Tag Archives: 32-bit ARM Core

The smart router is ready for IoT play


The evolution of router has reached the IoT’s doorsteps, and it raises some interesting prospects for industrial and smart home markets.


The router used to be largely a dumb device. Not anymore in the Internet of Things arena where node intelligence is imperative to make a play of the sheer amount of data acquired from sensors, machines and other ‘things.’ The IoT router marks a new era of network intelligence — but what makes a router smart?

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For starters, it employs embedded hardware platforms with DIY capabilities while balancing the performance and power consumption requirements. Next, an IoT router provides the operational status on an LCD screen while manipulating the data from different interfaces. In human machine interface (HMI) applications, for example, a smart router offers LCD and touch screen interfaces on expansion I/Os.

Take the case of the DAB-OWRT-53 smart router, which is developed by the Belgian design house DAB-Embedded. The sub-100 euro device — based on Atmel’s SAMA5D36 processor and OpenWRT router hardware platform — is mainly targeted at smart home and industrial IoT applications.

The smart router of DAB-Embedded

The IoT router supports popular wireless interfaces such as Wi-Fi, ZigBee and Z-Wave, as well as a diverse number of wired interfaces including Ethernet, USB, CAN 2.0A/B, KNX and RS-232. And all the data from these interfaces can be stored in either microSD card or NAND flash.

Anatomy of Smart Router

The Atmel | SMART SAMA5D36 is at the heart of the smart router design. First and foremost, it optimizes power consumption in the battery-operated router that features 3.7V lithium polymer battery support with charging capability over a microUSB connector. The router boasts eight hours of battery lifetime while being in full ON mode with Wi-Fi communications.

Second, the ARM Cortex-A5 processor shows a robust performance in the communications domain. For instance, the SAMA5D36 implements routing functionality to transfer data from one Ethernet port to another in a way that router designers don’t require an external hardware hub or switch. Moreover, Atmel’s MPU offers greater flexibility to run a lot of embedded software packages such as OpenZWave and LinuxMCE.

Third, the SAMA5D36-based IoT router offers users the ability to manipulate firewall settings, Disable PING, Telnet, SSH and UPnP features. Furthermore, the hardware security block in SAMA5D3 processor allows the use of CryptoDev Linux drivers to speed up the OpenSSL implementation. The Wi-Fi module — powered by Atmel’s WILC3000 single-chip solution — also supports the IEEE 802.11 WEP, WPA and WPA2 security mechanisms.

The smart router of DAB-Embedded employs Active-Semi’s ACT8945AQJ305-T power management IC, but the real surprise is Altera’s MAX 10 FPGA with an integrated analog-to-digital converter (ADC). That brings the additional flexibility for the main CPU: Atmel’s SAMA5D36.

The FPGA is connected to the 16-bit external bus interface (EBI) so that IoT developers can put any IP core in FPGA for communication with external sensors. All data is converted inside the FPGA to a specific format by using NIOS II’s soft CPU in FPGA. Next, the SAMA5D36 processor reads this data by employing DMA channel over the high-speed mezzanine card (HSMC) bus.

An FPGA has enough cells to start even two soft cores for data preprocessing. Case in point: A weather station with 8-channel external ADC managing light sensors, temperature sensors, pressure sensors and more. It’s connected to the FPGA together with PPS signal from GPS for correct time synchronization of each measurement.

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OpenWRT Framework

The SAMA5D36 embedded processor enables DAB’s smart router design to customize free OpenWRT Linux firmware according to the specific IoT application needs. The OpenWRT framework facilitates an easy way to set up router-like devices equipped with communications interfaces such as dual-port Ethernet and Wi-Fi connection.

What’s more, by using the OpenWRT framework, an IoT developer can add now his or her own application (C/C++) to exchange data with a KNX or Z-Wave transceiver. OpenWRT even supports the Lua embedded interpreter.

Next, while DAB-Embedded has built its smart router using the embedded Linux with OpenWRT framework, Belgium’s design house also offers a board support package (BSP) based on the Windows Embedded Compact 2013 software. That’s for IoT developers who have invested in Windows applications and want to use them on the new hardware: the DAB-OWRT-53 smart router.

Later, the embedded design firm plans to release smart router hardware based on the Windows 10 IoT software and Atmel’s SAMA5D family of embedded processors. The Belgian developer of IoT products has vowed to release the second version of its router board based on Atmel’s SAMA5D4 embedded processor and WILC3000 chipset that comes integrated with power amplifier, LNA, switch and power management. Atmel’s WILC3000 single-chip solution boasts IEEE 802.11 b/g/n RF/baseband/MAC link controller and Bluetooth 4.0 connection.


Majeed Ahmad is the author of books Smartphone: Mobile Revolution at the Crossroads of Communications, Computing and Consumer Electronics and The Next Web of 50 Billion Devices: Mobile Internet’s Past, Present and Future.

Profile of an IoT processor for the industrial and consumer markets


 If there’s a single major stumbling block that is hindering the IoT take-off at the larger industrial scale, it’s security.


The intersection of data with intelligent machines is creating new possibilities in industrial automation, and this new frontier is now being increasingly known as the Industrial Internet of Things (IIoT). However, if there is a single major stumbling block that is hindering the IoT take-off at the larger industrial scale, it’s security.

It’s imperative to have reliable data in the industrial automation environment, and here, the additional security layers in the IoT hardware often lead to compromises in performance. Then, there is counterfeiting of products and application software, which is becoming a growing concern in the rapidly expanding IoT market.

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Atmel’s answer to security concerns in the IIoT infrastructure: a microprocessor (MPU) that can deliver the security while maintaining the level of performance that Internet-connected systems require. The company’s Cortex A5 chip — the Atmel | SMART SAMA5D4 — securely stores and transfers data, as well as safeguards software assets to prevent cloning of IoT applications.

The SAMA5D4 series of MPUs enables on-the-fly encryption and decryption of software code from the external DRAM. Moreover, it boasts security features such as secure boot, tamper detection pins and safe erasure of security-critical data. The A5D4 processor also incorporates ARM’s system-wide security approach, TrustZone, which is used to secure peripherals such as memory and crypto blocks. TrustZone —comprising of security extensions that can be implemented in a number of ARM cores — is tightly integrated into ARM’s Cortex-A processors. It runs the processor in two different modes: First, a secure environment executes critical security and safety software, and secondly, a normal environment runs the rich OS software applications such as Linux. This lets embedded designers isolate critical software from OS software.

The system approach allows control access to CPU, memories, DMA and peripherals with programmable secure regions. That, in turn, ensures that on-chip parts like CPU and off-chip parts like peripherals are protected from software attacks.

Trust

Performance Uplift

The Atmel SMART | SAMA5D4 processor is based on the Cortex-A5, the smallest and simplest of the Cortex-A series cores that support the 32-bit ARMv7 instruction set. It’s targeted at applications requiring high-precision computing and fast signal processing — that includes industrial and consumer applications such as control panels, communication gateways and imaging terminals.

The use cases for SAMA5D4 span from kiosks, vending machines and barcode scanners, to smart grid, communications gateways and control panels for security, home automation, thermostats, etc. Atmel’s MPU features peripherals for connectivity and user interface applications. For instance, it offers a TFT LCD controller for human-machine interface (HMI) and control panel applications and a dual Ethernet MAC for networking and gateway solutions.

Apart from providing high-grade security, SAMA5D4 adds two other crucial features to address the limitations of its predecessor, SAMA5D3 processor. First, it uplifts performance through ARM’s NEON DSP engine and 128kB L2 cache. The NEON DSP with 128-bit single instruction, multiple data (SIMD) architecture accelerates signal processing for more effective handling of multimedia and graphics. Likewise, L2 cache enhances data processing capability for imaging applications.

The second prominent feature of the SAMA5D4 is video playback that boasts 720p resolution hardware video decoder with post-image processing capability. Atmel’s embedded processor offers video playback for H.264, VP8 and MPEG4 formats at 30fps.

A Quick Overview of the SAMA5D4

The SAMA5D4 processor, which got a 14 percent performance boost from its predecessor MPU, increasing operating speed to 528 MHz, is a testament of the changing microprocessor market in the IoT arena. Atmel’s microprocessor for IoT markets delivers 840 DMIPS that can facilitate imaging-centric applications hungry for processing power. Aside from that, the SAMA5D4 is equipped with a 32-bit wide DDR controller running up to 176 MHz, which can deliver up to 1408MB/s of bandwidth. That’s a critical element for high-speed peripherals common in the industrial environments where microprocessors are required to process large amounts of data.

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Finally, the SAMA5D4 is configurable in either a 16- or 32-bit bus interface allowing developers a trade-off between performance and memory cost. There are four distinct chips in the SAMA5D4 family: SAMA5D41 (16-bit DDR), SAMA5D42 (32-bit DDR), SAMA5D43 (16-bit DDR along with H.264 video decoder)and SAMA5D44 (32-bit DDR along with H.264 video decoder).

The SoC-specific hardware security and embedded vision capabilities are a stark reminder of specific requirements of different facets of IoT, in this case, industrial and consumers markets. And Atmel’s specific focus on security and rich media just shows how the semiconductor industry is getting around the key IoT stumbling blocks.


Majeed Ahmad is the author of books Smartphone: Mobile Revolution at the Crossroads of Communications, Computing and Consumer Electronics and The Next Web of 50 Billion Devices: Mobile Internet’s Past, Present and Future.

Secured SAMA5D4 for industrial, fitness or IoT display


To target applications like home automation, surveillance camera, control panels for security, or industrial and residential gateways, high DMIPS computing is not enough.


The new SAMA5D4 expands the Atmel | SMART Cortex-A5-based family, adding a 720p resolution hardware video decoder to target Human Machine Interface (HMI), control panel and IoT applications when high performance display capability is required. Cortex-A5 offers raw performance of 945 DMIPS (@ 600 MHz) completed by ARM NEON 128-bit SIMD (single instruction, multiple data) DSP architecture extension. To target applications like home automation, surveillance camera, control panels for security, or industrial and residential gateways, high DMIPS computing is not enough. In order to really make a difference, on top of the hardware’s dedicated video decoder (H264, VP8, MPEG4), you need the most complete set of security features.

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Whether for home automation purpose or industrial HMI, you want your system to be safeguarded from hackers, and protect your investment against counterfeiting. You have the option to select 16-b DDR2 interface, or 32-b if you need better performance, but security is no longer just an option. Designing with Atmel | SMART SAMA5D4 will guarantee secure boot, including ARM Trust Zone, encrypted DDR bus, tamper detection pins and secure data storage. This MPU also integrates hardware encryption engines supporting AES (Advanced Encryption Standard)/3DES (Triple Data Encryption Standard), RSA (Rivest-Shamir-Adleman), ECC (Elliptic Curves Cryptography), as well as SHA (Secure Hash Algorithm) and TRNG (True Random Number Generator).

If you design fitness equipment, such as treadmills and exercise machines, you may be more sensitive to connectivity and user interface functions than to security elements — even if it’s important to feel safe in respect with counterfeiting. Connectivity includes gigabit and 10/100 Ethernet and up to two High-Speed USB ports (configurable as two hosts or one host and one device port) and one High Speed Inter-Chip Interface (HSIC) port, several SDIO/SD/MMC, dual CAN, etc. Because the SAMA5D4 is intended to support industrial, consumer or IoT applications requiring efficient display capabilities, it integrates LCD controllers with a graphics accelerator, resistive touchscreen controller, camera interface and the aforementioned 720p 30fps video decoder.

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The MCU market is highly competitive, especially when you consider that most of the products are developed around the same ARM-based family of cores (from the Cortex-M to Cortex-A5 series). Performance is an important differentiation factor, and the SAMA5D4 is the highest performing MPUs in the Atmel ARM Cortex-A5 based MPU family, offering up to 945 DMIPS (@ 600 MHz) completed by DSP extension ARM NEON 128-bit SIMD (single instruction, multiple data). Using safety and security on top of performance to augment differentiation is certainly an efficient architecture choice. As you can see in the block diagram below, the part features the ARM TrustZone system-wide approach to security, completed by advanced security features to protect the application software from counterfeiting, like encrypted DDR bus, tamper detection pins and secure data storage. But that’s not enough. Fortunately, this microprocessor integrates hardware encryption engines supporting AES/3DES, RSA, ECC, as well as SHA and TRNG.

The SAMA5 series targets industrial or fitness applications where safety is a key differentiating factor. If security helps protecting the software asset and makes the system robust against hacking, safety directly protects the user. The user can be the woman on the treadmill, or the various machines connected to the display that SAMA5 MCU pilots. This series is equipped with functions that ease the implementation of safety standards like IEC61508, including a main crystal oscillator clock with failure detector, POR (power-on reset), independent watchdog timers, write protection register, etc.

Atmel-SMART-SAMA5D4-ARM-Cortex-MPU-AtmelThe SAMA5D4 is a medium-heavier processor and well suited for IoT, control panels, HMI, and the like, differentiating from other Atmel MCUs by the means of performance and security (not to mention, safety). The ARM Cortex-A5 based device delivers up to 945 DMIPS when running at 600 MHz, completed by DSP architecture extension ARM NEON 128-bit SIMD. The most important factor that sets the SAMA5D4 apart from the rest is probably its implemented security capabilities. These will protect OEM software investments from counterfeiting, user privacy against hacking, and its safety features make the SAMA5D4 ideal for industrial, fitness or IoT applications.


This post has been republished with permission from SemiWiki.com, where Eric Esteve is a principle blogger as well as one of the four founding members of the site. This blog first appeared on SemiWiki on October 6, 2015.

1:1 interview with Jean Anne Booth of UnaliWear


“What really makes the Kanega Watch different is that it goes where you go, both inside your home and away. It is discreetly styled, so there’s no stigma from wearing an assistive device, and it speaks to you in words.” 


In this interview, we feature Jean Anne Booth, a serial entrepreneur with a successful track record in hardware innovation, having previously launched and sold two large and notable companies. Her current project is UnaliWear, a wearable health technology startup that has recently made its Kickstarter debut. She comes with a wealth of experience, and her timing could’t be better as the wearable digital health market continues to unfold. What’s more, Kanega Watch — which we recently featured on Bits & Pieces — is looking to bring a much-needed vision for practical usage to that space.

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Tom Vu: What’s the main driver to going about this once again? Well, considering you did this before as the first person to launch the ARM Cortex-M3 at Luminary Micro?

Jean Anne Booth: Great question! I actually retired for a couple of years after I sold my last company to Texas Instruments. During this period, my mom turned 80, and she had a couple of incidents that made me start looking for a personal emergency response system for her. Many of the assistive devices available are flawed in one aspect of another. Most importantly, there are three reasons, which make them quite hard for seniors to desire to integrate into their lives. First, they are ugly. Secondly, if they have connectivity, the devices usually require some complicated installation of a tethered smart phone or access point. And one of the most overlooked objections, there is a big “HELP” button. This big button is quite visually disturbing. When you see the big “HELP” button made large for usability and functionality, it is so socially stigmatizing. I wanted my mom to live safely while being independent and not being socially stigmatized.

TV: How is the UnaliWear Kanega Watch different from other wearable tech?

JAB: Focus groups have called Kanega Watch a ‘wearable OnStar for seniors’ because we provide discreet support for falls, medication reminders, and a guard against wandering in a classically styled watch that uses an easy speech interface rather than buttons. What really makes the Kanega Watch different is that it goes where you go, both inside your home and away. It is discreetly styled, so there is no stigma from wearing an assistive device, and it speaks to you in words. The watch brand name “Kanega” is from Cherokee for “speak”.

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TV: Is what you’re creating really going to make our lives better?

JAB: Yes, it’s about being there when it counts. You can wear Kanega Watch on 24×7 basis, so you don’t forget to put it back on, and therefore you’re wearing when you need it. There is a very long battery life, unlike an Apple Watch, Android, or Samsung smartwatch. There is no need for an additional device, either an access point or a smartphone. For seniors, or those who are independent but vulnerable, it can help with issues at night like trips to the bathroom. It’s waterproof, not just water resistant, so you can wear it in the shower/bath (this is where a majority of falls happen), and also in your pool exercises. It works anywhere you go, and those who are vulnerable are not trapped at home. Importantly, there is a convenience to this as you’re wearing everything you need to stay safe.

For instance, here is one of the fundamental characteristics of how the watch works, and why our tagline is “Extending Independence with Dignity.” If the Kanega Watch wants to speak, it will ask permission first. It requests permission to speak by buzzing on the wearer’s wrist like a cellphone on silent, so there’s no visual or audible stigma of wearing an assistive device when socially inappropriate — like at church.

If it detects a potential fall, it will ask if you will need help, because two out of three falls do not require help. In fact, Kanega Watch will continuously monitor you – a kind of continuous welfare check. In a suspected fall, if you don’t respond to the request for permission to speak (for example, if you’re unconscious, unable to move, or unable to speak), then it will begin to escalate and then notify emergency and your contacts for help. There’s practical and smart logic built into the wearable.

Meds

TV: How has your experience in this industry going to help in fulfilling the practical/adoptable use of moving wearable tech toward broader acceptance/use?

JAB: To me, it’s not about advancing a category of technology. It’s about harnessing technology to solve real problems, and in this case, about allowing people to live independently, safely, for as long as possible. It’s been an interesting experience transitioning from semiconductors to healthcare, and has proven to be very rewarding building products that directly make people’s lives better. It’s a fantastic feeling!

TV: What hardware startups do you think are actually doing some really interesting things right now?

JAB: That’s a hard question for me because I’m biased toward products that make a difference and are directly useful. Often what is the most cool and interesting is not at all useful! One thing that our Kickstarter campaign has taught us is that the average person buying things that are cool is not quite in the same category as the people who would buy our wearable for seniors.

TV: How would you describe your team?

JAB: Today, our team consists of a cadre of three founders. Our CTO Marc DeVinney does all the hardware. Brian Kircher, who I’ve worked with for 14 years, does all the software for the Kanega Watch. I do everything else.

TV: Who do you look up to as a mentor now?

JAB: Jimmy Treybig, founder of Tandem Computers, has been a close friend for years and has always been helpful. Jimmy has been a source of a lot of wisdom. For this particular company, another extremely important mentor is my mother, Joan, who is also our Senior User Experience Advisor. She’s put together a number of focus groups, and has also been a lot of help in detailing the use cases.

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TV: What improvements will your product provide society? Perhaps even help the movement of IoT, connected things and wearables?

JAB: The Internet of Things promises to transform daily life, making it easier to work, shop, merchandise, exercise, travel and stay healthy. Really, thanks to billions of connected devices — from smart toothbrushes and thermostats to commercial drones and robotic companions for the elderly. It also will end up gathering vast amounts of data that could provide insights about our habits, religious beliefs, political leanings, sentiments, consumer interest, sports, and even as far as go to other highly personal aspects of our lives. I think the maturation of IoT and wearables is intertwined together. In some respects, what we are building at UnaliWear is also helping cement together the more meaningful adoption of wearables. In our particular case with the Kanega Watch, we couldn’t solve our user problem unless we could provide a better wearable device that is constantly connected all the time. Ultra-low power is very challenging fundamental backstop for every wearable device, and for most IoT devices as well. Our wearable includes cellular, GPS, and Wi-Fi built into one seamlessly integrated non-obtrusive wearable.

Our design goal for the Kanega Watch is that it must be wearable 24×7. It cannot be in a pocket or have requirements of being tucked into a purse. It also must have enough communications capability so that a senior is not stuck in their home all the time. To meet this goal, we have a unique patent-pending quick swap battery system enabling a user to not have to take the watch off to charge. The wearable can last 2 days for most users, and it comes with four batteries. It’s designed to have two batteries available on the charger and two batteries on the watch at all times. The device eliminates the need to be near a base station or smartphone.

Today, simply using built-in smartphone or app presents a couple of problems. Most seniors today don’t have nor operate a smart phone. Less than 5% of seniors over 80 years in age have a smart phone today. For the few seniors who do have smart phones, there are still problems using a smart phone for falls and reminders, because today’s smart phones still have only about 10 hours of real usage time per day.

TV: By 2050, what are some of your predictions for consumers or users interacting with technology on a day-to-day basis?

JAB: I do think that speech will definitely play a larger part in our interaction paradigm. Remember that popular Star Trek movie scene where they come back in time to save the whales and Scotty goes with Checkov to analyze the strength of the materials being used to make a housing for the whales, and the computer he is given is the original Macintosh. Scotty speaks to the Mac, Checkov reminds him that’s not the interface, and then Scotty picks up the mouse and speaks to the mouse. This seems to show a natural interface into the future as Scotty mistakes the old computer for one he can easily and naturally talk to. Now looking at where we are today – the senior population is the fastest growing population segment in the US, and by 2030 will be 20% of our total population. Today, there are 17 million seniors above the age of 75 who are living independently, yet only 2.2 million of those independent seniors have any kind of monitoring system to get help. Today’s 17 million seniors will burgeon to 27 million seniors by 2030. Natural speech interfaces and connectivity will be control what we’re able to build in the future.

TV: What question might you pose to someone in the middle of making a choice to purchase or carry something that is connected and electronically enabling for a senior in their lives?

JAB: I think the message is simple. We show over and over again that if you want to extend the time and quality of someone’s life, then extend their independence. That means you need products that a senior is willing to wear, and that fits into their active lifestyle. At its core, the wearable is based on an Atmel | SMART SAM4L Cortex-M4 MCU running FreeRTOS as the real time operating system and also includes the ATWINC1500 SmartConnect device for Wi-Fi. The Kanega Watch includes both Wi-Fi and cellular communications; when you’re at home, it uses your Wi-Fi. When you’re away, it transitions seamlessly to cellular.

unaliwear-prototype-progression

TV: Does the Kanega Watch have initial roots from the Maker Movement?

JAB: Yes, the roots are definitely Maker Movement – and also a lot of rapid prototyping (hardware’s version of the Lean Startup). We built our first industrial design prototypes at the TechShop in Austin, and our very first alpha design used a 3D-printed “box” as the “watch”. We make a lot of prototypes with rapid turn 3D-printing and CNC-machined aluminum. Before we built our own first prototypes, we created a software prototype on the Omate TrueSmart smart watch, which has dual 1.3 GHz ARM Cortex-A8’s running Android 4.0 “Ice Cream Sandwich.” Our only challenge with this prototype is that the battery life was an unsatisfying 5 hours – which meant that I had a battery pocket in my pocket and kept the watch plugged in with a cord hidden under my shirt when I needed to demonstrate over a long period, such as at a conference like SxSW. I like our current prototypes better!


Interested in learning more or have an elderly family member who could benefit from the Kanega Watch? Head over to UnaliWear’s current Kickstarter campaign here.

Arduino in research and biotech


Arduino’s acceptance into the biotech research community is evident from its increasing mentions in high-profile science and engineering journals. Mentions of Arduino in these journals alone have gone from zero to more than 150 in just in the last two years.


While it may be best known as staple for hobbyists, Makers, and hackers who build on their own time, Arduino and Atmel have a strong and rapidly growing following among professional engineers and researchers.

For biotech researchers like myself, experimental setups often require highly specific instruments with strict design rules for parameters such as timing, temperature, motion, force/pressure, and light. Such specific instruments would be time-consuming and expensive to have custom built, as the desired experimental conditions often change as we investigate different samples, cell types, etc. Here, Atmel chips and Arduino boards find a nice niche for making your own affordable, custom setups that are repeatable, precise, and automated. Arduino and Atmel provide microcontrollers in a myriad of form factors, I/O options, and connectivity that are available from a number of vendors. Meanwhile, freeware Arduino code and hardware drivers are also available with many sensors and actuators to go with your board. Best of all, Arduino is designed for a wide audience and range of experiences, making it easy to use for a variety of projects and complexities. So as experimental conditions or goals change, your hardware can easily be re-purposed and re-programmed according to specifications.

Arduino’s acceptance into the biotech research community is evident from its increasing mentions in high profile journals in science and engineering including Nature Methods, Proceedings of the National Academy of the SciencesLab on a Chip, Cell, Analytical Chemistry, and the Public Library of Science (PLOS). Mentions of Arduino in these journals alone have gone from zero to more than 150 in just in the last two years.

In recent years, Arduino-powered methods have started to appear in a variety of cutting edge biotechnology applications. One prominent example is optogenetics, a field in which engineered sequences of genes can be turned on and off using light. Using Arduino-based electronic control over lights and motors, researchers have constructed tools to measure how the presence or absence of these gene sequences can produce different behaviors in human neurons [1][6][7] or in bacterial cells [2]. Light and motor control has also allowed for rapid sorting of cells and gene sequences marked with fluorescent dyes, which can be detected by measuring light emitted to photodiodes. While the biology driving this research is richly complex and unexplored, the engineering behind the tools required to observe and measure these phenomena are now simple to use and well-characterized.

Neuroscientists Voights, Sanders, and Newman at the Open Ephys project provide walkthroughs and add-ons for using Arduino to help them create tools for probing cells.  From left to right, Arduino-based hardware for creating custom electrodes, providing multi-channel input to neurons, and for control over optogenetic lighting circuits.  [6],[7]

Neuroscientists Voights, Sanders, and Newman at the Open Ephys project provide walkthroughs and add-ons for using Arduino to help them create tools for probing cells. From left to right, Arduino-based hardware for creating custom electrodes, providing multi-channel input to neurons, and for control over optogenetic lighting circuits. [6],[7]

Neuroscientists Voights, Sanders, and Newman at the Open Ephys project provide walkthroughs and add-ons for using Arduino to help them create tools for probing cells. From left to right, Arduino-based hardware for creating custom electrodes, providing multi-channel input to neurons, and for control over optogenetic lighting circuits. [6],[7]

Arduino-based automation can be used for supplanting a number of traditional laboratory techniques including control of temperature, humidity, and/or pressure during cell culture conditions; monitoring cell culturing through automated sampling and optical density measurements over time; neurons sending and receiving electrochemical signals; light control and filtration in fluorescence measurements; or measurement of solution salinity. This kind of consistent, automated handling of cells is a key part of producing reliable results for research in cell engineering and synthetic biology.

Synthetic biologists Sauls et al. provide open-source schematics for creating an Arduino-powered turbidostat to automate the culturing of cells with recombinant genes. [5]

Synthetic biologists Sauls et al. provide open-source schematics for creating an Arduino-powered turbidostat to automate the culturing of cells with recombinant genes. [5]

Synthetic biologists Sauls et al. provide open-source schematics for creating an Arduino-powered turbidostat to automate the culturing of cells with recombinant genes. [5]

Arduino has also found an excellent fit in the microfluidics communityMicrofluidics is the miniaturization of fluid-handling technologies—comparable to the miniaturization of electronic components. The development of microfluidic technologies has enabled a myriad of technical innovations including DNA screening microchips, inkjet printers, and the screening and testing of biological samples into compact and affordable formats (often called “lab on a chip” diagnostics) [3]. Their use often requires precise regulation of valves, motors, pressure regulation, timing, and optics, all of which can be achieved using Arduino. Additionally, the compact footprint of the controller allows it to be easily integrated into prototypes for use in medical laboratories or at the point of care. Recent work by the Collins and Yin research groups at MIT has produced prototypes for rapid, point-of-care Ebola detection using paper microfluidics and an Arduino-powered detection system [4].

Microfluidic devices made from paper (left) or using polymers (right) have been used with Arduino to create powerful, compact medical diagnostics (Left: Ebola diagnostic from Pardee et. Al [4], Right: Platelet function diagnostic from Li et al. [9])

Microfluidic devices made from paper (left) or using polymers (right) have been used with Arduino to create powerful, compact medical diagnostics (Left: Ebola diagnostic from Pardee et. Al [4], Right: Platelet function diagnostic from Li et al. [9])

Microfluidic devices made from paper (left) or using polymers (right) have been used with Arduino to create powerful, compact medical diagnostics (Left: Ebola diagnostic from Pardee et. Al [4], Right: Platelet function diagnostic from Li et al. [9])

Finally, another persistent issue in running biological experiments is continued monitoring and control over conditions, such as long-term time-lapse experiments or cell culture.   But what happens when things go wrong? Often this can require researchers to stay near the lab to check in on their experiments. However, researchers now have access to on-board wi-fi control boards [8] that can send notifications via email or text when their experiments are completed or need special attention.  This means fewer interruptions, better instruments, and less time spent worrying about your setup.

The compact Arduino Yun microcontroller combines the easy IDE of Arduino with the accessibility of built-in wi-fi to help you take care of your experiments remotely [8]

The compact Arduino Yun microcontroller combines the easy IDE of Arduino with the accessibility of built-in wi-fi to help you take care of your experiments remotely [8]

True to Arduino’s open-source roots, the building, use, and troubleshooting of the Arduino-based tools themselves are also available in active freeware communities online [5]–[7].

Simply put, Arduino is a tool whose ease of use, myriad applications, and open-source learning tools have provided it with a wide and growing user base in the biotech community.


Melissa Li is a postdoctoral researcher in Bioengineering who has worked on biotechnology projects at UC Berkeley, the Scripps Research Institute, the Massachusetts Institute of Technology, Georgia Institute of Technology, and the University of Washington. She’s used Arduino routinely in customized applications in optical, flow, and motion regulation, including a prototype microfluidic blood screening diagnostic for measuring the protective effects of anti-thrombosis medications [9], [10]. The opinions expressed in this article are solely her own and do not reflect those of her institutions of research.

[1]       L. J. Bugaj, A. T. Choksi, C. K. Mesuda, R. S. Kane, and D. V. Schaffer, “Optogenetic protein clustering and signaling activation in mammalian cells,” Nat. Methods, vol. 10, no. 3, pp. 249–252, Mar. 2013.

[2]       E. J. Olson, L. A. Hartsough, B. P. Landry, R. Shroff, and J. J. Tabor, “Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals,” Nat. Methods, vol. 11, no. 4, pp. 449–455, Apr. 2014.

[3]       E. K. Sackmann, A. L. Fulton, and D. J. Beebe, “The present and future role of microfluidics in biomedical research,” Nature, vol. 507, no. 7491, pp. 181–189, Mar. 2014.

[4]       K. Pardee, A. A. Green, T. Ferrante, D. E. Cameron, A. DaleyKeyser, P. Yin, and J. J. Collins, “Paper-Based Synthetic Gene Networks,” Cell.

[5]       “Evolvinator – OpenWetWare.” [Online]. Available: http://openwetware.org/wiki/Evolvinator. [Accessed: 12-Jan-2015].

[6]       “Open Ephys,” Open Ephys. [Online]. Available: http://www.open-ephys.org/. [Accessed: 12-Jan-2015].

[7]       Boyden, E. “Very simple off-the-shelf systems for in-vivo optogenetics”. http://syntheticneurobiology.org/protocols/protocoldetail/35/9 [Accessed: 12-Jan-2015].

[8]       “Arduino Yun”. http://arduino.cc/en/Guide/ArduinoYun [Accessed: 12-Jan-2015].

[9]       “Can aspirin prevent heart attacks? This device may know the answer,” CNET. [Online]. Available: http://www.cnet.com/news/can-aspirin-prevent-heart-attacks-this-device-may-know-the-answer/. [Accessed: 12-Jan-2015].

[10]       M. Li, N. A. Hotaling, D. N. Ku, and C. R. Forest, “Microfluidic thrombosis under multiple shear rates and antiplatelet therapy doses.,” PloS One, vol. 9, no. 1, 2014.

 

Simply the highest performing Cortex-M MCU


Why develop a new MCU instead of using a high-performance MPU? Eric Esteve says “simplicity.”


By Eric Esteve

If you target high growth markets like wearable (sport watches, fitness bands, medical), industrial (mPOS, telematics, etc.) or smart appliances, you expect using a power efficient MCU delivering high DMIPs count. We are talking about systems requiring a low bill of material (BoM) both in terms of cost and devices count. Using a MCU (microController) and not a MPU (microProcessor) allows for the minimizing of power consumption as such device like the SAM S70 runs at the 300 MHz range, not the GigaHertz, while delivering 1500 CoreMark. In fact, it’s the industry’s highest performing Cortex-M MCUs, but the device is still a microcontroller, offering multiple interface peripherals and the related control capabilities, like 10/100 Ethernet MAC, HS USB port (including PHY), up to 8 UARTs, two SPI, three I2C, SDIOs and even interfaces with Atmel Wi-Fi and ZigBee companion IC.

Atmel has a wide MCU offering from the lower end 8-bit MCU to the higher end Cortex-A5 MPU.

The Cortex-M7 family fits within the SAM4 Cortex-M4 and the SAM9 ARM9 products.
The Cortex-M7 family offers high performance up to 645 Dhrystone MIPS but as there is no Memory Management Unit, we can not run Operating System such as Linux. This family targets applications with high performance requirements and running RTOS or bare metal solution.

This brand new SAM S/E/V 70 32-bit MCU is just filling the gap between the 32-bit MPU families based on Cortex-A5 ARM processor core delivering up to 850 DMIPS and the other 32-bit MCU based on ARM Cortex-M. Why develop a new MCU instead of using one of this high performance MPU? Simplicity is the first reason, as the MCU does not require using an operating system (OS) like Linux or else. Using a simple RTOS or even a scheduler will be enough. A powerful MCU will help to match increasing application requirements, like:

  • Network Layers processing (gateway IoT)
  • Higher Data Transfer Rates
  • Better Audio and Image Processing to support standard evolution
  • Graphical User Interface
  • Last but not least: Security with AES-256, Integrity Check Monitor (SHA), TRNG and Memory Scrambling

Building MCU architecture probably requires more human intelligence to fulfill all these needs in a smaller and cheaper piece of silicon than for a MPU! Just look at the SAM S70 block diagram below, for instance.

SAM S70 Block diagram

SAM S70 Block diagram

The memory configuration is a good example. Close to the CPU, implementing 16k Bytes Instruction and 16k Bytes Data caches is a well-known practice. On top of the cache, the MCU can access Tightly Coupled Memories (TCM) through a controller running at MPU speed, or 300 MHz. These TCM are part of (up to) 384 Kbytes of SRAM, implemented by 16 Kbytes blocks and this SRAM can also be accessed through a 150 MHz bus matrix by most of the peripheral functions, either directly through a DMA (HS USB or Camera interface), either through a peripheral bridge. The best MCU architecture should provide the maximum flexibility: a MCU is not an ASSP but a general purpose device, targeting a wide range of applications. The customer benefits from flexibility when partitioning the SRAM into System RAM, Instruction TCM and Data TCM.

SRAM Partition Atmel Cortex M7
As you can see, the raw CPU performance efficiency can be increased by smart memory architecture. However, in terms of embedded Flash memory, we come back to a basic rule: the most eFlash is available on-chip, the easier and the safer will be the programming. The SAM S70 (or E70) family offers 512 Kbytes, 1 MB or 2 MB of eFlash… and this is a strong differentiator with the direct competitor offering only up to 1 MB of eFlash. Nothing magical here as the SAM S70 is processed on 65nm when the competition is lagging on 90nm. Targeting a most advanced node is not only good for embedding more Flash, it’s also good for CPU performance (300 MHz delivering 1500 DMIPS, obviously better than 200 MHz) — and it’s finally very positive in power consumption.

Indeed, Atmel has built a four mode strategy to minimize overall power consumption:

  • Backup mode (VDDIO only) with low power regulators for SRAM retention
  • Wait mode: all clocks and functions are stopped except some peripherals can be configured to wake up the system and Flash can be put in deep power down mode
  • Sleep mode: the processor is stopped while all other functions can be kept running
  • Active mode
Atmel's SMART | ARM Cortex M7 SAM S Series Target Applications

Target Applications depicted above for Atmel’s SMART | ARM based Cortex M7 SAM S Series. The SAM S series are general-purpose Flash MCUs based on the high-performance 32-bit ARM based Cortex-M7 RISC processors with floating point unit (FPU).

If you think about IoT, the SAM S70 is suited to support gateway applications, among many other potential uses, ranging from wearable (medical or sport), industrial or automotive (in this case it will be the SAM V70 MCU, offering EMAC and dual CAN capability on top of S70).


This post has been republished with permission from SemiWiki.com, where Eric Esteve is a principle blogger as well as one of the four founding members of SemiWiki.com. This blog first appeared on SemiWiki on February 22, 2015.

Ready to wear sensor hubs


Majeed Ahmad explores the latest sensor hub offerings for wearable devices.  


By Majeed Ahmad

Atmel has beefed up its sensor hub offerings for wearable devices with SAM D20 Cortex M0+ microcontroller core to add more functionality and further lower the power bar for battery-operated devices. The SAM D20 MCUs offer ultra-low power through a patented power-saving technique called “Event System” that allows peripherals to communicate directly with each other without involving the CPU.

Atmel is part of the group of chipmakers that use low-power MCUs for sensor management as opposed to incorporating low-power core within the application processor. According to market research firm IHS Technology, Atmel is the leading sensor hub device supplier with 32 percent market share.

Sensor hubs are semiconductor devices that carry out sensor processing tasks — like sensor fusion and sensor calibration — through an array of software algorithms and subsequently transform sensor data into app-ready information for smartphones, tablets and wearable devices. Sensor hubs combine inputs from multiple sensors and sensor types including motion sensors — such as accelerometers, magnetometers and gyroscopes — and environmental sensors that provide light level, color, temperature, pressure, humidity, and many other inputs.

Atmel has supplied MCU-centric sensor hub solutions for a number of smartphones. Take China’s fourth largest smartphone maker, Coolpad, which has been using Atmel’s low-power MCU to offload sensor management tasks from handset’s main processor. However, while still busy in supplying sensor hub chips for smartphones and tablets, Atmel is looking at the next sensor-laden frontier: wearable devices.

SAM D20 Evaluation Kit

SAM D20 Evaluation Kit

Wearable devices are becoming the epitome of always-on sensor systems as they mirror and enhance cool smartphone apps like location and transport, activity and gesture monitoring, and voice command operation in far more portable manner. At the same time, however, always-on sensor ecosystem within connected wearables requires sensor hubs to interpret and combine multiple types of sensing—motion, sound and face—to enable context, motion and gesture solutions for devices like smartwatch.

Sensor hubs within wearable environment should be able to manage robust context awareness, motion detection, and gesture recognition demands. Wearable application developers are going to write all kinds of apps such as tap-to-walk and optical gesture. And, for sensor hubs, that means a lot more processing work and a requirement for greater accuracy.

So, the low-power demand is crucial in wearable devices given that sensor hubs would have to process a lot more sensor data at a lot lower power budget compared to smartphones and tablets. That’s why Atmel is pushing the power envelope for connected wearables through SAM D20 Cortex M0+ cores that offload the application processor from sensor-related tasks.

LifeQ’s sensor module for connected wearables.

LifeQ’s sensor module for connected wearables

The SAM D20 devices have two software-selectable sleep modes: idle and standby. In idle mode, the CPU is stopped while all other functions can be kept running. In standby mode, all clocks and functions are stopped except those selected to continue running.

Moreover, SAM D20 microcontroller supports SleepWalking, a feature that allows the peripheral to wake up from sleep based on predefined conditions. It allows the CPU to wake up only when needed — for instance, when a threshold is crossed or a result is ready.

The SAM D20 Cortex M0+ core offers the peripheral flexibility through a serial communication module (SERCOM) that is fully software-configurable to handle I2C, USART/UART and SPI communications. Furthermore, it offers memory densities ranging from 16KB to 256KB to give designers the option to determine how much memory they will require in sleep mode to achieve better power efficiency.

Atmel’s sensor hub solutions support Android and Windows operating systems as well as real-time operating system (RTOS) software. The San Jose–based chipmaker has also partnered with sensor fusion software and application providers including Hillcrest Labs and Sensor Platforms. In fact, Hillcrest is providing sensor hub software for China’s Coolpad, which is using Atmel’s low-power MCU for sensor data management.

The company has also signed partnership deals with major sensor manufacturers — including Bosch, Intersil, Kionix, Memsic and Sensirion — to streamline and accelerate design process for OEMs and ensure quick and seamless product integration.

Atmel-Sensor-Hub-Software-from-Hillcrest-Labs-Block-Diagram

Atmel Sensor Hub Software from Hillcrest Labs


 

This post has been republished with permission from SemiWiki.com, where Majeed Ahmad is a featured blogger. It first appeared there on February 4, 2015.  Majeed Ahmad is author of books Smartphone: Mobile Revolution at the Crossroads of Communications, Computing and Consumer Electronics and The Next Web of 50 Billion Devices: Mobile Internet’s Past, Present and Future. Majeed has a background in Engineering MS, former EE Times Editor in Chief (Asia), Writer for EC Magazine, Author of SmartPhone, Nokia’s SMART Phone.