Arduino MOSFET-Based Power Switch

Circuit Cellar columnist Ed Nisley has used Arduino SBCs in many projects over the years. He has found them perfect for one-off designs and prototypes, since the board’s all-in-one layout includes a micrcontroller with USB connectivity, simple connectors, and a power regulator.

But the standard Arduino presents some design limitations.

“The on-board regulator can be either a blessing or a curse, depending on the application. Although the board will run from an unregulated supply and you can power additional circuitry from the regulator, the minute PCB heatsink drastically limits the available current,” Nisley says. “Worse, putting the microcontroller into one of its sleep modes doesn’t shut off the rest of the Arduino PCB or your added circuits, so a standard Arduino board isn’t suitable for battery-powered applications.”

In Circuit Cellar’s January issue, Nisley presents a MOSFET-based power switch that addresses such concerns. He also refers to one of his own projects where it would be helpful.

“The low-resistance Hall effect current sensor that I described in my November 2013 column should be useful in a bright bicycle taillight, but only if there’s a way to turn everything off after the ride without flipping a mechanical switch…,” Nisley says. “Of course, I could build a custom microcontroller circuit, but it’s much easier to drop an Arduino Pro Mini board atop the more interesting analog circuitry.”

Nisley’s January article describes “a simple MOSFET-based power switch that turns on with a push button and turns off under program control: the Arduino can shut itself off and reduce the battery drain to nearly zero.”

Readers should find the article’s information and circuitry design helpful in other applications requiring automatic shutoff, “even if they’re not running from battery power,” Nisley says.

Figure 1: This SPICE simulation models a power p-MOSFET with a logic-level gate controlling the current from the battery to C1 and R2, which simulate a 500-mA load that is far below Q2’s rating. S1, a voltage-controlled switch, mimics an ordinary push button. Q1 isolates the Arduino digital output pin from the raw battery voltage.

Figure 1: This SPICE simulation models a power p-MOSFET with a logic-level gate controlling the current from the battery to C1 and R2, which simulate a 500-mA load that is far below Q2’s rating. S1, a voltage-controlled switch, mimics an ordinary push button. Q1 isolates the Arduino digital output pin from the raw battery voltage.

The article takes readers from SPICE modeling of the circuitry (see Figure 1) through developing a schematic and building a hardware prototype.

“The PCB in Photo 1 combines the p-MOSFET power switch from Figure 2 with a Hall effect current sensor, a pair of PWM-controlled n-MOFSETs, and an Arduino Pro Mini into

The power switch components occupy the upper left corner of the PCB, with the Hall effect current sensor near the middle and the Arduino Pro Mini board to the upper right. The 3-D printed red frame stiffens the circuit board during construction.

Photo 1: The power switch components occupy the upper left corner of the PCB, with the Hall effect current sensor near the middle and the Arduino Pro Mini board to the upper right. The 3-D printed red frame stiffens the circuit board during construction.

a brassboard layout,” Nisley says. “It’s one step beyond the breadboard hairball I showed in my article “Low-Loss Hall Effect Current Sensing” (Circuit Cellar 280, 2013), and will help verify that all the components operate properly on a real circuit board with a good layout.”

For much more detail about the verification process, PCB design, Arduino interface, and more, download the January issue.

The actual circuit schematic includes the same parts as the SPICE schematic, plus the assortment of connectors and jumpers required to actually build the PCB shown in Photo 1.

Figure 2: The actual circuit schematic includes the same parts as the SPICE schematic, as well as the assortment of connectors and jumpers required to actually build the PCB shown in Photo 1.

Client Profile: Digi International, Inc

Contact: Elizabeth Presson

Featured Product: The XBee product family ( is a series of modular products that make adding wireless technology easy and cost-effective. Whether you need a ZigBee module or a fast multipoint solution, 2.4 GHz or long-range 900 MHz—there’s an XBee to meet your specific requirements.

XBee Cloud Kit

Digi International XBee Cloud Kit

Product information: Digi now offers the XBee Wi-Fi Cloud Kit ( for those who want to try the XBee Wi-Fi (XB2B-WFUT-001) with seamless cloud connectivity. The Cloud Kit brings the Internet of Things (IoT) to the popular XBee platform. Built around Digi’s new XBee Wi-Fi
module, which fully integrates into the Device Cloud by Etherios, the kit is a simple way for anyone with an interest in M2M and the IoT to build a hardware prototype and integrate it into an Internet-based application. This kit is suitable for electronics engineers, software designers, educators, and innovators.

Exclusive Offer: The XBee Wi-Fi Cloud Kit includes an XBee Wi-Fi module; a development board with a variety of sensors and actuators; loose electronic prototyping parts to make circuits of your own; a free subscription to Device Cloud; fully customizable widgets to monitor and control connected devices; an open-source application that enables two-way communication and control with the development board over the Internet; and cables, accessories, and everything needed to connect to the web. The Cloud Kit costs $149.

A Look at Low-Noise Amplifiers

Maurizio Di Paolo Emilio, who has a PhD in Physics, is an Italian telecommunications engineer who works mainly as a software developer with a focus on data acquisition systems. Emilio has authored articles about electronic designs, data acquisition systems, power supplies, and photovoltaic systems. In this article, he provides an overview of what is generally available in low-noise amplifiers (LNAs) and some of the applications.

By Maurizio Di Paolo Emilio
An LNA, or preamplifier, is an electronic amplifier used to amplify sometimes very weak signals. To minimize signal power loss, it is usually located close to the signal source (antenna or sensor). An LNA is ideal for many applications including low-temperature measurements, optical detection, and audio engineering. This article presents LNA systems and ICs.

Signal amplifiers are electronic devices that can amplify a relatively small signal from a sensor (e.g., temperature sensors and magnetic-field sensors). The parameters that describe an amplifier’s quality are:

  • Gain: The ratio between output and input power or amplitude, usually measured in decibels
  • Bandwidth: The range of frequencies in which the amplifier works correctly
  • Noise: The noise level introduced in the amplification process
  • Slew rate: The maximum rate of voltage change per unit of time
  • Overshoot: The tendency of the output to swing beyond its final value before settling down

Feedback amplifiers combine the output and input so a negative feedback opposes the original signal (see Figure 1). Feedback in amplifiers provides better performance. In particular, it increases amplification stability, reduces distortion, and increases the amplifier’s bandwidth.

 Figure 1: A feedback amplifier model is shown here.

Figure 1: A feedback amplifier model is shown.

A preamplifier amplifies an analog signal, generally in the stage that precedes a higher-power amplifier.

Op-amps are widely used as AC amplifiers. Linear Technology’s LT1028 or LT1128 and Analog Devices’s ADA4898 or AD8597 are especially suitable ultra-low-noise amplifiers. The LT1128 is an ultra-low-noise, high-speed op-amp. Its main characteristics are:

  • Noise voltage: 0.85 nV/√Hz at 1 kHz
  • Bandwidth: 13 MHz
  • Slew rate: 5 V/µs
  • Offset voltage: 40 µV

Both the Linear Technology and Analog Devices amplifiers have voltage noise density at 1 kHz at around 1 nV/√Hz  and also offer excellent DC precision. Texas Instruments (TI)  offers some very low-noise amplifiers. They include the OPA211, which has 1.1 nV/√Hz  noise density at a  3.6 mA from 5 V supply current and the LME49990, which has very low distortion. Maxim Integrated offers the MAX9632 with noise below 1nV/√Hz.

The op-amp can be realized with a bipolar junction transistor (BJT), as in the case of the LT1128, or a MOSFET, which works at higher frequencies and with a higher input impedance and a lower energy consumption. The differential structure is used in applications where it is necessary to eliminate the undesired common components to the two inputs. Because of this, low-frequency and DC common-mode signals (e.g., thermal drift) are eliminated at the output. A differential gain can be defined as (Ad = A2 – A1) and a common-mode gain can be defined as (Ac = A1 + A2 = 2).

An important parameter is the common-mode rejection ratio (CMRR), which is the ratio of common-mode gain to the differential-mode gain. This parameter is used to measure the  differential amplifier’s performance.

Figure 2: The design of a simple preamplifier is shown. Its main components are the Linear Technology LT112 and the Interfet IF3602 junction field-effect transistor (JFET).

Figure 2: The design of a simple preamplifier is shown. Its main components are the Linear Technology LT1128 and the Interfet IF3602 junction field-effect transistor (JFET).

Figure 2 shows a simple preamplifier’s design with 0.8 nV/√Hz at 1 kHz background noise. Its main components are the LT1128 and the Interfet IF3602 junction field-effect transistor (JFET).  The IF3602 is a dual Nchannel JFET used as stage for the op-amp’s input. Figure 3 shows the gain and Figure 4 shows the noise response.

Figure 3: The gain of a low-noise preamplifier.

Figure 3: The is a low-noise preamplifier’s gain.


Figure 4: The noise response of a low-noise preamplifier

Figure 4: A low-noise preamplifier’s noise response is shown.

The Stanford Research Systems SR560 low-noise voltage preamplifier has a differential front end with 4nV/√Hz input noise and a 100-MΩ input impedance (see Photo 1a). Input offset nulling is accomplished by a front-panel potentiometer, which is accessible with a small screwdriver. In addition to the signal inputs, a rear-panel TTL blanking input enables you to quickly turn the instrument’s gain on and off (see Photo 1b).

Photo 1a:The Stanford Research Systems SR560 low-noise voltage preamplifier

Photo 1a: The Stanford Research Systems SR560 low-noise voltage preamplifier. (Photo courtesy of Stanford Research Systems)

Photo 1 b: A rear-panel TTL blanking input enables you to quickly turn the Stanford Research Systems SR560 gain on and off.

Photo 1b: A rear-panel TTL blanking input enables you to quickly turn the Stanford Research Systems SR560 gain on and off. (Photo courtesy of Stanford Research Systems)

The Picotest J2180A low-noise preamplifier provides a fixed 20-dB gain while converting a 1-MΩ input impedance to a 50-Ω output impedance and 0.1-Hz to 100-MHz bandwidth (see Photo 2). The preamplifier is used to improve the sensitivity of oscilloscopes, network analyzers, and spectrum analyzers while reducing the effective noise floor and spurious response.

Photo 2: The Picotest J2180A low-noise preamplifier is shown.

Photo 2: The Picotest J2180A low-noise preamplifier is shown. (Photo courtesy of

Signal Recovery’s Model 5113 is among the best low-noise preamplifier systems. Its principal characteristics are:

  • Single-ended or differential input modes
  • DC to 1-MHz frequency response
  • Optional low-pass, band-pass, or high-pass signal channel filtering
  • Sleep mode to eliminate digital noise
  • Optically isolated RS-232 control interface
  • Battery or line power

The 5113 (see Photo 3 and Figure 5) is used in applications as diverse as radio astronomy, audiometry, test and measurement, process control, and general-purpose signal amplification. It’s also ideally suited to work with a range of lock-in amplifiers.

Photo 3: This is the Signal Recovery Model 5113 low-noise pre-amplifier.

Photo 3: This is the Signal Recovery Model 5113 low-noise preamplifier. (Photo courtesy of Signal Recovery)

Figure 5: Noise contour figures are shown for the Signal Recovery Model 5113.

Figure 5: Noise contour figures are shown for the Signal Recovery Model 5113.

This article briefly introduced low-noise amplifiers, in particular IC system designs utilized in simple or more complex systems such as the Signal Recovery Model 5113, which is a classic amplifier able to obtain different frequency bands with relative gain. A similar device is the SR560, which is a high-performance, low-noise preamplifier that is ideal for a wide variety of applications including low-temperature measurements, optical detection, and audio engineering.

Moreover, the Krohn-Hite custom Models 7000 and 7008 low-noise differential preamplifiers provide a high gain amplification to 1 MHz with an AC output derived from a very-low-noise FET instrumentation amplifier.

One common LNA amplifier is a satellite communications system. The ground station receiving antenna will connect to an LNA, which is needed because the received signal is weak. The received signal is usually a little above background noise. Satellites have limited power, so they use low-power transmitters.

Telecommunications engineer Maurizio Di Paolo Emilio was born in Pescara, Italy. Working mainly as a software developer with a focus on data acquisition systems, he helped design the thermal compensation system (TCS) for the optical system used in the Virgo Experiment (an experiment for detecting gravitational waves). Maurizio currently collaborates with researchers at the University of L’Aquila on X-ray technology. He also develops data acquisition hardware and software for industrial applications and manages technical training courses. To learn more about Maurizio and his expertise, read his essay on “The Future of Data Acquisition Technology.”

Client Profile: Pololu Robotics

Pololu Robotics
920 Pilot Road
Las Vegas, NV 89119


Pololu Robotics Zumo

Pololu Robotics Zumo

Embedded Products/Services: Pololu designs, manufactures, and distributes a variety of robotic and electronic parts. Get the building blocks for your next project at Pololu, where you can find wheels, motors, motion controllers, basic prototyping supplies, sensors, complete robot kits, and more. Pololu also offers a custom laser cutting service starting at $25.

Product information: The Pololu Zumo robot is an Arduino-controllable tracked robot platform that measures less than 10 cm × 10 cm, which is small enough to qualify for Mini Sumo. The Zumo includes two micro-metal gearmotors coupled to a pair of silicone tracks, a stainless steel bulldozer-style blade, six infrared reflectance sensors for line following or edge detection, a three-axis accelerometer and magnetometer, and a buzzer for simple sounds and music. A kit version is also available.

Exclusive offer: Use coupon code ZUMOCC20 for 20% off any one item in Pololu’s Zumo category (

Natural Human-Computer Interaction

Recent innovations in both hardware and software have brought on a new wave of interaction techniques that depart from mice and keyboards. The widespread adoption of smartphones and tablets with capacitive touchscreens shows people’s preference to directly manipulate virtual objects with their hands.

Going beyond touch-only interaction, the Microsoft Kinect sensor enables users to play

This shows the hand tracking result from Kinect data. The red regions are our tracking results and the green lines are the skeleton tracking results from the Kinect SDK (based on data from the ChAirGest corpus:

This shows the hand tracking result from Kinect data. The red regions are our tracking results and the green lines are the skeleton tracking results from the Kinect SDK (based on data from the ChAirGest corpus:

games with their entire body. More recently, Leap Motion’s new compact sensor, consisting of two cameras and three infrared LEDs, has opened up the possibility of accurate fingertip tracking. With Project Glass, Google is pioneering new technology in the wearable human-computer interface. Other new additions to wearable technology include Samsung’s Galaxy Gear Smartwatch and Apple’s rumored iWatch.

A natural interface reduces the learning curve, or the amount of time and energy a person requires to complete a particular task. Instead of a user learning to communicate with a machine through a programming language, the machine is now learning to understand the user.

Hardware advancements have led to our clunky computer boxes becoming miniaturized, stylish sci-fi-like phones and watches. Along with these shrinking computers come ever-smaller sensors that enable a once keyboard-constrained computer to listen, see, and feel. These developments pave the way to natural human-computer interfaces.
If sensors are like eyes and ears, software would be analogous to our brains.

Understanding human speech and gestures in real time is a challenging task for natural human-computer interaction. At a higher level, both speech and gesture recognition require similar processing pipelines that include data streaming from sensors, feature extraction, and pattern recognition of a time series of feature vectors. One of the main differences between the two is feature representation because speech involves audio data while gestures involve video data.

For gesture recognition, the first main step is locating the user’s hand. Popular libraries for doing this include Microsoft’s Kinect SDK or PrimeSense’s NITE library. However, these libraries only give the coordinates of the hands as points, so the actual hand shapes cannot be evaluated.

Fingertip tracking using a Kinect sensor. The green dots are the tracked fingertips.

Our team at the Massachusetts Institute of Technology (MIT) Computer Science and Artificial Intelligence Laboratory has developed methods that use a combination of skin-color and motion detection to compute a probability map of gesture salience location. The gesture salience computation takes into consideration the amount of movement and the closeness of movement to the observer (i.e., the sensor).

We can use the probability map to find the most likely area of the gesturing hands. For each time frame, after extracting the depth data for the entire hand, we compute a histogram of oriented gradients to represent the hand shape as a more compact feature descriptor. The final feature vector for a time frame includes 3-D position, velocity, and hand acceleration as well as the hand shape descriptor. We also apply principal component analysis to reduce the feature vector’s final dimension.

A 3-D model of pointing gestures using a Kinect sensor. The top left video shows background subtraction, arm segmentation, and fingertip tracking. The top right video shows the raw depth-mapped data. The bottom left video shows the 3D model with the white plane as the tabletop, the green line as the arm, and the small red dot as the fingertip.

The next step in the gesture-recognition pipeline is to classify the feature vector sequence into different gestures. Many machine-learning methods have been used to solve this problem. A popular one is called the hidden Markov model (HMM), which is commonly used to model sequence data. It was earlier used in speech recognition with great success.

There are two steps in gesture classification. First, we need to obtain training data to learn the models for different gestures. Then, during recognition, we find the most likely model that can produce the given observed feature vectors. New developments in the area involve some variations in the HMM, such as using hierarchical HMM for real-time inference or using discriminative training to increase the recognition accuracy.

Ying Yin

Ying Yin is a PhD candidate and a Research Assistant at the Massachusetts Institute of Technology (MIT) Computer Science and Artificial Intelligence Laboratory. Originally from Suzhou, China, Ying received her BASc in Computer Engineering from the University of British Columbia in Vancouver, Canada, in 2008 and an MS in Computer Science from MIT in 2010. Her research focuses on applying machine learning and computer vision methods to multimodal human-computer interaction. Ying is also interested in web and mobile application development. She has won awards in web and mobile programming competitions at MIT.

Currently, the newest development in speech recognition at the industry scale is a method called deep learning. Earlier machine-learning methods require careful selection of feature vectors. The goal of deep learning is automatic discovery of powerful features from raw input data. So far, it has shown promising results in speech recognition. It can possibly be applied to gesture recognition to see whether it can further improve accuracy.

As component form factors shrink, sensor resolutions grow, and recognition algorithms become more accurate, natural human-computer interaction will become more and more ubiquitous in our everyday life.

Web-Based Remote I/O Control

The RIO-2010 is a web-based remote I/O control module. The Ethernet-ready module is equipped with eight relays, 16 photo-isolated digital inputs, and a 1-Wire interface for digital temperature sensor connection. The RIO-2010’s built-in web server enables you to access the I/O and use a standard web browser to remotely control the RIO-2010’s relay.

The RIO-2010 can be easily integrated into supervisory control and data acquisition (SCADA) and industrial automation systems using the standard Modbus TCP protocol. The I/O module also comes with RS-485 serial interface for applications requiring Modbus RTU/ASCII. Its built-in web server enables you to use standard web-editing tools and Ajax dynamic page technology to customize your webpage.

Contact Artila for pricing.

Artila Electronics Co., Ltd.

DC Motor for Fine Rotary Motions

The RE 30 EB precious metal brushed motor features a low start-up voltage, even after a long period in standstill. With a 53-mNm rated torque, the powerful motor provides twice the power of an Maxon RE 25 EB. In addition, the RE 30 EB features minimal high-frequency interference.

The RE 30 EB motor is specifically designed for haptic applications (e.g., surgical robots). Therefore, the motor can also be used as a highly sensitive sensor, acting as the sense of touch to register mechanical resistance.

Contact Maxon for pricing.

Maxon Precision Motors

Dual-Display Digital Multimeter

The DM3058E digital multimeter (DMM) is designed with 5.5-digit resolution and dual display. The DMM can enable system integration and is suitable for high-precision, multifunction, and automatic measurement applications.

The DM3058E is capable of measuring up to 123 readings per second. It can quickly save or recall up to 10 preset configurations, including built-in cold terminal compensation for thermocouples.

The DMM provides a convenient and flexible platform with an easy-to-use design and a built-in help system for information acquisition. In addition, it supports 10 different measurement types including DC voltage (200 mV to approximately 1,000 V), AC voltage (200 mV to approximately 750 V), DC current (200 µA to approximately
10 A), AC current (20 mA to approximately 10 A), frequency measurement (20 Hz to approximately 1 MHz), 2-Wire and 4-Wire resistance (200 O to approximately 100 MO), and diode, continuity, and capacitance.

The DM3058 is ideal for research and development labs and educational applications, as well as low-end detection, maintenance, and quality tests where automation combined with capability and value are needed.

The DM3058E digital multimeter costs $449.

Rigol Technologies, Inc.

Two-Channel CW Laser Diode Driver with an MCU Interface

The iC-HT laser diode driver enables microcontroller-based activation of laser diodes in Continuous Wave mode. With this device, laser diodes can be driven by the optical output power (using APC), the laser diode current (using ACC), or a full controller-based power control unit.

The maximum laser diode current per channel is 750 mA. Both channels can be switched in parallel for high laser diode currents of up to 1.5 A. A current limit can also be configured for each channel.

Internal operating points and voltages can be output through ADCs. The integrated temperature sensor enables the system temperature to be monitored and can also be used to analyze control circuit feedback. Logarithmic DACs enable optimum power regulation across a large dynamic range. Therefore, a variety of laser diodes can be used.

The relevant configuration is stored in two equivalent memory areas. Internal current limits, a supply-voltage monitor, channel-specific interrupt-switching inputs, and a watchdog safeguard the laser diodes’ operation through iC-HT.

The device can be also operated by pin configuration in place of the SPI or I2C interface, where external resistors define the APC performance targets. An external supply voltage can be controlled through current output device configuration overlay (DCO) to reduce the system power dissipation (e.g., in battery-operated devices or systems).

The iC-HT operates on 2.8 to 8 V and can drive both blue and green laser diodes. The diode driver has a –40°C-to-125°C operating temperature range and is housed in a 5-mm × 5-mm, 28-pin QFN package.

The iC-HT costs $13.20 in 1,000-unit quantities.

iC-Haus GmbH

Accurate Measurement Power Analyzer

The PA4000 power analyzer provides accurate power measurements. It offers one to four input modules, built-in test modes, and standard PC interfaces.

The analyzer features innovative Spiral Shunt technology that enables you to lock onto complex signals. The Spiral Shunt design ensures stable, linear response over a range of input current levels, ambient temperatures, crest factors, and other variables. The spiral construction minimizes stray inductance (for optimum high-frequency performance) and provides high overload capability and improved thermal stability.

The PA4000’s additional features include 0.04% basic voltage and current accuracy, dual internal current shunts for optimal resolution, frequency detection algorithms for noisy waveform tracking, application-specific test modes to simplify setup. The analyzer  easily exports data to a USB flash drive or PC software. Harmonic analysis and communications ports are included as standard features.

Contact Tektronix for pricing.

Tektronix, Inc.

AAR Arduino Autonomous Mobile Robot

The AAR Arduino Robot is a small autonomous mobile robot designed for those new to robotics and for experienced Arduino designers. The robot is well suited for hobbyists and school projects. Designed in the Arduino open-source prototyping platform, the robot is easy to program and run.

The AAR, which is delivered fully assembled, comes with a comprehensive CD that includes all the software needed to write, compile, and upload programs to your robot. It also includes a firmware and hardware self test. For wireless control, the robot features optional Bluetooth technology and a 433-MHz RF.

The AAR robot’s features include an Atmel ATmega328P 8-bit AVR-RISC processor with a 16-MHz clock, Arduino open-source software, two independently controlled 3-VDC motors, an I2C bus, 14 digital I/Os on the processor, eight analog input lines, USB interface programming, an on-board odometer sensor on both wheels, a line tracker sensor, and an ISP connector for bootloader programming.

The AAR’s many example programs help you get your robot up and running. With many expansion kits available, your creativity is unlimited.

Contact Global Specialties for pricing.

Global Specialties

Embedded Sensor Innovation at MIT

During his June 5 keynote address at they 2013 Sensors Expo in Chicago, Joseph Paradiso presented details about some of the innovative embedded sensor-related projects at the MIT Media Lab, where he is the  Director of the Responsive Environments Group. The projects he described ranged from innovative ubiquitous computing installations for monitoring building utilities to a small sensor network that transmits real-time data from a peat bog in rural Massachusetts. Below I detail a few of the projects Paradiso covered in his speech.


Managed by the Responsive Enviroments group, the DoppelLab is a virtual environment that uses Unity 3D to present real-time data from numerous sensors in MIT Media Lab complex.

The MIT Responsive Environments Group’s DoppleLab

Paradiso explained that the system gathers real-time information and presents it via an interactive browser. Users can monitor room temperature, humidity data, RFID badge movement, and even someone’s Tweets has he moves throughout the complex.

Living Observatory

Paradiso demoed the Living Observatory project, which comprises numerous sensor nodes installed in a peat bog near Plymouth, MA. In addition to transmitting audio from the bog, the installation also logs data such as temperature, humidity, light, barometric pressure, and radio signal strength. The data logs are posted on the project site, where you can also listen to the audio transmission.

The Living Observatory (Source:


The GesturesEverywhere project provides a real-time data stream about human activity levels within the MIT Media Lab. It provides the following data and more:

  • Activity Level: you can see the Media Labs activity level over a seven-day period.
  • Presence Data: you can see the location of ID tags as people move in the building

The following video is a tracking demo posted on the project site.

The aforementioned projects are just a few of the many cutting-edge developments at the MIT Media Lab. Paradiso said the projects show how far ubiquitous computing technology has come. And they provide a glimpse into the future. For instance, these technologies lend themselves to a variety of building-, environment-, and comfort-related applications.

“In the early days of ubiquitous computing, it was all healthcare,” Paradiso said. “The next frontier is obviously energy.”

Embedded Wireless Made Simple

Last week at the 2013 Sensors Expo in Chicago, Anaren had interesting wireless embedded control systems on display. The message was straightforward: add an Anaren Integrated Radio (AIR) module to an embedded system and you’re ready to go wireless.

Bob Frankel demos embedded mobile control

Bob Frankel of Emmoco provided a embedded mobile control demonstration. By adding an AIR module to a light control system, he was able to use a tablet as a user interface.

The Anaren 2530 module in a light control system (Source: Anaren)

In a separate demonstration, Anaren electrical engineer Mihir Dani showed me how to achieve effective light control with an Anaren 2530 module and TI technology. The module is embedded within the light and compact remote enables him to manipulate variables such as light color and saturation.

Visit Anaren’s website for more information.

Infrared Communications for Atmel Microcontrollers

Are you planning an IR communications project? Do you need to choose a microcontroller? Check out the information Cornell University Senior Lecturer Bruce Land sent us about inexpensive IR communication with Atmel ATmega microcontrollers. It’s another example of the sort of indispensable information covered in Cornell’s excellent ECE4760 course.

Land informed us:

I designed a basic packet communication scheme using cheap remote control IR receivers and LED transmitters. The scheme supports 4800 baud transmission,
with transmitter ID and checksum. Throughput is about twenty 20-character packets/sec. The range is at least 3 meters with 99.9% packet receive and moderate (<30 mA) IR LED drive current.

On the ECE4760 project page, Land writes:

I improved Remin’s protocol by setting up the link software so that timing constraints on the IR receiver AGC were guaranteed to be met. It turns out that there are several types of IR reciever, some of which are better at short data bursts, while others are better for sustained data. I chose a Vishay TSOP34156 for its good sustained data characteristics, minimal burst timing requirements, and reasonable data rate. The system I build works solidly at 4800 baud over IR with 5 characters of overhead/packet (start token, transmitter number, 2 char checksum , end token). It works with increasing packet loss up to 9000 baud.

Here is the receiver circuit.

The receiver circuit (Source: B. Land, Cornell University ECE4760 Infrared Communications
for Atmel Mega644/1284 Microcontrollers)

Land explains:

The RC circuit acts a low-pass filter on the power to surpress spike noise and improve receiver performance. The RC circuit should be close to the receiver. The range with a 100 ohm resistor is at least 3 meters with the transmitter roughly pointing at the receiver, and a packet loss of less then 0.1 percent. To manage burst length limitations there is a short pause between characters, and only 7-bit characters are sent, with two stop bits. The 7-bit limit means that you can send all of the printing characters on the US keyboard, but no extended ASCII. All data is therefore sent as printable strings, NOT as raw hexidecimal.

Land’s writeup also includes a list of programs and packet format information.

CC269: Break Through Designer’s Block

Are you experiencing designer’s block? Having a hard time starting a new project? You aren’t alone. After more than 11 months of designing and programming (which invariably involved numerous successes and failures), many engineers are simply spent. But don’t worry. Just like every other year, new projects are just around the corner. Sooner or later you’ll regain your energy and find yourself back in action. Plus, we’re here to give you a boost. The December issue (Circuit Cellar 269) is packed with projects that are sure to inspire your next flurry of innovation.

Turn to page 16 to learn how Dan Karmann built the “EBikeMeter” Atmel ATmega328-P-based bicycle computer. He details the hardware and firmware, as well as the assembly process. The monitoring/logging system can acquire and display data such as Speed/Distance, Power, and Recent Log Files.

The Atmel ATmega328-P-based “EBikeMeter” is mounted on the bike’s handlebar.

Another  interesting project is Joe Pfeiffer’s bell ringer system (p. 26). Although the design is intended for generating sound effects in a theater, you can build a similar system for any number of other uses.

You probably don’t have to be coerced into getting excited about a home control project. Most engineers love them. Check out Scott Weber’s garage door control system (p. 34), which features a MikroElektronika RFid Reader. He built it around a Microchip Technology PIC18F2221.

The reader is connected to a breadboard that reads the data and clock signals. It’s built with two chips—the Microchip 28-pin PIC and the eight-pin DS1487 driver shown above it—to connect it to the network for testing. (Source: S. Weber, CC269)

Once considered a hobby part, Arduino is now implemented in countless innovative ways by professional engineers like Ed Nisley. Read Ed’s article before you start your next Arduino-related project (p. 44). He covers the essential, but often overlooked, topic of the Arduino’s built-in power supply.

A heatsink epoxied atop the linear regulator on this Arduino MEGA board helped reduce the operating temperature to a comfortable level. This is certainly not recommended engineering practice, but it’s an acceptable hack. (Source: E. Nisley, CC269)

Need to extract a signal in a noisy environment? Consider a lock-in amplifier. On page 50, Robert Lacoste describes synchronous detection, which is a useful way to extract a signal.

This month, Bob Japenga continues his series, “Concurrency in Embedded Systems” (p. 58). He covers “the mechanisms to create concurrently in your software through processes and threads.”

On page 64, George Novacek presents the second article in his series, “Product Reliability.” He explains the importance of failure rate data and how to use the information.

Jeff Bachiochi wraps up the issue with a article about using heat to power up electronic devices (p. 68). Fire and a Peltier device can save the day when you need to charge a cell phone!

Set aside time to carefully study the prize-winning projects from the Reneas RL78 Green Energy Challenge (p. 30). Among the noteworthy designs are an electrostatic cleaning robot and a solar energy-harvesting system.

Lastly, I want to take the opportunity to thank Steve Ciarcia for bringing the electrical engineering community 25 years of innovative projects, essential content, and industry insight. Since 1988, he’s devoted himself to the pursuit of EE innovation and publishing excellence, and we’re all better off for it. I encourage you to read Steve’s final “Priority Interrupt” editorial on page 80. I’m sure you’ll agree that there’s no better way to begin the next 25 years of innovation than by taking a moment to understand and celebrate our past. Thanks, Steve.