What is Data Acquisition (DAQ)?

These systems have embedded processors and internal storage that allow them to operate independently without being directly connected to a PC. Standalone DAQ systems can function in remote environments or industrial settings where continuous monitoring is required. The NR-X100 is a great option when standalone logging is required.

PC-based DAQ systems connect directly to a computer via USB, PCI, or Ethernet, relying on a computer’s processing power to analyze data in real time. These systems are flexible in handling multiple input types at once. The NR-500 data logger is the industry's smallest, most capable PC based DAQ system.

For applications that require multiple sensors or custom configuration, a modular DAQ system offers the most flexibility. These systems are separate, interchangeable modules that can accommodate a business’s rapid growth. Modular DAQ systems also support automation platforms for advanced industrial applications. The NR-Series is completely modular, allowing users to completely customize their DAQ system for whatever application they face.

As more industries adopt IoT devices, DAQ systems are moving to the cloud. Wireless DAQ systems eliminate the need for extensive cabling. Being cloud-connected allows for remote access and real-time monitoring. With 5G connectivity, wireless DAQ systems can provide near-instantaneous access to data from multiple locations.

Modern DAQ systems can process millions of data samples per second, which makes them ideal for high-speed logging and rapid signal analysis. These include capturing transient voltage spikes in power electronics and monitoring high-speed conveyor belts in manufacturing.

Some industries need DAQ systems to monitor temperature, humidity, air quality, and emissions. Many of these systems are used to keep products and processes in line with regulatory standards from the FDA and EPA.

DAQ systems are also used to detect early warning signs of wear and tear for industrial machinery. Predictive maintenance strategies benefit from the data provided by DAQ systems to help prevent unscheduled downtime and costly repairs.

These DAQ systems are used to detect anomalies as they happen, allowing operators to immediately respond to potential issues. These systems are useful in high-stakes industries like industrial automation, process control, and medical diagnostics.

While real-time DAQ focuses on immediate anomaly detection, post-processing analysis helps evaluate long-term trends and simulate predictive modeling.

Measurement Type

Determine whether you need to monitor electrical (i.e. current, voltage), mechanical (i.e. vibration, force), or environmental (i.e. temperature, humidity) parameters.

Number of Channels Required

Large-scale operations may require hundreds of input channels while smaller applications can function with fewer.

Compatibility with Existing Software & Cloud Platforms

The DAQ system selected should integrate with existing enterprise software, automation tools, and IoT platforms.

AI-driven DAQ platforms can predict equipment failures, monitor and maintain energy consumption, and improve quality control processes. These systems allow businesses to automate data analysis, detect patterns, and improve machine output without manual intervention.

With the rise of smart factories, IoT-enabled DAQ systems allow businesses to remotely access and monitor data from multiple locations without having to visit each individual plant.

DAQ systems are evolving to consume less power and adapt to renewable energy sources. Low-power DAQ systems help industries fulfill sustainability initiatives by reducing energy consumption in remote monitoring stations and wireless IoT deployments.