Mini Multi-Sensor Module for Wearables & IoT Designs

STMicroelectronics’s miniature SensorTile sensor board of its type comprises an MEMS accelerometer, gyroscope, magnetometer, pressure sensor, and a MEMS microphone. With the on-board low-power STM32L4 microcontroller, the SensorTile can be used as a sensing and connectivity hub for developing products ranging from wearables to Internet of Things (IoT) devices.

The 13.5 mm × 13.5 mm SensorTile features a Bluetooth Low-Energy (BLE) transceiver including an onboard miniature single-chip balun, as well as a broad set of system interfaces that support use as a sensor-fusion hub or as a platform for firmware development. You can plug it into a host board. At power-up, it immediately starts streaming inertial, audio, and environmental data to STMicro’s BlueMS free smartphone app.

Software development is simple with an API based on the STM32Cube Hardware Abstraction Layer and middleware components, including the STM32 Open Development Environment. It’s fully compatible with the Open Software eXpansion Libraries (Open.MEMS, Open.RF, and Open.AUDIO), as well as numerous third-party embedded sensing and voice-processing projects. Example programs are available (e.g., software for position sensing, activity recognition, and low-power voice communication).

The complete kit includes a cradle board, which carries the 13.5 mm × 13.5 mm SensorTile core system in standalone or hub mode and can be used as a reference design. This compact yet fully loaded board contains a humidity and temperature sensor, a micro-SD card socket, as well as a lithium-polymer battery (LiPo) charger. The pack also contains a LiPo rechargeable battery and a plastic case that provides a convenient housing for the cradle, SensorTile, and battery combination.

SensorTile kit’s main features, specs, and benefits:

  • Cradle/expansion board with an analog audio output, a micro-USB connector, and an Arduino-like interface that can be plugged into any STM32 Nucleo board to expand developers’ options for system and software development.
  • Programming cable
  • LSM6DSM 3-D accelerometer and 3-D gyroscope
  • LSM303AGR 3-D magnetometer and 3-D accelerometer
  • LPS22HB pressure sensor/barometer
  • MP34DT04 digital MEMS microphone
  • STM32L476 microcontroller
  • BlueNRG-MS network processor with integrated 2.4-GHz radio

Source: STMicroelectronics

Sensor-to-Cloud Kit for Developing IoT Applications

Interested in developing cloud-connected wireless sensing products? Silicon Labs recently introduced its Thunderboard Sense Kit for developing cloud-connected devices with multiple sensing and connectivity options. The “inspiration kit” provides you with all the hardware and software needed to develop battery-powered wireless sensor nodes for the IoT.

The Thunderboard Sense Kit’s features and benefits:

  • Silicon Labs EFR32 Mighty Gecko multiprotocol wireless SoC with a 2.4-GHz chip antenna
  • ARM Cortex-M4 processor-based
  • Supports Bluetooth low energy, ZigBee, Thread, and proprietary protocols
  • Silicon Labs EFM8 Sleepy Bee microcontroller enabling fine-grained power control
  • Silicon Labs Si7021 relative humidity and temperature sensor
  • Silicon Labs Si1133 UV index and ambient light sensor
  • Bosch Sensortec BMP280 barometric pressure sensor
  • Cambridge CCS811 indoor air quality gas sensor
  • InvenSense ICM-20648 six-axis inertial sensor
  • Knowles SPV1840 MEMS microphone
  • Four high-brightness RGB LEDs
  • On-board SEGGER J-Link debugger for easy programming and debugging
  • USB Micro-B connector with virtual COM port and debug access
  • Mini Simplicity connector to access energy profiling and wireless network debugging
  • 20 breakout pins to connect to external breadboard hardware
  • CR2032 coin cell battery connector and external battery connector
  • Silicon Labs’s Simplicity Studio tools support the Thunderboard Sense

The Thunderboard Sense kit (SLTB001A) costs $36. All hardware schematics, open-source design files, mobile apps, and cloud software are included for free.

Source: Silicon Labs

Human Vision Image-Sensing System Provides 10× Faster Recognition

Mouser Electronics is now offering Omron Electronic Components’s fully integrated B5T HVC-P2 face detection sensor modules. The Human Vision Component (HVC) plug-in modules are based on Omron’s OKAO Vision Image Sensing Technology, which is used to quickly and accurately detect human bodies and faces.Omron Image Sensors

Well suite for a variety of IoT applications, the face detection sensor modules comprise a camera and a separate main board that are connected via a flexible flat cable, which enables you to install it on the edge of a flat display unit. The boards feature UART and USB interfaces to control the module and send the data output (as no image output, 160 × 120 pixels, or 320 × 240 pixels) to an external system.

Available in both wide-angle (90-degree lens) and long-distance lenses (50-degree lens), the B5T HVC-P2 modules can detect a human body up to four times per second. The long-distance module can detect and presume attributes (e.g., gender and age, sight line, and facial expression) from a maximum distance of 3 m. The wide-angle module can cover an area 100 cm × 75 cm from a distance of 50 cm.

Source: Mouser Electronics

The Future of Biomedical Signal Analysis Technology

Biomedical signals obtained from the human body can be beneficial in a variety of scenarios in a healthcare setting. For example, physicians can use the noninvasive sensing, recording, and processing of a heart’s electrical activity in the form of electrocardiograms (ECGs) to help make informed decisions about a patient’s cardiovascular health. A typical biomedical signal acquisition system will consist of sensors, preamplifiers, filters, analog-to-digital conversion, processing and analysis using computers, and the visual display of the outputs. Given the digital nature of these signals, intelligent methods and computer algorithms can be developed for analysis of the signals. Such processing and analysis of signals might involve the removal of instrumentation noise, power line interference, and any artifacts that act as interference to the signal of interest. The analysis can be further enhanced into a computer-aided decision-making tool by incorporating digital signal processing methods and algorithms for feature extraction and pattern analysis. In many cases, the pattern analysis module is developed to reveal hidden parameters of clinical interest, and thereby improve the diagnostic and monitoring of clinical events.Figure1

The methods used for biomedical signal processing can be categorized into five generations. In the first generation, the techniques developed in the 1970s and 1980s were based on time-domain approaches for event analysis (e.g., using time-domain correlation approaches to detect arrhythmic events from ECGs). In the second generation, with the implementation of the Fast Fourier Transform (FFT) technique, many spectral domain approaches were developed to get a better representation of the biomedical signals for analysis. For example, the coherence analysis of the spectra of brain waves also known as electroencephalogram (EEG) signals have provided an enhanced understanding of certain neurological disorders, such as epilepsy. During the 1980s and 1990s, the third generation of techniques was developed to handle the time-varying dynamical behavior of biomedical signals (e.g., the characteristics of polysomnographic (PSG) signals recorded during sleep possess time-varying properties reflecting the subject’s different sleep stages). In these cases, Fourier-based techniques cannot be optimally used because by definition Fourier provides only the spectral information and doesn’t provide a time-varying representation of signals. Therefore, the third-generation algorithms were developed to process the biomedical signals to provide a time-varying representation, and   clinical events can be temporally localized for many practical applications.

This essay appears in Circuit Cellar 315, October 2016. Subscribe to Circuit Cellar to read project articles, essays, interviews, and tutorials every month!

These algorithms were essentially developed for speech signals for telecommunications applications, and they were adapted and modified for biomedical applications. The nearby figure illustrates an example of knee vibration signal obtained from two different knee joints, their spectra, and joint time-frequency representations. With the advancement in computing technologies, for the past 15 years, many algorithms have been developed for machine learning and building intelligent systems. Therefore, the fourth generation of biomedical signal analysis involved the automatic quantification, classification, and recognition of time-varying biomedical signals by using advanced signal-processing concepts from time-frequency theory, neural networks, and nonlinear theory.

During the last five years, we’ve witnessed advancements in sensor technologies, wireless technologies, and material science. The development of wearable and ingestible electronic sensors mark the fifth generation of biomedical signal analysis. And as the Internet of Things (IoT) framework develops further, new opportunities will open up in the healthcare domain. For instance, the continuous and long-term monitoring of biomedical signals will soon become a reality. In addition, Internet-connected health applications will impact healthcare delivery in many positive ways. For example, it will become increasingly effective and advantageous to monitor elderly and chronically ill patients in their homes rather than hospitals.

These technological innovations will provide great opportunities for engineers to design devices from a systems perspective by taking into account patient safety, low power requirements, interoperability, and performance requirements. It will also provide computer and data scientists with a huge amount of data with variable characteristics.

The future of biomedical signal analysis looks very promising. We can expect  innovative healthcare solutions that will improve everyone’s quality of life.

Sridhar (Sri) Krishnan earned a BE degree in Electronics and Communication Engineering at Anna University in Madras, India. He earned MSc and PhD degrees in Electrical and Computer Engineering at the University of Calgary. Sri is a Professor of Electrical and Computer Engineering at Ryerson University in Toronto, Ontario, Canada, and he holds the Canada Research Chair position in Biomedical Signal Analysis. Since July 2011, Sri has been an Associate Dean (Research and Development) for the Faculty of Engineering and Architectural Science. He is also the Founding Co-Director of the Institute for Biomedical Engineering, Science and Technology (iBEST). He is an Affiliate Scientist at the Keenan Research Centre at St. Michael’s Hospital in Toronto.

The Hunt for Power Remote Sensing

With the advent of the Internet of Things (IoT), the need for ultra-low power passive remote sensing is on the rise for battery-powered technologies. Always-on motion-sensing technologies are a great option to turn to. Digital cameras have come light years from where they were a decade ago, but low power they are not. When low-power technologies need always-on remote sensing, infrared motion sensors are a great option to turn to.

Passive infrared (PIR) sensors and passive infrared detectors (PIDs) are electronic devices that detect infrared light emitted from objects within their field of view. These devices typically don’t measure light per se; rather, they measure the delta of a system’s latent energy. This change generates a very small potential across a crystalline material (gallium nitride, cesium nitrate, among others), which can be amplified to create a usable signal.

Infrared technology was built on a foundation of older motion-sensing technologies that came before. Motion sensing was first utilized in the early 1940s, primarily for military purposes nearing the end of World War II. Radar and ultrasonic detectors were the progenitors of motion-sensing technologies seen today, relying on reflecting sound waves to determine the location of objects in a detection environment. Though effective for its purpose, its use was limited to military applications and was not a reasonable option for commercial users.

This essay appears in Circuit Cellar 314 (September 2016).

 
The viability of motion detection tools began to change as infrared-sensing options entered development. The birth of modern PIR sensors began towards the end of the sixties, when companies began to seek alternatives to the already available motion technologies that were fast becoming outdated.

The modern versions of these infrared motion sensors have taken root in many industries due to the affordability and flexibility of their use. The future of motion sensors is PID, and it has several advantages over its counterparts:

  • Saving Energy—PIDs are energy efficient. The electricity required to operate PIDs is minimal, with most units actually reducing the user’s energy consumption when compared to other commercial motion-sensing devices.
  • Inexpensive—Cost isn’t a barrier to entry for those wanting to deploy IR motion sensing technology. This sensor technology makes each individual unit affordable, allowing users to deploy multiple sensors for maximum coverage without breaking the bank.
  • Durability—It’s hard to match the ruggedness of PIDs. Most units don’t employ delicate circuitry that is easily jarred or disrupted; PIDs are routinely used outdoors and in adverse environments that would potentially damage other styles of detectors.
  • Simple and Small—The small size of PIDs work to their advantage. Innocuous sensors are ideal for security solutions that aren’t obtrusive or easily noticeable. This simplicity makes PIDs desirable for commercial security, when businesses want to avoid installing obvious security infrastructure throughout their buildings.
  • Wide Lens Range—The wide field of vision that PIDs have allow for comprehensive coverage of each location in which they are placed. PIDs easily form a “grid” of infrared detection that is ideal for detecting people, animals, or any other type of disruption that falls within the lens range.
  • Easy to Interface With—PIDs are flexible. The compact and simple nature of PIDs lets the easily integrate with other technologies, including public motion detectors for businesses and appliances like remote controls.

With the wealth of advantages PIDs have over other forms of motion-sensing technology, it stands to reason that PIR sensors and PIDs will have a place in the future of motion sensor development. Though other options are available, PIDs operate with simplicity, energy-efficiency, and a level of durability that other technologies can’t match. Though there are some exciting new developments in the field of motion-sensing technology, including peripherals for virtual reality and 3-D motion control, the reliability of infrared motion technology will have a definite role in the evolution of motion sensing technology in the years to come.

As the Head Hardware Engineer at Cyndr (www.cyndr.co), Kyle Engstrom is the company’s lead electron wrangler and firmware designer. He specializes in analog electronics and power systems. Kyle has bachelor’s degrees in electrical engineering and geology. His life as a rock hound lasted all of six months before he found his true calling in engineering. Kyle has worked three years in the aerospace industry designing cutting-edge avionics.

New Highly integrated Hall sensors

Infineon Technologies recently introduced a new family of Hall sensors targeted at cost-effective, compact designs. Available as latch and switch-type devices, the sensors in the TLx496x family have precise switching points, stable operation, and a low power consumption.Infineon TLx496x

The TLx496x Hall sensors consume no more than 1.6 mA. In addition, they have an integrated Hall element, a voltage regulator (to power the Hall element and the active circuits), choppers (ensure that the temperature remains stable), an oscillator, and an output driver.

 

The TLE496x-xM series is well suited for automotive applications (e.g., power windows and sunroofs, trunk locks, and windshield wipers) with an operating voltage of 3 to 5.5 V. The TLI496x-xM series units function like the TLE496x-xM units, but it is specified for a temperature range of –40° to 125°C and is JESD47 qualified. The TLI496x-xM is used in BLDC motors in e-bikes and fans in PCs and in electric drives in building automation. The TLV496x-xTA/B series was specifically developed for the cost-effective, contactless positioning. Typical applications are BLDC motors in home appliances (e.g., dishwashers), compressors in air-conditioners, and more. Despite the pressure to cut costs, these applications need very precise Hall latches or Hall switches (unipolar/bipolar) for temperatures ranging from –40 °C to 125 °C. The TLV496x-xTA/B versions have a power consumption of 1.6 mA and an ESD protection up to 4 kVH Human Body Model (HBM). The output has overcurrent protection and automatically switches off at high temperatures.

The Hall sensors of all three series are available in high volume. Development support includes online simulation tools and application manuals.

 

Source: Infineon Technologies

Super-Compact, Nine-Axis Motion Sensor

Bosch Sensortec recently announced the launch of the compact BMX160 nine-axis motion sensor, which a great option for small, power-constrained applications ranging from “smart” wearables to virtual reality (VR) devices. Housed in a compact 2.5 × 3 × 0.95 mm3 package, the sensor combines advanced accelerometer, gyroscope, and geomagnetic sensor technologies.Bosch-BMX160

The BMX160’s features, specs, and benefits:

  • Compact size: 2.5 × 3 × 0.95 mm3
  • Reduces power consumption below 1.5 mA
  • Enables Android wearable applications that rely on sensor data
  • You can use the sensor with the Bosch Sensortec BSX sensor data fusion software library.
  • Pin- and register-compatibility with the six-axis BMI160 IMU s
  • Built-in power management unit

BMX160 samples are now available for development partners.

Source: Bosch Sensortec

The Future of Sensor Technology for the IoT

Sensors are at the heart of many of the most innovative and game-changing Internet of Things (IoT) applications. We asked five engineers to share their thoughts on the future of sensor technology.


ChrisCantrellCommunication will be the fastest growth area in sensor technology. A good wireless link allows sensors to be placed in remote or dynamic environments where physical cables are impractical. Home Internet of Things (IoT) sensors will continue to leverage home Wi-Fi networks, but outdoor and physically-remote sensors will evolve to use cell networks. Cell networks are not just for voice anymore. Just ask your children. Phones are for texting—not for talking. The new 5G mobile service that rolls out in 2017 is designed with the Internet of Things in mind. Picocells and Microcells will better organize our sensors into manageable domains. What is the best cellular data plan for your refrigerator and toaster? I can’t wait for the TV commercials. — Christopher Cantrell (Software Engineer, CGI Federal)


TylerSensors of the future will conglomerate into microprocessor controlled blocks that are accessed over a network. For instance, weather sensors will display temperature, barometric pressure, humidity, wind speed, and direction along with latitude, longitude, altitude, and time thrown in for good measure, and all of this will be available across a single I2C link. Wide area network sensor information will be available across the Internet using encrypted links. Configuration and calibration can be done using webpages and all documentation will be stored online on the sensors themselves. Months’ worth of history will be saved to MicroSD drives or something similar. These are all things that we can dream of and implement today. Tomorrow’s sensors will solve tomorrow’s problems and we can really only make out the barest of glimpses of what tomorrow will hold. It will be entertaining to watch the future unfold and see how much we missed. — David C. Tyler (Retired Computer Scientist)



Quo vadis electronics? During the past few decades, electrical engineering has gone through an unprecedented growth. As a result, we see electronics to control just about everything around us. To be sure, what we call electronics today is in fact a symbiosis of hardware and software. At one time every electrical engineer worth his salt had to be able to solder and to write a program. A competent software engineer today may not understand what makes the hardware tick, just as a hardware engineer may not understand software, because it’s often too much for one person to master. In most situations, however, hardware depends on software and vice versa. While current technology enables us to do things we could not even dream about just a few years ago, when it comes to controlling or monitoring physical quantities, we remain limited by what the data sensors can provide. To mimic human intellect and more, we need sensors to convert reality into electrical signal. For that research scientists in the fields of physics, chemistry, biology, mathematics, and so forth work hard to discover novel, advanced sensors. Once a new sensor principle has been found, hardware and software engineers will go to work to exploit its detection capabilities in practical use. In my mind, research into new sensors is presently the most important activity for sustaining progress in the field of electronic control. — George Novacek (Engineer, Columnist, Circuit Cellar)


GustafikIt’s hard to imagine the future of sensors going against the general trend of lower power, greater distribution, smaller physical size, and improvements in all of the relevant parameters. With the proliferation of small connected devices beyond industrial and specialized use into homes and to average users (IoT), great advances and price drops are to be expected. Tech similar to that, once reserved for top-end industrial sensor networks, will be readily available. As electrical engineers, we will just have to adjust as always. After years of trying to avoid the realm of RF magic, I now find myself reading up on the best way to integrate a 2.4-GHz antenna onto my PCB. Fortunately, there is an abundance of tools, application notes, and tutorials from both the manufacturers and the community to help us with this next step. And with the amazing advances in computational power, neural networks, and various other data processing, I am eager to see what kind of additional information and predictions we can squeeze out of all those measurements. All in all, I am looking forward to a better, more connected future. And, as always, it’s a great time to be an electrical engineer. — David Gustafik (Hardware Developer, MicroStep-MIS)


MittalMiniature IoT, sensor, and embedded technologies are the future. Today, IoT technology is a favorite focus among many electronics startups and even big corporations. In my opinion, sensor-based medical applications are going to be very important in our day-to-day lives in the not-so-distant future. BioMEMS sensors integrated on a chip have already made an impact in industry with devices like glucometers and alcohol detectors. These types of BioMEMS sensors, if integrated inside mobile phones for many medical applications, can address many human needs. Another interesting area is wireless charging. Imagine if you could charge all your devices wirelessly as soon as you walk into your home. Wouldn’t that be a great innovation that would make your life easier? So, technology has a very good future provided it can bring out solutions which can really solve human needs. — Nishant Mittal (Master’s Student, IIT Bombay, Mumbai)

Low-Power 12 DOF Bluetooth Smart Sensor Development Platform

Dialog Semiconductor now offers a small, low-power 12 Degrees-of-Freedom (DOF) wireless smart sensor development kit for Internet of Things (IoT) applications, such as wearables, virtual reality, 3-D indoor mapping, and navigation. The DA14583 SmartBond Bluetooth Smart SoC is combined with Bosch Sensortec’s gyroscope, accelerometer, magnetometer, and environmental sensors. A 16 mm × 15 mm PCB is supplied as a dongle in a plastic housing. Current consumption is only 1.3 mA (typical) when streaming sensor data; it’s less than 110 µA in advertising mode and under 11 µA in power-save mode.Dialog DS025

The complementary software development kit (SDK) includes Dialog’s SmartFusion smart sensor library for data acquisition, auto-calibration, and sensor data fusion. It runs on the DA14583’s embedded Cortex M0 processor. The DA14583 has an ARM Cortex-M0 baseband processor with an integrated ultra-low power Bluetooth Smart radio. The development kit includes the following Bosch sensors: a BMI160 six-axis inertial measurement unit, a BMM150 three-axis geomagnetic field sensor, and a BME280 integrated environmental unit, which measures pressure, temperature, and humidity.

Source: Dialog Semiconductor

Heart Rate Monitoring Sensor Solution

Silicon Labs recently announced an optical heart rate-sensing solution for wrist-based heart rate monitoring (HRM) applications. The new Si1144 HRM solution includes a low-power optical sensor module paired with an EFM32 Gecko microcontroller running Silicon Labs’s advanced HRM algorithm. The compact Si1144 sensor module integrates an optical sensor, green LED, an ADC, LED drivers, control logic, and an I2C digital interface, making it a good option for power-sensitive wearables.Silicon Labs Si1144

 

 

The Si1144-AAGX HRM module’s features:

  • Accurately senses weak blood flow signals on the wrist
  • Choice of two algorithms to support static HRM and optional dynamic motion-compensated HRM using data from an external accelerometer
  • HRM solution pairs optical module with a Pearl Gecko microcontroller
  • Fully integrated HRM IC with green LED lens, high-sensitivity photodiode, low-noise ADC, LED drivers, optical blocking, and host communications/interrupts
  • Two LED drivers
  • Ultra-low-power consumption for long battery life (less than 500 nA standby current with 1.71-to-3.6-V supply voltage)
  • I2C serial communications, up to 3.4-Mbps data rate
  • 10-lead 4.9 × 2.85 × 1.2 mm LGA module package

Samples and production quantities of the Si1144-AAGX HRM module currently available. The Si1144 module along with Silicon Labs’s HRM algorithm costs $2.82 in 10,000-unit quantities. The HRM44-GGG-PS development board costs $57.60.

Source: Silicon Labs

Robots with a Vision

Machine chine vision is a field of electrical engineering that’s changing how we interact with our environment, as well as the ways by which machines communicate with each other. Circuit Cellar has been publishing articles on the subject since the mid-1990s. The technology has come a long way since then. But it’s important (and exciting) to regularly review past projects to learn from the engineers who paved the way for today’s ground-breaking innovations.

In Circuit Cellar 92, a team of engineers (Bill Bailey, Jon Reese, Randy Sargent, Carl Witty, and Anne Wright) from Newton Labs, a pioneer in robot engineering, introduced readers to the M1 color-sensitive robot. The robot’s main functions were to locate and carry tennis balls. But as you can imagine, the underlying technology was also used to do much more.

The engineering team writes:

Machine vision has been a challenge for AI researchers for decades. Many tasks that are simple for humans can only be accomplished by computers in carefully controlled laboratory environments, if at all. Still, robotics is benefiting today from some simple vision strategies that are achievable with commercially available systems.

In this article, we fill you in on some of the technical details of the Cognachrome vision system and show its application to a challenging and exciting task—the 1996 International AAAI Mobile Robot Competition in Portland, Oregon… In 1996, the contest was for an autonomous robot to collect 10 tennis balls and 2 quickly and randomly moving, self-powered squiggle balls and deliver them to a holding pen within 15 min.

In M1’s IR sensor array, each LED is fired in turn and detected reflections are latched by the 74HC259 into an eight-bit byte.

In M1’s IR sensor array, each LED is fired in turn and detected reflections are latched by the 74HC259 into an eight-bit byte.

At the time of the conference, we had already been manufacturing the Cognachrome for a while and saw this contest as an excellent way to put our ideas (and our board) to the test. We outfitted a general-purpose robot called M1 with a Cognachrome and a gripper and wrote software for it to catch and carry tennis balls… M1 follows the wall using an infrared obstacle detector. The code drives two banks of four infrared LEDs one at a time, each modulated at 40 kHz.

The left half of M1’s infrared sensor array is composed of a Sharp GP1U52X infrared detector sandwiched between four infrared LEDs

The left half of M1’s infrared sensor array is composed of a Sharp GP1U52X infrared detector sandwiched between four infrared LEDs

Two standard Sharp GP1U52X infrared remote-control reception modules detect reflections. The 74HC163/74HC238 combination fires each LED in turn, and the ’HC259 latches detected reflections. This system provides reliable obstacle detection in the 8–12″ range.

The figure above shows the schematic. The photo shows the IR sensors.

The system provides only yes/no information about obstacles in the eight directions around the front half of the robot. However, M1 can crudely estimate distance to large obstacles (e.g., walls) via patterns in the reflections. The more adjacent directions with detected reflections, the closer the obstacle probably is.

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SimpleLink Simplifies IoT Prototyping

Texas Instruments recently introduced the next-generation SimpleLink SensorTag development kit, which enables the fast integration of sensor data with wireless cloud connectivity.TI Simplelink

Features of the new SensorTags include:

  • Flexible development with wireless connectivity options including Bluetooth low energy, 6LoWPAN and ZigBee based on the SimpleLink ultra-low power CC2650 wireless microcontroller
  • 10 integrated low-power sensors
  • New DevPack plug-in modules that extend the kits’ functionality and programmability
  • Out of the box capabilities with a free iOS or Android app
  • Connect to the cloud in minutes via TI’s IoT cloud ecosystem including IBM’s Bluemix IoT Foundation
  • Available TI Design reference designs, including 3-D print files of the SensorTag enclosures, that enable you to reuse the SensorTags for new designs

The SensorTag kits come with ready-to-use protocol stacks, a free Code Composer Studio IDE license, online training, and 24/7 online TI E2E community support. In addition, TI’s cloud-based software development tools provide instant access to examples, documentation, software and even an integrated development environment (IDE) all from the convenience of the web.

Expanding the standards supported by the SensorTag, there will be two different development kit versions:

  • The multi-standard SensorTag, based on the SimpleLink ultra-low power CC2650 wireless MCU, supports development for Bluetooth Smart, 6LoWPAN and ZigBee. This SensorTag has a unique feature that enables developers to change between different 2.4-GHz technologies by simply loading new software images directly from the SensorTag app over-the-air. When the SensorTag is used as a ZigBee and 6LoWPAN device, it connects to the cloud via a BeagleBone Black gateway. For Bluetooth Smart development, it connects via a smartphone.
  • The Wi-Fi SensorTag will allow users to demo the SimpleLink CC3200 wireless MCU. Further details and availability information will be coming soon. Start developing today with the CC3200 solution with these development tools.
  • Both SensorTags come with 10 integrated low-power sensors including the TI OPT3001 precision ambient light sensor, TI HDC1000 integrated humidity and temperature sensor and TI TMP007 contactless IR thermopile sensor. Additional sensors include a nine-axis motion sensor (gyroscope, compass and accelerometer), altimeter/ pressure sensor, digital microphone, and magnet sensor.

New to the next-generation CC2650 SensorTag is the ability for developers to customize their kit to fit their design with new DevPack plug-in modules. DevPacks available today include:

  • The $15 Debug DevPack is based on the TM4C1294 microcontroller (MCU) to add debug capabilities to the SensorTag. Plug it into the DevPack expansion header and debug the SensorTag with Code Composer Studio IDE, TI Cloud Tools, or IAR embedded workbench for ARM.
  • The Display (watch) DevPack adds a 1.35 inch ultra-low power graphical display to the SensorTag. The Watch DevPack is designed for development of smartwatches, refrigerator displays and any other application that has a need for a remote display.
  • The LED Audio DevPack consists of four high power multi-color LEDs and a 4W audio amplifier powered by a micro-USB for home automation and smart lighting applications.
  • Create your own! If developers cannot find a specific DevPack to fit their needs, they can create their own by downloading the Build Your Own DevPack guide.

The new SimpleLink multi-standard CC2650 SensorTag (CC2650STK) is available now for $29 in the TI Store and authorized distributors. Related software for each connectivity standard is also available:

  • Bluetooth Smart software
  • 6LoWPAN software
  • ZigBee software

The SimpleLink SensorTag DevPacks are also available on the TI Store and through TI authorized distributors. The Debug DevPack (CC-DEVPACK-DEBUG) costs $15. The Display DevPack (DEVPACK-WATCH) costs $19. The LED Audio DevPack (DEVPACK-LED-AUDIO) is $19. Pricing and availability for the SimpleLink Wi-Fi CC3200 SensorTag will be coming later in 2015.

New Motion Module for Easy Motion Monitoring

Microchip Technology announced at the Embedded World conference in Germany the MM7150 Motion Module, which combines Microchip’s SSC7150 motion co-processor combined with nine-axis sensors. Included in compact form factor are an accelerometer, magnetometer, and gyroscope.  With a simple I2C connection to most MCUs/MPUs, embedded applications and Internet of Things (IoT) systems can easily tap into the module’s advanced motion and position data.Microchip MM7150

The SSC7150 motion co-processor is preprogrammed with sensor fusion algorithms that intelligently filter, compensate, and combine the raw sensor data to provide highly accurate position and orientation information.  The small module self-calibrates during operation utilizing data from the prepopulated sensors—Bosch BMC150 (six-axis digital compass) and the BMG160 (three-axis gyroscope).

The single-sided MM7150 motion module is easily soldered down during the manufacturing process. You can develop motion applications for a variety of products with Microchip’s MM7150 PICtail Plus Daughter Board.  The MM7150 Motion Module is well suited for a wide range of applications: embedded (e.g., portable devices and robotics), industrial (e.g., commercial trucks, industrial automation, and patient tracking), and consumer electronics (e.g., IoT, remote controls, and wearable devices).

The MM7150 is supported by the MM7150 PICtail Plus Daughter Board (AC243007, $50) that plugs directly  into Microchip’s Explorer 16 Development Board (DM240001, $129) to enable quick and easy prototyping utilizing Microchip’s extensive installed base of PIC microcontrollers.

The 17 mm × 17 mm MM7150 is priced at $26.76 each in 1,000-unit quantities.

Source: Microchip Technology www.microchip.com

 

 

 

 

Flexible I/O Expansion for Rugged Applications

WynSystemsThe SBC35-CC405 series of multi-core embedded PCs includes on-board USB, gigabit Ethernet, and serial ports. These industrial computers are designed for rugged embedded applications requiring extended temperature operation and long-term availability.

The SBC35-CC405 series features the latest generation Intel Atom E3800 family of processors in an industry-standard 3.5” single-board computer (SBC) format COM Express carrier. A Type 6 COM Express module supporting a quad-, dual-, or single-core processor is used to integrate the computer. For networking and communications, the SBC35-CC405 includes two Intel I210 gigabit Ethernet controllers with IEEE 1588 timestamping and 10-/100-/1,000-Mbps multispeed operation. Four Type-A connectors support three USB 2.0 channels and one high-speed USB 3.0 channel. Two serial ports support RS-232/-422/-485 interface levels with clock options up to 20 Mbps in the RS-422/-485 mode and up to 1 Mbps in the RS-232 mode.

The SBC35-CC405 series also includes two MiniPCIe connectors and one IO60 connector to enable additional I/O expansion. Both MiniPCIe connectors support half-length and full-length cards with screw-down mounting for improved shock and vibration durability. One MiniPCIe connector also supports bootable mSATA solid-state disks while the other connector includes USB. The IO60 connector provides access to the I2C, SPI, PWM, and UART signals enabling a simple interface to sensors, data acquisition, and other low-speed I/O devices.

The SBC35-CC405 runs over a 10-to-50-VDC input power range and operates at temperatures from –40°C to 85°C. Enclosures, power supplies, and configuration services are also available.

Linux, Windows, and other x86 OSes can be booted from the CFast, mSATA, SATA, or USB interfaces, providing flexible data storage options. WinSystems provides drivers for Linux and Windows 7/8 as well as preconfigured embedded OSes.
The single-core SBC35-CC405 costs $499.

Winsystems, Inc.
www.winsystems.com