We have entered the Age of Data. The amount of data being collected is growing at an explosive rate as companies rely more heavily on data to make critical business decisions. Engineers require reliable, accurate, and easy-to-use data acquisition systems to meet this need. However, innovation in the data acquisition market has not kept pace with this unquenchable thirst for data. Data acquisition tools must evolve to better address the demands of the growing population of users who need data to inform their design decisions. These tools have fallen behind in two critical areas: providing simple yet flexible software and simplifying measurement system setup.
Today, users are forced to choose between limited configuration software, which helps with basic data recording but cannot be modified to meet application requirements, or their own custom data acquisition applications that must be programmed from scratch. Hardware vendors provide software with the bare essentials for recording data from devices, but they push users to a different tool to program a solution when needs beyond that software’s capabilities arise. This is an unnecessary forced trade-off; data acquisition software should evolve to span the gulf between configuration and customization. System setup requires different measurements with a variety of wiring schemes and hardware and software configurations to represent a user’s true signal with maximum fidelity. Again, software must improve to make system setup easier for users. Engineering efficiency is suffering because of these shortcomings. In a survey of 3,800 engineers, 27% identified that developing software for their application was the most time consuming part of their task, while 21% spent most of their time struggling with system setup.
To keep up with the growing need for data, engineers must demand more from data acquisition systems. Innovation in data acquisition software can play a critical role in meeting these challenges.
Engineers use two types of data acquisition software products at opposite ends of a complexity spectrum: the fixed-functionality configuration-based measurement software included with a data acquisition device and the custom software applications users code to control their devices. Fixed-functionality software is good for setting up a quick, simple measurement from a device to configure basic settings like sampling rate, hit a record button, and save raw data to a file. But custom software applications give users the power to program any functionality if they have the know-how and patience to do it. In the programming scenario, engineers can define exactly; the measurement or behavior they need. This requires the time for programming and validating a solution as well as the expertise needed to build this software from scratch.
Users who want a mostly typical data acquisition application for acquiring and saving data, with some minor modifications like a custom analysis algorithm or basic conditional logic, are forced to choose between these two extremes. As soon as their needs increase beyond the software that comes in the box with their hardware devices, they must make the leap to the other extreme: a fully custom, programmed solution.
There is no reason that data acquisition software can’t evolve to better fill this spectrum. A software solution that offers a continuum from configurable measurements to customization through programming would help engineers be more efficient. A configuration-based experience is tremendously useful for the common parts of a data acquisition application, like setting up the sensors attached to a channel, selecting sampling rates, and implementing basic triggering and scaling. A software solution that could preserve this configuration, and help engineers use that configuration as a foundation to build custom functionality in an intuitive programming environment, would remove the strict trade-off between ease of use via configuration and maximum flexibility via programming.
System Setup Time Sink
Anyone who has built a measurement system knows that setup is time-consuming, and an incorrect setup can introduce errors into a system that may be hard to debug. Different types of measurements may require varying hardware specifications, wiring schemes, and unique software configurations to represent a true signal with maximum fidelity. Today, engineers can choose from a wide range of systems featuring flexible, modular data acquisition hardware that they can adapt and reconfigure to meet changing I/O and sampling needs. Though this is highly beneficial to users who face challenging or evolving system requirements, the flexibility of the system complicates the system setup process.
Consider a device with a single function like a handheld device for measuring temperature. When using this device, the risk for error in measurement setup is low. Since the device has a single use, the hardware and software for that device are built to meet that need, and the possible set of configurations is limited. Conversely, a modular data acquisition system features a range of I/O options and provides many different measurement combinations. This flexibility helps lower total system cost since the same set of hardware can be adapted to serve a range of applications. But with that comes more possible configuration options that can complicate system setup. Data acquisition software can be better designed to remove this complexity.
Today, the software packaged with data acquisition devices does little to help users understand and document system connections such as wires between sensors. There is a tremendous opportunity for software to overcome these complexities. Better data acquisition software could reduce system setup complexity through improved system visualization, recommendations for correct wiring, and better checks for channel configuration.
Data acquisition plays a critical role in driving innovation and discovery. Engineers rely heavily on acquiring the right data to support design decisions, and advances in data acquisition software could have a tremendous impact on improving their efficiency. To achieve this, data acquisition software must evolve to fill the gap between limited configurable software and flexible but costly to build custom programmatic solutions without increasing system setup complexity. To keep pace with the growing demand for data, it’s time to demand more from the software we use to acquire it.