Cognitive scenario generation computing in the Internet of things for enterprise information systems

ABSTRACT

This paper proposes an enhanced Bayesian probability-based method to generate high-quality scenarios using a small number of collected sensory data. Diverse kinds of new scenarios can be generated inexpensively using the proposed method, and these new scenarios have characteristics similar to the stochastic characteristics of manually collected datasets. The validity of this method was evaluated based on a real dataset. Experiments showed that the factor of the effect was 0.46351, indicating that the proposed method can generate scenarios that are highly consistent with real sensory big data.

KEYWORDS:

• Cognitive computing
• activity recognition
• probability computing
• scenario generation

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Dongguk University-Seoul [2017].