention must also be paid to the routing of analog signals between the sensors and the ADC.
    • Beyond basic sensor interfacing, designer should consider digitally assisted analog (DAA) – or digital logic embedded in analog circuitry that functions as a digital signal processor.
    Blyler: What challenges do designers face when integrating analog sensor and wireless IP with digital buses like ARM’s AMBA and others?
    Williamson (ARM): Designers need to consider system-level performance when designing the interface between the processor core and the analog peripherals. For example a sensor peripheral might be running continuously, providing data to the CPU only when event thresholds are reached. Alternatively the analog sensor may be passing bursts of sampled data to the CPU for processing.  These different scenarios may require that the designer develop a digital interface that offers simple register control, or more advanced memory access. The design of the interface needs to enable control of the peripheral through a broad range of modes and in a manner that optimizes power efficiency at a system and application level.
    O’Reilly (Analog Devices): One challenge is ultra-low power designs to enable management of the overall system power consumption. In IoT systems, typically there is one main SoC connected with multiple sensors running at different Output Data Rates (ODR) using asynchronous clocking. The application processor SoC collects the data from multiple sensors and completes the processing. To keep power consumption low, the SoC generally isn’t active all of the time. The SoC will collect data at certain intervals. To support the needs of sensor fusion it’s necessary that the sensor data includes time information. This highlights the second challenge, the ability to align a variety of different data types in a time sequence required for fusion processing. This raises the question “How can an entire industry adequately sort the various sensor data streams in sequence, in types, and include the ability to do sample or rate conversion.?”
    Nizic (Cadence): Typically a sensor will generate a small (low voltage/current) analog signal which needs to be properly conditioned and amplified before converting it to digital signal sent over a bus to memory register for further processing by a DSP or a controller. Sometimes, to save area, multiple sensor signals are multiplexed (sampled) to reduce the number of A2D converters.
    From the design methodology aspect, the biggest design challenge is verification. To ensure analog sensor signals are sampled correctly and all control and data signals are timed properly, cycle-accurate simulations must be performed. Since these systems now contain analog, in addition to digital and bus protocol verification, a mixed-signal simulation must cover both hardware and software. To effectively apply mixed-signal simulation, designers must model and abstract behavior of sensors, analog multiplexers, A2D converters and other analog components. On the physical implementation side, busses will require increased routing resources, which in turn mean more careful floor-planning and routing of bus and analog signals to keep chip area at minimum and avoid signal interference.
    Lowman (Synopsys): For an IC designer, the digital bus provides a very easy way to snap together an IC by hanging interface controllers such as I2C, SPI, and UARTs to connect to sensors and wireless controllers.  It’s also an easy method to hang USB and Ethernet, as well as analog interfaces, memories and processing engines.  However, things are a bit more complicated on the system level. For example, the sensor in a control system helps some actuator know what to do and when to do it.  The challenge is that there is a delay in bus cycles from sensing to calculating a response to actually delivering a response that ultimately optimizes the control and efficiency of the system.  Examples include motor control, vision systems and power conversion applications. Ideally, you’d want a sensor and control subsystem that has optimized 9D Sensor Fusion application. This subsystem significantly reduces cycles spent traveling over a digital bus by essentially removing the bus and tightly integrating the necessary components needed to sense and process the algorithms. This technique will be critical to reducing power and increasing performance of IoT control systems and sensor applications in a deeply embedded world.
    Mathis (Mathworks): It is no surprise that mathematical and signal processing algorithms of increasing complexity are driving many of the innovations in embedded IoT. This trend is partly enabled by the increasing capability of SoC hardware being deployed for the IoT. These SoCs provide embedded engineers greater flexibility regarding where the algorithms get implemented. The greater flexibility, however, leads to new questions in early stage design exploration. Where should the (analog and mixed) signal processing of that data occur? Should it occur in a hardware implementation, which is natively faster but more costly in on-chip resources? Or in software, where inherent latency issues may exist? One key challenge we see is that hardware design and software design have inherently different workflows, and as a result, use different design tools and methodologies. This means SoC architects need to be fluent in both C and HDL, and the hardware/software co-design environments needed for both. Another key challenge is that this integration further exacerbates the functional, gate- or circuit-level, and final sign-off verification problems that have dogged designers for decades. Interestingly, designers facing either or both of these key challenges could benefit significantly from top-down design and verification methodologies. (See last month’s discussion, “Is Hardware Really That Much Different From Software?”)
    Chaitow (Hillcrest Labs): In most sensor-based applications, data is ultimately processed in the digital realm so an analog to digital conversion has to occur somewhere in the system before the processing occurs. MEMS sensors measure tiny variations in capacitance, and amplification of that signal is necessary to allow sufficient swing in the signal to ensure a reasonable resolution. Typically the analog to digital conversion is performed at the sensor to allow for reduction of error in the measurement. Errors are generally present because of the presence of noise in the system, but the design of the sensing element and amplifiers have attributes that contribute to error. For a given sensing system minimizing the noise is therefore paramount. The power supply of the ADC needs to be carefully designed to minimize noise and the routing of analog signals between the sensors and the ADC requires careful layout. If the ADC is part of an MCU, then the power regulation of the ADC and the isolation of the analog front end from the digital side of the system is vital to ensure an effective sampling system.
    As always with design there are many tradeoffs. A given analog MEMS supplier may be able to provide a superior measurement system to a MEMS supplier that provides a digital output. By accepting the additional complexity of the mixed-signal system and combining the analog sensor with a capable ADC, an improved measurement system can be built. In addition if the application requires multiple sensors, using a single external multiple channel ADC with analog sensors can yield a less expensive system, which will be increasingly important as the IoT revolution continues.
    Murphy (Atrenta): Aside from the software needs, there are design and integration considerations. On the design side, there is nothing very odd. The sensor needs to be presented to an AMBA fabric as a slave of some variety (eg APB or AHB), which means it needs all the digital logic to act as a well-behaved slave (see Figure). It should recognize it is not guaranteed to be serviced on demand and therefore should support internal buffering (streaming buffer if an output device for audio, video or other real-time signal). Sensors can be power-hungry so they should support power down that can be signaled by the bus (as requested by software).
    The implementation side is definitely more interesting. All of that logic is generally bundled with the analog circuitry into one AMS block and it is usually difficult to pin down a floor-plan outline on such a block until quite close to final layout. This makes full-chip floor planning more challenging because you are connecting to an AMBA switch fabric, which likes to connect to well-constrained interfaces because the switch matrix itself doesn’t constrain layout well on its own. This may lead to a little more iteration of the floor plan than you otherwise might expect
    Beyond basic sensor interfacing, you need to consider digitally assisted analog (DAA). This is when you have digital logic embedded in analog circuitry, functioning as a digital signal processor to perform effectively an analog function but perhaps more flexibly and certainly with more programmability that analog circuitry. Typical applications are for beamforming in radio transmission and for super-accurate ADCs.

    Figure: The AMBA Bus SOC Platform is a configurable with several peripherals and system functions, e.g., AHB Bus(es), APB Bus(es), arbiters, decoders. Popular peripherals include RAM controllers, Ethernet, PCI, USB, 1394a, UARTs, PWMs, PIOs. (Courtesy of ARM Community - http://community.arm.com/docs/DOC-3752)
    Newton (STMicroelectronics): Integration of devices such as analog sensors and wireless IP (radios) is widespread today via the use of standard digital bus interfaces such as I2C and SPI. Integration of analog IP with a bus – such as ARM’s AMBA – becomes a matter of connecting the relevant buses to the digital registers contained within the IP. This is exactly what happens when you use I2C or SPI to communicate to standalone sensors or wireless radio, with the low-speed bus interfaces giving external access to the internal registers of the analog IP. The challenges for integration to devices with higher-end busses isn’t so much on the bus interface, as it is in defining and qualifying the resulting SoC. In particular, packaging characteristics, the number of GPIO’s available, the size of package, the type of processing device used (MPU or MCU), internal memory capability such as flash or internal SRAM, and of course the power capabilities of the device in question: does it need very low standby power? Wake capability?  Most of these questions are driven by market requirements and capabilities and must be weighed against the cost and complexity of the integration effort.
    The challenges for integration to devices with higher-end busses isn’t so much on the bus interface, as it is in defining packaging characteristics, available GPIOs, type of processing device, memory such as flash or internal SRAM, and power capabilities.