A new perspective on the temperature inside tropical forests

Tropical forests host up to half of the planet's biodiversity but up to now, ecological studies over tropical forests often relied on large scale datasets depicting open-air temperatures—that is, the temperature outside ...

Tree-hugging AI to the rescue of Brazilian Amazon

Small, artificially intelligent boxes tied to tree trunks in the Brazilian Amazon are the latest weapon in the arsenal of scientists and environmentalists battling destructive jungle invaders.

Soil sensor yields beneficial information for farmers

If you're a gardener, you know that planting seeds in the ground doesn't always mean you'll have a good yield at the end of growing season. On a personal level, this can be disappointing. Farmers are in charge of growing ...

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Sensor fusion

Sensor fusion is the combining of sensory data or data derived from sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually. The term better in that case can mean more accurate, more complete, or more dependable, or refer to the result of an emerging view, such as stereoscopic vision (calculation of depth information by combining two-dimensional images from two cameras at slightly different viewpoints).

The data sources for a fusion process are not specified to originate from identical sensors. One can distinguish direct fusion, indirect fusion and fusion of the outputs of the former two. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft sensors, and history values of sensor data, while indirect fusion uses information sources like a priori knowledge about the environment and human input.

Sensor fusion is also known as (multi-sensor) Data fusion and is a subset of information fusion.

This text uses material from Wikipedia, licensed under CC BY-SA