Data Logging

Mackenzie, Aselin, Adrian

Image of Mars generated using data from the Mars Orbiter Laser Altimeter aboard the Mars Global Surveyor spacecraft and satellite imagery from the Blue Marble Next Generation project.


Data logging is the automatic recording of data using sensors, without human intervention.

How it works: First, the data logger is connected to a personal computer. Then the turn-key data logging software is used to select logging parameters (sampling intervals, start time, etc.) and initiate the logger. The logger is then disconnected and deployed in the desired location. The logger records each measurement and stores it in memory along with the time and date. The logger is then reconnected to the personal computer and the software is used again to readout the data and see the measurements as a graph, showing the profile over time. The interface box stores/converts signals from sensors into a form the computer can understand. The tabular data can be viewed as well, or exported to a spreadsheet for further manipulation.

Analog vs. Digital Data: Analog data (continuous data) is what's measured. Digital data (discrete data) is what is counted. Physical data such as temperature, altitude and speed are analog signals, and because computers only work with digital data, the analog signals must be processed by and Analog to  Digital Converter. This is digitization, sometimes called sampling. The quality of digitization depends on two things, the sample rate- the number of times each second a sample of the analog data is taken, and sample precision- amount of data that can be represented.

What data logging is used for: Monitoring weather, environmental data, space environments, health vitals, flight data, traffic pollution, and vehicle response.

Satellite Communication and Imaging: Advanced imaging satellites (the use on satellites to measure or record information, usually about the Earth) orbit the earth and take photos of any location of our planet at high resolutions. Remote sensing use techniques like Radar (radio waves), Lidar (lasers), and Sonar (sound waves) to record things that are not visible. The returned data is then processed to produce useful visualization of the data.

Weather monitoring: Photographs taken by satellites and information taken from remote sensors are used to monitor climate and environmental change. This is helpful because weather can be monitored in remote places which are too large or dangerous to be measured manually on the ground. Collection of data from infrared sensors enables land and ocean temperatures to be calculated which can help to make predictions about weather.

Advantages: Data loggers can sample large numbers of variables at once and frequently. The integrity of the data is also greater because it takes human error out of the equation. Data can also be collected in harsh or dangerous environments with limited risk to humans. Data logging systems can record data constantly but only alert humans when values pass outside a certain range. This way, humans don't have to monitor the data all the time.

Disadvantages: In practice, when the data loggers work well, there are very few disadvantages, but if the data logging equipment breaks, some of the data could be lost or not recorded. Equipment can be expensive, and sensors must be carefully calibrated.

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