Augmented Reality for Accident Analysis

Introduction

Around the world a large number of undesirable events, commonly called accidents, occur every year (Heidi, 2017; Schoijet, 1993; US-Chemical Safety & Hazard Investigation Board, 2007; Wadle, 2016; Rogers, 1986; Kunii, Akagi and Kita, 1995). These events have implications such as: injuries of all kinds, fatalities (in many cases tens, hundreds and thousands), infrastructure losses, economic losses, and negative impacts on the environment. After a detailed analysis of most of these events and the reflection about them, two aspects are obvious: the first is that they all have multiple causal factors and the second is that most are avoidable. There are many reasons why they are not avoided; But the main reason is the inability of individuals and organizations to learn from mistakes.

Likewise, most of the investigations that have been made in the area accidents prevention in different areas has been, under different to the systemic approaches; see for example, Fuboa, Kepinga and Xiaominga (2016); Cohen and Felson (1979); Thomas, Int Panis, and Vandenbulcke (2017); Felson and Clarke (1998); Kauker, Kaminski, Karcher, Dowdall, Brown, Hosseini and Strand. (2016); Cornish and Clarke (1986, 1998); Garbarino, Guglielmi, Sanna, Mancardi and Magnavita (2016); Clarke (1997); Clarke and Eck (2003); Townsley and Pease (2001); US (1997); Leight et to the. (1996, 1998); Read and Nick (1998), among others. Despite numerous studies and investigations that have been carried out on failures of systems (accidents); However, there is much evidence of an investigation on the development of methodologies and models for the analysis of accidents with augmented reality.

In this context, the knowledge can be obtained in several ways, but in the vast majority of cases, it is not possible to acquire all relevant information to the event (accident) which arises, so that it is almost never possible to eliminate all elements of uncertainty. In addition to the above, in all cases there is the limitation of the time in the decision-making process: the result is undoubtedly a distinction between correct and incorrect decisions. We can be classified as good or bad decision when you have the evaluation in hindsight.

In short, for decision-making, it is necessary to perform an analysis of the system involved. I.e., a process aimed at the orderly and timely acquisition, as well as the exploration of specific information from the system in a decision taken, i.e. having a learning through events that have occurred in the past.

Various investigations have been developed in use of augmented reality for the development of learning environments or improves these. Foster (2016) is developing a project to create a customizable application usable on a smart phone that implements a selective processing to make it easier for students with visual disabilities to participate and learn from the conferences. Giap, Yin, Hong and Ee (2016) proposed a learning environment with augmented reality for study and compression of the 4 course of biology matter in secondary schools in Malaysia using markers such as pointing devices, is a long-term study that aims to improve the perception and comprehension of students about the processes and phenomena in biology. The use of augmented reality in learning environments not only in classical topics in the development of students, for example, Orman, Price, and Russell (2017), raised the viability of using a learning environment to improve musical abilities.