Virtual training system development to measure performance and professional behavior of public and private security area

Abstract

Development of a corporate education technology platform using Virtual Reality, IoT (Internet of Things) and analytical algorithms for the engagement, training and behavioral analysis of private and public security professionals. The purpose is to identify when a company employee is able or not to work in a certain field operational activity. Often companies invest in training for their employees to be able to act in an adequate way in their daily life, however, the vast majority of the training is timely and there is no continuity to know if the professional is engaged or with the correct attitudes to the field operations. Often, he may be going through a period of stress and dispersion, and therefore, not being able to properly perform his activities.It is crucial to know if the employee is in a stress phase, or even starting a depressive symptom. And how he reacts to a situation that requires his attitude. With this the company is able to suggest the best placement of the professional within the framework of operational activities that it operates. The system allows a large volume of professionals to be trained continuously in specific practical situations (shopping, hotel, airport, hospitals, transport of values, etc.) at low cost. For example, with the use of the mobile simulator, proposed in this project, it is possible to train the collaborator anywhere and at any time, avoiding to remove him from the stations and the field operation. It is also a way of promoting the personalization of the learning of each collaborator following its level of evolution. In addition, it is possible to train security techniques such as OMD (Observe, Memorize, Describe) and IDA (Identify, Decide, Act) in a scalable way. In the market intelligence study, he found that training for operational activities is time consuming and very theoretical. It is not able to sensitize the profile of the professionals that in the great majority are not adapted to the traditional learning (expositive class, reading, etc.).One of the hallmarks of the solution lies in integrating the technologies of Virtual Reality, IoT and analytical algorithms with an active educational methodology, called PBL (Problem Based Learning) and with the personalization of learning. This platform allows the professional to take a more active stance, in which he solves problems and builds his own knowledge. Another innovation is the use of physiological data to compose the information that will allow an analysis of the attitude of each professional through machine learning algorithms. Simulated training will stimulate the practitioner's attitudes and reactions, and the readings of physiological data along with the other results of this training will allow building a profile of each practitioner's performance and behavior.The technology platform is composed of four parts that communicate via 3G / 4G / Wi-Fi communication to allow training data, both with TIS MB (mobile simulator) and TIS VR (standard simulator), to be sent and stored on the cloud computing platform (InfoTIS). In addition, there are physiological data (heart rate) obtained from the professional during the training sessions (biofeedback) that are also sent to InfoTIS. With this set of data it is possible to perform the performance and behavior measurement of each professional generating certain outputs of information that can aid in decisions involving the professional that goes from his level of engagement, through recognition, and can even reach in the repositioning of their attributions, among others. (AU)