Causal Analytics in IIoT – AI That Knows What Causes What, and When
These real-world applications involve methods that take into account the complexity of systems( thereby including analytics of system machine and log data). The inter-dependencies and dimensionality of many IIoT system devices mean that identifying their behavior( causal and otherwise) can be extremely difficult depending on the magnitude and nature of the couplings. One variable may be found to be a driver of another, but not alone. The multiple influences that have an impact on a particular variable must be teased out, such as the timings, state-dependencies and multi-dimensionality of other influences that impact an‘ effect’ of interest, such as a decrease in pressure or rise in temperature. These are identified as part of the rCA process for IIoT. industrial applied mathematics." 31 This is a fairly recent set of developments and especially with respect to incorporating AI and machine learning where these algorithms can be applied to IIoT data at scale.
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Although the rCA approach can be employed on an ad-hoc basis by an analyst, the real benefits come from automating the rCA AI analysis as part of an IoT process. The rCA function can be executed based on trigger events such as data changes or exceptions. The rCA algorithms are embedded in the functions library of the XMPro IoT Process platform.
This approach has led to an area of causal research from a dynamical systems perspective. A dynamical system is one in which a function describes the time dependence of a point in a geometrical space. 27 28 29 30 A dynamical systems course at Harvard states that the methods have a focus on the behavior of systems described by ordinary differential equations. Application areas“… are diverse and multidisciplinary, ranging over areas of applied science and engineering, including biology, chemistry, physics, finance, and
27 https:// en. wikipedia. org / wiki / Dynamical _ system
28 https:// en. wikipedia. org / wiki / Dynamical _ systems _ theory
29 https:// mathinsight. org / dynamical _ system _ idea
30 http:// math. huji. ac. il /~ mhochman / research-expo. html
31 https:// scholar. harvard. edu / siams / am-147-nonlinear-dynamical-systems
IIC Journal of Innovation- 11-