Co-Simulation of Cyber Physical Systems with HMI for Human in the Loop Investigation

2019 ◽  
Vol 47 ◽  
pp. 249-265 ◽  
Author(s):  
Christos Emmanouilidis ◽  
Petros Pistofidis ◽  
Luka Bertoncelj ◽  
Vassilis Katsouros ◽  
Apostolos Fournaris ◽  
...  

Computer ◽  
2012 ◽  
pp. 1-1 ◽  
Author(s):  
Gunar Schirner ◽  
D. Erdogmus ◽  
Kaushik Chowdhury ◽  
Taskin Padir

Author(s):  
Maya S. Luster ◽  
Brandon J. Pitts

The field of Cyber-Physical Systems (CPS) is increasingly recognizing the importance of integrating Human Factors for Human-in-the-loop CPS (HiLCPS) developments. This is because psychological, physiological, and behavioral characteristics of humans can be used to predict human-machine interactions. The goal of this pilot study is to collect initial data to determine whether driving and eye tracking metrics can provide evidence of learning for a CPS project. Six participants performed a series of 12 repeated obstacle avoidance tasks in manual driving. Lane deviations and fixation-related eye data were recorded for each trial. Overall, participants displayed either conservation/safe or aggressive/risky in their lateral position with respect to the obstacle during successive trials. Also, eye tracking metrics were not significantly affected by trial number, but observational trends suggest their potential for aiding in understanding adjustments humans make in learning. Results can inform predictive modeling algorithms that can anticipate and mitigate potential problems in real-time.


2019 ◽  
Vol 130 ◽  
pp. 21-39 ◽  
Author(s):  
Miriam Gil ◽  
Manoli Albert ◽  
Joan Fons ◽  
Vicente Pelechano

Telecom ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 18-31
Author(s):  
Soraya Sinche ◽  
Pablo Hidalgo ◽  
José Fernandes ◽  
Duarte Raposo ◽  
Jorge Silva ◽  
...  

Is it possible to analyze student academic performance using Human-in-the-Loop Cyber-Physical Systems (HiLCPS) and offering personalized learning methodologies? Taking advantage of the Internet of Things (IoT) and mobile phone sensors, this article presents a system that can be used to adapt pedagogical methodologies and to improve academic performance. Thus, in this domain, the present work shows a system capable of analyzing student behavior and the correlation with their academic performance. Our system is composed of an IoT application named ISABELA and a set of open-source technologies provided by the FIWARE Project. The analysis of student performance was done through the collection of data, during 30 days, from a group of Ecuadorian university students at “Escuela Politécnica Nacional” in Quito, Ecuador. Data gathering was carried out during the first period of classes using the students’ smartphones. In this analysis, we found a significant correlation between the students’ lifestyle and their academic performance according to certain parameters, such as the time spent on the university campus, the students’ sociability, and physical activity, etc.


Sign in / Sign up

Export Citation Format

Share Document