Human safety in a man-made ecosystem

Abstract

The human health condition and operating capability depend on a variety of environmental factors. It is of great importance to perform studies addressing these factors and their influence on humans as it can help to form an optimal strategy in emergency situations and help humans to attain maximum performance. The best results are shown in studies performed in isolation in a man-made ecosystem because in this case environmental processes are defined and controlled. Man-made ecosystems include a life support system (LSS) combined with the environment and a key element-human. The research defines these three components as a complex system. This study is dedicated to interaction analysis and the human safety in this system, especially in case of emergencies. It includes supporting simulation models based on two types of experiments conducted by the researchers, namely the studies on the mean time to failure (MTF), and on human behavior during emergencies. The basic imitators of life support systems are complemented by additional environmental models where a human is represented as a loading element. To prevent hazards in low performance situations, the simulator used during the experiment, had a decision-making system, controlling environmental parameters and taking actions for the stabilization. It could also control the human condition, such as pulse, pressure, etc., during the entire operation. The results of the studies showed the dependency of human performance on fatigue, the time spent in isolation, as well as the emergencies. The methodology recommendations and safety requirements are discussed in the paper. The results of these studies were used in forming an information database for automated control system of the "artificial lungs" equipment.

Finding Pluto: An Analytics-Based Approach to Safety Data Ecosystems

“…This organizational shift can be seen as a shift from an individualized safety model (with data collection and analysis focusing on past incidents) to a focus on a workplace safety ecosystems model , with data collection and analysis that draws on a variety of data sources, including huge data repositories [ 6 , [25] , [26] , [27] ]. Some researchers refer to these two ways of thinking as “Safety I" and “Safety II.” [ 9 , 28 ] One such data repository, for example, is the data accumulated by smart devices and machines: the so-called Internet of Things [ 29 ].…”