Data Acquisition (DAQ) Hardware Market Share, Size, Regional Trend, Future Growth, Leading Players Updates 2025

Data acquisition hardware comprises signal conditioning circuitry, sensors, and analog-to-digital converters. Sensors are also called transducers that convert physical parameters into measurable electrical signals. The signal circuitry converts sensor signals to numerical values. Data acquisition hardware is an industrial control system that collects the data from instruments and sensors positioned at isolated sites, then communicates and demonstrates this data at an essential site for monitoring and control purposes. It is also used to collect and analyze data in real time. DAQ exploits the processing power, productivity, and connectivity capabilities of industry standard computers to provide powerful, cost effective, and flexible measurement solutions.

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Factors favorable to the growth of the market are the increasing developments related to plug-in data acquisition board size. Further, increasing adoption of dedicated solutions for strategic decision making is expected to favor the growth of the data acquisition hardware market. With the number of industrial sites being set up in remote locations projected to surge during the forecast period, central monitoring requirements are projected to drive the DAQ market. Moreover, higher growth rate of industrial operations is anticipated to increase the demand for automation requirements resulting in higher opportunities for the market.

Data acquisition hardware is widely adopted for design validation, research & analysis, manufacturing & quality tests, asset condition monitoring, verification, diagnostics & repair, and computer based control and automation. Further, increasing analysis and design activities such as modeling behavior of scientific phenomenon and new product design is expected to support the growth of the data acquisition hardware market. Operations such as verifying product lifecycle, testing for accuracy and reliability, ensuring conformance to industry standards, and establishing evidence, design validation and testing is required for maintaining the required standards. The manufacturing and quality testing for electrical, mechanical, and environmental parameters is also carried out with the help of data acquisition hardware. Diagnostics and repair systems are useful to recognize root cause of the problem within machinery and image inspection systems. Moreover, asset conditioning and monitoring solutions are used for the durable condition monitoring of equipment such as turbines and compressors and to detect problems and prevent failures. Condition monitoring helps to prevent outages, optimize performance, and reduce repair costs. Computer based control systems help in handling various processes and machinery without human interaction. However, increasing complexity related to signal conditioning in the data acquisition market is expected to restrain the growth of this market.

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The data acquisition (DAQ) hardware market is anticipated to expand at a higher rate during the forecast period. Also, large investments in infrastructure would support the growth of the market. Industries are progressively demanding automated processes to simplify the operations. The market of data acquisition (DAQ) hardware is forecast to experience an encouraging surge in growth with the increasing demand for real time decision making and analysis.

The data acquisition (DAQ) hardware market can be segmented on the basis of component and end-users. Based on component, the market can be segregated into human machine interface, data acquisition software, remote terminal unit (RTU), SCADA, communication system, and programmable logic components. Furthermore, it is used by various end-users such as aviation and defense, chemicals, transportation, food and beverages, power generation, oil & gas, manufacturing, waste water treatment and others.

Some of the leading players driving the data acquisition (DAQ) hardware market are ABB Ltd., Advantech, Agilent Technologies, Campbel Scientific, Data Translation, Schneider Electric, Honeywell International, Siemens AG, Rockwell Automation, MathWorks, General Electric, Omron, Alstom,Yokogawa Electric Co, and Emerson Electric Co.

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