Description and definition of data loggers and data acquisition, and a summary of the main benefits.

What is a data logger?

Data loggers are electronic devices which automatically monitor and record environmental parameters over time, allowing conditions to be measured, documented, analysed and validated. The data logger contains a sensor to receive the information and a computer chip to store it. Then the information stored in the data logger is transferred to a computer for analysis.

Loggers in the Tinytag range monitor parameters including temperature, humidity, single and three phase power usage, CO₂, mV, mA, voltage, pulses or counts.

What is data acquisition?

Data acquisition is the sampling of the real world to generate data that can be manipulated by a computer. Sometimes abbreviated DAQ, data acquisition typically involves acquisition of signals and waveforms and processing of the signals to obtain desired information. The components of data acquisition systems include appropriate sensors that convert any measurement parameter to an electrical signal, which is acquired by data acquisition hardware (such as data loggers). Acquired data typically is displayed, analysed, and stored on a PC.

Benefits of using a data logger

Data logging can be done manually by constant human observation. An example of this might be recording the temperature changes over the course of an hour in a centrally heated room using a timer, thermometer, pen and paper. However, using an electronic data logger is much more effective, accurate and reliable than taking periodic manual readings. It does the job of all the tools mentioned above, saving time and expense.

The time taken to see the benefits of using data loggers will depend on the way in which the units are used. However, quantifiable benefits from the using loggers may often be seen within a very short time. Typically, only one or two logging runs are required to pinpoint areas that would benefit from extra attention.

Next page: Where and why are data loggers used?

Go back to: Understanding Data Loggers