FIELD: information technology.
SUBSTANCE: invention relates to computer systems, namely to the Internet of Things. Disclosed is a method for detecting hidden interactions on the Internet of Things, comprising collection of data from devices connected to the Internet, aggregation of received data by devices, data normalization, event generation, characterized by the fact that data is generated from the event data described by the tuple: Event = {source, recipient, type, time}, then the events are classified for each device in terms of the degree of similarity, then for the whole set of devices, the devices are selected by pairs, wherein for each device from the pair, events of the same type are selected, for example, "command" or "measurement value", the time period T during which for both selected devices connected to the Internet, the database has the events generated by them, is selected, such events that occurred during the period T are selected from the database and two sets of data are obtained, where each set consists of a sequence of events selected from the database, and for these two sets of data, a pair correlation coefficient characterizing the linear relationship between the data sets, and the agreement coefficient in dynamics, characterizing the nonlinear interaction between data sets and calculated using the mathematical apparatus of finite differences, are calculated; if the values of both coefficients are more than 0.5 modulo, there is interaction, and it is linear; if the values of the agreement coefficient in dynamics are less than 0.3 modulo, there is no interaction; if the value of the correlation coefficient is less than 0.3, and the value of the agreement coefficient in dynamics is more than 0.5, there is interaction, and it is nonlinear.
EFFECT: detecting hidden interactions on the Internet of Things.
1 cl, 1 dwg, 2 tbl
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Authors
Dates
2018-05-16—Published
2015-11-10—Filed