AFFECTIVE COMPUTING AND AUGMENTED REALITY FOR CAR DRIVING SIMULATORS

Car simulators are essential for training and for analyzing the behavior, the responses and the performance of the driver. Augmented Reality (AR) is the technology that enables virtual images to be overlaid on views of the real world. Affective Computing (AC) is the technology that helps reading emotions by means of computer systems, by analyzing body gestures, facial expressions, speech and physiological signals. The key aspect of the research relies on investigating novel interfaces that help building situational awareness and emotional awareness, to enable affect-driven remote collaboration in AR for car driving simulators. The problem addressed relates to the question about how to build situational awareness (using AR technology) and emotional awareness (by AC technology), and how to integrate these two distinct technologies [4], into a unique affective framework for training, in a car driving simulator

Public Awareness and Education for Flooding Disasters

In recent years, dramatic river flooding occurred in the city of Prague causing the raising of the river water level more than 8 m and the inundation of the lower parts of the city. The disaster resulted in numerous casualties and damages of buildings and infrastructures. Prior disaster analysis showed that the city was not well prepared for facing the disasters. A digital training could be a powerful tool for increasing knowledge and awareness of the citizens and providing training facilities about response to such disasters. A special Massive Open Online Course (MOOC), therefore, has been developed focused on flooding in Prague offering educational material in crisis flooding. Dedicated technologies have been developed such as a flooding alert and a nonverbal communication language based on icons. The MOOC enables participants to train the new technologies. Participants can also play roles in the crisis management team to increase the sensitivity of the complexity of a flooding crisis and its measurements. The first prototype of the MOOC was tested on a group of students of the Technical Universities of Prague and Delft. The test results will be reported

Crisis Management Using Multiple Camera Surveillance Systems

ABSTRACT During recent disasters such as tsunami, flooding, hurricanes, nuclear disaster, earthquake people have to leave their living areas for their own safety. But it proves that some people are not informed about the evacuation, or are not willing or able to leave or don't know how to leave the hazardous areas. The topic of the paper is how to adapt current video surveillance systems along highway and streets to semi-automatic surveillance systems. When a suspicious event is detected a human operator in the control room has to be alerted to take appropriate actions. The architecture of the system and main modules are presented in the paper. Different algorithms to detect localize and track people are published by the authors elsewhere but are summarized in the current paper. The system has been tested in a real life environment and the test results are presented in the paper