Abstract
A wide methodological spectrum regarding future research is offered by anticipation studies, with a special role of foresight studies. Many studies of this type focus on generating the desired future, taking into account the fact that it is accompanied by uncertainty. The author of this publication postulates treating uncertainty as an equivalent—in relation to the future—research object. This approach allows us to formulate general assumptions for a model of the anticipatory management of systemic uncertainty in IoT networks. The goal of such a model will not be to eliminate or even minimize uncertainty, but to regulate it to a desired level. Such an action can bring many more benefits than trying to zero out uncertainty. On the general side, uncertainty can be studied in two ways: (1) as an abstract idea, or (2) as a feature of a particular structure, also with elements of research on its abstract component. In this paper the attention is focused on the second approach. The main research area is the IoT network in its broadest sense, with a particular role of the social construct, in the context of the study of systemic uncertainty in relation to selected anticipatory actions. The overarching goal is to define a desired state, or to determine what such a desired state is, of anticipatory IoT uncertainty.
Highlights
IntroductionA complex system is a system with multiple parts interacting, usually on a feedback basis, and affecting the subsequent new properties and behaviors of that system
Anticipatory Foresight Perspective.Currently, the importance of the complex systems paradigm is a growing phenomenon.In the traditional view, a complex system is a system with multiple parts interacting, usually on a feedback basis, and affecting the subsequent new properties and behaviors of that system
The main research object in this paper is the systemic uncertainty of the complex Internet of Things (IoT) sensor network as a subsystem of Industry 4.0 [2]
Summary
A complex system is a system with multiple parts interacting, usually on a feedback basis, and affecting the subsequent new properties and behaviors of that system. Such a system has an important component in the form of unavoidable uncertainty conditioned by the following reasons: (1) the inability to measure the initial conditions of the system with infinite precision [1], (2) the difficulty of determining the ideal/expected value of such a system, and (3) the difficulty of accurately determining the future state of the system. The unknown nature of the future introduces the study of uncertainty as a possible research topic for different technologies (in addition to ambiguity and ignorance) in the areas of foresight and anticipation [3]
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