Redundancy is when sensor readings or items of data replicate in full or part data that is sensed or stored elsewhere. Redundancy can be seen as a source of inefficiency so that one may try to remove redundant values as part of data clearening. However, redundancy can also be critical in fault tolerant systems allowinga. level of recovery if a sensor fails or data is lost. Redundancy may be precise, in that one peoce of data can be calculated from others. Alterbatively, the redundant data items may be statistically related, for example where several values in some way measure or represnt the same thing, but have a degree of noise. In this case statistical techniques, including simple averaging or {[time series}} techniques can be used to obtian a smaller number of more accurate readings. In actvity recognition systems redundant sensors give more {[robust}} detection, but also mean that as new sensors are addedd, they can be correlated with existing sensors, adding to redundacy especially if existing sensors fail or are removed and allowing deployments of sensors to change whilst retaining higher-level reasoning.
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Also known as redundant data