Reducing Sensors according to a Vectors Analysis of stored measurements (ReSeVA)

Balouch, Ammar (2015) Reducing Sensors according to a Vectors Analysis of stored measurements (ReSeVA). American Research Journal of Computer Science and Information Technology, Chicago, USA, 1 (1 (DEC). 20 - 28.

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The recognition of motion is widely used in games development field but it is active too in care systems. Recognition of motion according measurements needs data (values) from many sensors, like Position, Velocity, Acceleration, Orintation, etc. We have two major ways to determine which placements of sensors on the body are required to recognize the motion. The first way connects its work with the results of other science branches like sports science and game development. The other one depends on the following strategy. Many sensors were placed on the body, without the knowledge, which sensors are required. Then according an analysis of the stored data for each sensors, the behavioral similarity of these sensors will be extracted. The target of both ways is to reduce the cost of building a suit of sensors, and simultaneously to keep the results of the recognition of motion correct. In this paper we follow the second way and define a new regression analysis “ReSeVA” depending on vector definition (on its angles and longs) and on the principle of Newton’s law of metion.

Item Type: Article
Uncontrolled Keywords: Data analysis, Distance matrix analysis, Elimination of sensors, linear Regression, recognition of motion, Vector
Subjects: Autorenart > DBIS-Publikationen
Depositing User: Dbis Admin
Date Deposited: 24 Mar 2016 11:11
Last Modified: 24 Mar 2016 11:11

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