The Future of Data Acquisition Technology

Maurizio Di Paolo Emilio

Maurizio Di Paolo Emilio

By Maurizio Di Paolo Emilio

Data acquisition is a necessity, which is why data acquisition systems and software applications are essential tools in a variety of fields. For instance, research scientists rely on data acquisition tools for testing and measuring their laboratory-based projects. Therefore, as a data acquisition system designer, you must have an in-depth understanding of each part of the systems and programs you create.

I mainly design data acquisition software for physics-related experiments and industrial applications. Today’s complicated physics experiments require highly complex data acquisition systems and software that are capable of managing large amounts of information. Many of the systems require high-speed connections and digital recording. And they must be reconfigurable. Signals that are hard to characterize and analyze with a real-time display are evaluated in terms of high frequencies, large dynamic range, and gradual changes.

Data acquisition software is typically available in a text-based user interface (TUI) that comprises an ASCII configuration file and a graphic user interface (GUI), which are generally available with any web browser. Both interfaces enable data acquisition system management and customization, and you don’t need to recompile the sources. This means even inexperienced programmers can have full acquisition control.

Well-designed data acquisition and control software should be able to quickly recover from instrumentation failures and power outages without losing any data. Data acquisition software must provide a high-level language for algorithm design. Moreover, it requires data-archiving capability for verifying data integrity.

You have many data acquisition software options. An example is programmable software that uses a language such as C. Other software and data acquisition software packages enable you to design the custom instrumentation suited for specific applications (e.g., National Instruments’s LabVIEW and MathWorks’s MATLAB).

In addition to data acquisition software design, I’ve also been developing embedded data acquisition systems with open-source software to manage user-developed applications. The idea is to have credit-card-sized embedded data acquisition systems managing industrial systems using open-source software written in C. I’m using an ARM processor that will give me the ability to add small boards for specific applications (e.g., a board to manage data transmission via Wi-Fi or GSM).

A data acquisition system’s complexity tends to increase with the number of physical properties it must measure. Resolution and accuracy requirements also affect a system’s complexity. To eliminate cabling and provide for more modularity, you can combine data acquisition capabilities and signal conditioning in one device.

Recent developments in the field of fiber-optic communications have shown longer data acquisition transmission distances can cause errors. Electrical isolation is also an important topic. The goal is to eliminate ground loops (common problems with single-ended measurements) in terms of accuracy and protection from voltage spikes.

During the last year, some new technological developments have proven beneficial to the overall efficacy of data acquisition applications. For instance, advances in USB technology have made data acquisition and storage simpler and more efficient than ever (think “plug and play”). Advances in wireless technology have also made data transmission faster and more secure. This means improved data acquisition system and software technologies will also figure prominently in smartphone design and usage.

If you look to the future, consumer demand for mobile computing systems will only increase, and this will require tablet computers to feature improved data acquisition and storage capabilities. Having the ability to transmit, receive, and store larger amounts of data with tablets will become increasingly important to consumers as time goes on. There are three main things to consider when creating a data acquisition-related application for a tablet. Hardware connectivity: Tablets have few control options (e.g., Wi-Fi and Bluetooth). Program language support: Many tablets support Android apps created in Java. Device driver availability: Device drivers permit a high-level mode to easily and reliably execute a data acquisition board’s functionality. C and LabVIEW are not supported by Android or Apple’s iOS. USB, a common DAQ bus, is available in a set of tablets. In the other case, an adapter is required. In these instances, moving a possible data acquisition system to a tablet requires extra attention.

For all of the aforementioned reasons, I think field-programmable arrays (FPGAs) will figure prominently in the evolution of data acquisition system technology. The flexibility of FPGAs makes them ideal for custom data acquisition systems and embedded applications.

The Future of FPGAs (CC 25th Anniversary Preview)

Field-programmable gate arrays (FPGAs) have been around for more than two decades. What does the future hold for this technology? According to Halifax, Canada-based electrical engineering consultant Colin O’Flynn, current FPGA-related research and recent innovations seem to presage a coming revolution in digital system design, and this could lead to striking fast advances in several fields of engineering.

In the upcoming Circuit Cellar 25th Anniversary Issue—which is slated for publication in early 2013—O’Flynn shares his thoughts on the future of FPGA technology. He writes:

Field-programmable gate arrays (FPGAs) provide a powerful means to design digital systems (see Photo 1). Rather than writing a software program, you can design a number of hardware blocks to perform your tasks at blazing speeds…

Photo 1: Source: C. O’Flynn, CC 25th Anniversary issue

Microcontrollers have long played the peripheral game: the integration of easy-to-use dedicated peripherals onto the same physical chip as your digital core. FPGAs, it would seem, have no use for dedicated logic, since you can just design everything exactly as you desire. But dedicated logic has its advantages.

Beyond technical advantages, such as lower power consumption or smaller area with dedicated cores compared to programmable cores, dedicated cores can also reduce development effort. For example, current technology sees FPGAs with integrated high-end ARM cores, capable of running Linux on the integrated hard-core. Anyone familiar with setting up Linux on an ARM-based microprocessor can use this, without needing to learn about how one develops cores and peripherals on the FPGA itself.
Beyond integrating digital cores to simplify development, you can expect to see the integration of analog peripherals. Looking at the microcontroller market, you can find a variety of tightly integrated SoC devices with analog and digital on a single device. For instance, a variety of radio devices contain a complete RF front-end combined with a digital microcontroller. While current FPGA devices offer very limited analog peripherals (most have none), having a FPGA with an integrated high-speed ADC or DAC would be the making of a highly flexible radio-on-a-chip platform. The high development cost and lack of a current market has meant this remains only an interesting idea. To see where this market comes from, let’s look at some applications for such an FPGA.

Software-Defined Radio
Software-defined radio (SDR) takes a curious approach to receiving radio waves: digitize it all, and let software sort it out. The radio front-end is simple. Typically, the center frequency of interest is just downshifted to the baseband, everything else is filtered out, and a high-speed ADC digitizes it. All the demodulation and decoding then can be down in software. Naturally, this can require some fast sampling speeds. Anything from 20 to 500 MSps is fairly typical for these systems. Dealing with this much data is suited to FPGAs, since one can generate blocks to perform all the different functions that operate simultaneously…

Circuit Cellar’s Circuit Cellar 25th Anniversary Issue will be available in early 2013. Stay tuned for more updates on the issue’s content.

Q&A: Hai (Helen) Li (Academic, Embedded System Researcher)

Helen Li came to the U.S. from China in 2000 to study for a PhD at Purdue University. Following graduation she worked for Intel, Qualcomm, and Seagate. After about five years of working in industry, she transitioned to academia by taking a position at the Polytechnic Institute of New York University, where she teaches courses such as circuit design (“Introduction to VLSI”), advanced computer architecture (“VLSI System and Architecture Design”), and system-level applications (“Real-Time Embedded System Design”).

Hai (Helen) Li

In a recent interview Li described her background and provided details about her research relating to spin-transfer torque RAM-based memory hierarchy and memristor-based computing architecture.

An abridged version of the interview follows.

NAN: What were some of your most notable experiences working for Intel, Qualcomm, and Seagate?

HELEN: The industrial working experience is very valuable to my whole career life. At Seagate, I led a design team on a test chip for emerging memory technologies. Communication and understanding between device engineers and design communities is extremely important. The joined effects from all the related disciplines (not just one particular area anymore) became necessary. The concept of cross layers (including device/circuit/architecture/system) cooptimization, and design continues in my research career.

NAN: In 2009, you transitioned from an engineering career to a career teaching electrical and computer engineering at the Polytechnic Institute of New York University (NYU). What prompted this change?

HELEN: After five years of working at various industrial companies on wireless communication, computer systems, and storage, I realized I am more interested in independent research and teaching. After careful consideration, I decided to return to an academic career and later joined the NYU faculty.

NAN: How long have you been teaching at the Polytechnic Institute of NYU? What courses do you currently teach and what do you enjoy most about teaching?

HELEN: I have been teaching at NYU-Poly since September 2009. My classes cover a wide range of computer engineering, from basic circuit design (“Introduction to VLSI”), to advanced computer architecture (“VLSI System and Architecture Design”), to system-level applications (“Real-Time Embedded System Design”).

Though I have been teaching at NYU-Poly, I will be taking a one-year leave of absence from fall 2012 to summer 2013. During this time, I will continue my research on very large-scale integration (VLSI) and computer engineering at University of Pittsburgh.

I enjoy the interaction and discussions with students. They are very smart and creative. Those discussions always inspire new ideas. I learn so much from students.

Helen and her students are working on developing a 16-Kb STT-RAM test chip.

NAN: You’ve received several grants from institutions including the National Science Foundation and the Air Force Research Lab to fund your embedded systems endeavors. Tell us a little about some of these research projects.

HELEN: The objective of the research for “CAREER: STT-RAM-based Memory Hierarchy and Management in Embedded Systems” is to develop an innovative spin-transfer torque random access memory (STT-RAM)-based memory hierarchy to meet the demands of modern embedded systems for low-power, fast-speed, and high-density on-chip data storage.

This research provides a comprehensive design package for efficiently integrating STT-RAM into modern embedded system designs and offers unparalleled performance and power advantages. System architects and circuit designers can be well bridged and educated by the research innovations. The developed techniques can be directly transferred to industry applications under close collaborations with several industry partners, and directly impact future embedded systems. The activities in the collaboration also include tutorials at the major conferences on the technical aspects of the projects and new course development.

The main goal of the research for “CSR: Small Collaborative Research: Cross-Layer Design Techniques for Robustness of the Next-Generation Nonvolatile Memories” is to develop design technologies that can alleviate the general robustness issues of next-generation nonvolatile memories (NVMs) while maintaining and even improving generic memory specifications (e.g., density, power, and performance). Comprehensive solutions are integrated from architecture, circuit, and device layers for the improvement on the density, cost, and reliability of emerging nonvolatile memories.

The broader impact of the research lies in revealing the importance of applying cross-layer design techniques to resolve the robustness issues of the next-generation NVMs and the attentions to the robust design context.

The research for “Memristor-Based Computing Architecture: Design Methodologies and Circuit Techniques” was inspired by memristors, which have recently attracted increased attention since the first real device was discovered by Hewlett-Packard Laboratories (HP Labs) in 2008. Their distinctive memristive characteristic creates great potentials in future computing system design. Our objective is to investigate process-variation aware memristor modeling, design methodology for memristor-based computing architecture, and exploitation of circuit techniques to improve reliability and density.

The scope of this effort is to build an integrated design environment for memristor-based computing architecture, which will provide memristor modeling and design flow to circuit and architecture designers. We will also develop and implement circuit techniques to achieve a more reliable and efficient system.

An electric car model controlled by programmable emerging memories is in the developmental stages.

NAN: What types of projects are you and your students currently working on?

HELEN: Our major efforts are on device modeling, circuit design techniques, and novel architectures for computer systems and embedded systems. We primarily focus on the potentials of emerging devices and leveraging their advantages. Two of our latest projects are a 16-Kb STT-RAM test chip and an electric car model controlled by programmable emerging memories.

The complete interview appears in Circuit Cellar 267 (October 2012).

CC266: Microcontroller-Based Data Management

Regardless of your area of embedded design or programming expertise, you have one thing in common with every electronics designer, programmer, and engineering student across the globe: almost everything you do relates to data. Each workday, you busy yourself with acquiring data, transmitting it, repackaging it, compressing it, securing it, sharing it, storing it, analyzing it, converting it, deleting it, decoding it, quantifying it, graphing it, and more. I could go on, but I won’t. The idea is clear: manipulating and controlling data in its many forms is essential to everything you do.

The ubiquitous importance of data is what makes Circuit Cellar’s Data Acquisition issue one of the most popular each year. And since you’re always seeking innovative ways to obtain, secure, and transmit data, we consider it our duty to deliver you a wide variety of content on these topics. The September 2012 issue (Circuit Cellar 266) features both data acquisition system designs and tips relating to control and data management.

On page 18, Brian Beard explains how he planned and built a microcontroller-based environmental data logger. The system can sense and record relative light intensity, barometric pressure, relative humidity, and more.

a: This is the environmental data logger’s (EDL) circuit board. b: This is the back of the EDL.

Data acquisition has been an important theme for engineering instructor Miguel Sánchez, who since 2005 has published six articles in Circuit Cellar about projects such as a digital video recorder (Circuit Cellar 174), “teleporting” serial communications via the ’Net (Circuit Cellar 193), and a creative DIY image-processing system (Circuit Cellar 263). An informative interview with Miguel begins on page 28.

Turn to page 38 for an informative article about how to build a compact acceleration data acquisition system. Mark Csele covers everything you need to know from basic physics to system design to acceleration testing.

This is the complete portable accelerometer design. with the serial download adapter. The adapter is installed only when downloading data to a PC and mates with an eight pin connector on the PCB. The rear of the unit features three powerful
rare-earth magnets that enable it to be attached to a vehicle.

In “Hardware-Accelerated Encryption,” Patrick Schaumont describes a hardware accelerator for data encryption (p. 48). He details the advanced encryption standard (AES) and encourages you to consider working with an FPGA.

This is the embedded processor design flow with FPGA. a: A C program is compiled for a softcore CPU, which is configured in an FPGA. b: To accelerate this C program, it is partitioned into a part for the software CPU, and a part that will be implemented as a hardware accelerator. The softcore CPU is configured together with the hardware accelerator in the FPGA.

Are you now ready to start a new data acquisition project? If so, read George Novacek’s article “Project Configuration Control” (p. 58), George Martin’s article “Software & Design File Organization” (p. 62), and Jeff Bachiochi’s article “Flowcharting Made Simple” (p. 66) before hitting your workbench. You’ll find their tips on project organization, planning, and implementation useful and immediately applicable.

Lastly, on behalf of the entire Circuit Cellar/Elektor team, I congratulate the winners of the DesignSpark chipKIT Challenge. Turn to page 32 to learn about Dean Boman’s First Prize-winning energy-monitoring system, as well as the other exceptional projects that placed at the top. The complete projects (abstracts, photos, schematic, and code) for all the winning entries are posted on the DesignSpark chipKIT Challenge website.

FPGA-Based VisualSonic Design Project

The VisualSonic Studio project on display at Design West last week was as innovative as it was fun to watch in operation. The design—which included an Altera DE2-115 FPGA development kit and a Terasic 5-megapixel CMOS Sensor (D5M)—used interactive tokens to control computer-generated music.

at Design West 2012 in San Jose, CA (Photo: Circuit Cellar)

I spoke with Allen Houng, Strategic Marketing Manager for Terasic, about the project developed by students from National Taiwan University. He described the overall design, and let me see the Altera kit and Terasic sensor installation.

A view of the kit and sensor (Photo: Circuit Cellar)

Houng also he also showed me the design in action. To operate the sound system, you simply move the tokens to create the sound effects of your choosing. Below is a video of the project in operation (Source: Terasic’s YouTube channel).