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Terms starting with D
Definition
Many options exist for air sensor data communication from the sensor to the sensor data repository and include cellular, WiFi, Bluetooth, satellite, low-power wide-area network (LoRa), or other methods. Remember that you may want to test the communications at the actual site and inquire about ongoing costs associated with communicating data via cellular and other protocols. Ensure that you have the ability to enable the necessary settings on your computer and/or WiFi network to allow you to use the selected data transmission option (if applicable). Connectivity is key to any Internet of Things (IoT) deployment. Communication between machines is integral in IoT as it enables pieces of hardware to gather and exchange data.
Drift or shift in data refers to a gradual change in sensor’s response characteristics over time. The shift can be positive or negative, which may lead to wrong conclusions. Drifts may occur due to a variety of reasons. One of the ways to reduce the drift is to calibrate the sensor frequently so that the instrument only drifts a small amount between each recalibration. A change in the response or concentration reported by a sensor when challenged by the same pollutant concentration over a period during which the sensor is operated continuously and without adjustment.
A collection of procedures and software needed to acquire, process, and distribute data.
Data points with higher concentrations from one or more instruments.
A pollutant-and sample-specific process that extends the evaluation of data beyond method, procedural, or contractual compliance (i.e., data verification) to determine the analytical quality of a specific data set.
The placement or arrangement of air sensors or instruments for a specific monitoring purpose or objective.
When the autocorrelation is high at a specific lag, it indicates that there is a repeating pattern or relationship between data points separated by that time lag. Autocorrelation is often used in time series analysis to identify trends, seasonality, or periodic patterns in data. It is a valuable tool in fields such as statistics, signal processing, and econometrics for understanding and modeling temporal dependencies in data.
Where air goes after moving over an area of interest.
Quantitative acceptance criteria for the quality and quantity of data to be collected, relative to the ultimate use of the data.
