K-Means Clustering-Based Safety System in Large-Scale Industrial Site Using Industrial Wireless Sensor Networks

Abstract

A large number of workers and heavy equipment are used in most industrial sizes, and the prevention of safety accidents is one of the most important issues. Therefore, although a number of systems have been proposed to prevent accidents, existing studies assume that workers are gathered in some areas. These assumptions are not suitable for large-scale industrial sites in which workers form as a group and work in a large area. In other words, in a large-scale industrial site, existing schemes are unsuitable for the timely notifying of warnings of threats, and excessive energy is consumed. Therefore, we propose a k-means clustering-based safety system for a large-scale industrial site. In the proposed scheme, workers deployed over a large area are divided into an appropriate number of groups, and threat notification is delivered by a multicasting tree toward each cluster. The notification to workers is delivered through local flooding in each cluster. The simulation results show that the system is able to deliver the notification within a valid time, and it is energy efficient compared to the existing scheme.

Construction of a Climate Early Warning System: Predicting Future Temperatures and Climate Security Using BiLSTM

“…The climate safety warning system can also indirectly reflect warnings for premature crop production or public health, making the construction of such a system necessary. Zhu (2021) et al utilized the K-means algorithm to establish a financial risk warning [25], and Seo (2022) et al applied the K-means algorithm to build an industrial safety warning system [26]. While some scholars in early warning systems use existing data or resources as warning indicators [19][20], others construct warning indicators through certain algorithms or other methods [25][26].…”

“…Zhu (2021) et al utilized the K-means algorithm to establish a financial risk warning [25], and Seo (2022) et al applied the K-means algorithm to build an industrial safety warning system [26]. While some scholars in early warning systems use existing data or resources as warning indicators [19][20], others construct warning indicators through certain algorithms or other methods [25][26]. In constructing the climate security warning system, this paper aims to create indicators that can be manipulated to enable adjustments in response to warnings.…”