scholarly journals Real-time Local Topic Extraction using Density-based Adaptive Spatiotemporal Clustering for Enhancing Local Situation Awareness

2015 ◽  
Author(s):  
Tatsuhiro Sakai ◽  
Keiichi Tamura ◽  
Shota Kotozaki ◽  
Tsubasa Hayashida ◽  
Hajime Kitakami
Keyword(s):  
Real Time ◽  
Situation Awareness ◽  
Topic Extraction ◽  
Spatiotemporal Clustering

Detecting Pedestrian Situation Awareness in Real-Time: Algorithm Development Using Heart Rate Variability and Phone Position

2018 ◽  
Vol 62 (1) ◽  
pp. 1579-1583
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Yi Wang ◽  
Si Yang
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Real Time ◽  
Situation Awareness ◽  
Mental State ◽  
Time Algorithm ◽  
Support Vector ◽  
Vehicle Design ◽  
Automated Vehicle ◽  
Hrv Analysis

To help automated vehicles learn surrounding environments via V2X communications, it is important to detect and transfer pedestrian situation awareness to the related vehicles. Based on the characteristics of pedestrians, a real-time algorithm was developed to detect pedestrian situation awareness. In the study, the heart rate variability (HRV) and phone position were used to understand the mental state and distractions of pedestrians. The HRV analysis was used to detect the fatigue and alert state of the pedestrian, and the phone position was used to define the phone distractions of the pedestrian. A Support Vector Machine algorithm was used to classify the pedestrian’s mental state. The results indicated a good performance with 86% prediction accuracy. The developed algorithm shows high applicability to detect the pedestrian’s situation awareness in real-time, which would further extend our understanding on V2X employment and automated vehicle design.

scholarly journals WFMHT Method of Orbit Maneuver Detection Based on Space-Based Bearing-Only Measurement

2018 ◽  
Vol 36 (6) ◽  
pp. 1185-1192
Author(s):  
Lei Liu ◽  
Jianfeng Cao ◽  
Ye Liu
Keyword(s):  
Real Time ◽  
Situation Awareness ◽  
Detection System ◽  
Hypothesis Test ◽  
Test Methods ◽  
Time Motion ◽  
Weighted Fusion ◽  
Innovation Characteristics ◽  
Detection Window ◽  
Time Awareness

The method of orbit maneuver detection of space targets is investigated using the space-based bearing-only measurement, which aims to acquire a real-time or nearly real-time awareness of orbit maneuver in the space situation awareness. First, the model for estimating real-time motion of a space target is presented, which only uses the space-based bearing-only measurements. The innovation characteristics of the normal orbit and orbit maneuver are analyzed and compared. Second, based on the hypothesis test methods of the distribution characteristic of the stochastic sequence, the WFMHT (i.e., weighted fusion of multi hypothesis tests) method with the innovation is put forward to detect the orbit maneuver. Furthermore, the criterion of determining the weight coefficients is studied. Finally, the method is validated by numeric simulations. The results show that the highest gained success rate is up to 36% with the WFMHT method than the prevalent Chi2 method. With the WFMHT method, the detection system achieves a strengthened robustness with greatly shortened detection window. The research will be beneficial to construction of our space situation awareness system.

Detection of Primitive Collective Behaviours in a Crowd Panic Simulation Based on Multi-Agent Approach

2012 ◽  
Vol 3 (3) ◽  
pp. 50-65 ◽  
Author(s):  
Jérémy Patrix ◽  
Abdel-Illah Mouaddib ◽  
Sylvain Gatepaille
Keyword(s):  
Real Time ◽  
Situation Awareness ◽  
Hidden Markov ◽  
Extended Model ◽  
Multi Agent System ◽  
Complex Behaviour ◽  
Simulation Based ◽  
Fusion Methods ◽  
Multi Agent ◽  
Using Data

In case of emergency and evacuation, it is often impossible to interpret manually the complex behaviour of a crowd, essentially due to the lack of staff and time needed to understand a situation. In the literature, a monitored system using data fusion methods makes it possible to perform automatic situation awareness. Using Swarm Intelligence domain, the authors propose an approach based on multi-agent system to simulate and detect primitive collective behaviours emerging from a crowd panic. It enables anticipating collective behaviours in real-time as well as their anomalies according to specific scenarios. Detection is the possibility to learn, recognize and anticipate different behaviours by a probabilistic model. The collective behaviour detection of a crowd panic in real-time is based on a learning method on an extended model of Hidden Markov Model. This paper presents experiments of simulation and detection using an implementation of a virtual environment.

HomCam

2016 ◽  
Vol 60 (1) ◽  
pp. 800-804 ◽  
Author(s):  
Brian Peck ◽  
Stephen Gilbert ◽  
Eliot Winer ◽  
Robert C. Ray
Keyword(s):  
Real Time ◽  
Situation Awareness ◽  
Network Performance ◽  
Situational Awareness ◽  
Visual Display ◽  
Initial Test ◽  
Video System ◽  
Wearable Technologies ◽  
Remote Location ◽  
New Applications

The growth of mobile and wearable technologies has enabled a host of new applications, including remote situational awareness, in which a device worn by a remote partner can simulate being present in the remote location for an observer. We illustrate this idea by constructing the HomCam, a helmet-based omnidirectional video system that gives an observer the 360-degree perspective of a remote wearer. To our knowledge, the HomCam was the first wearable system that enabled real-time streaming of 360-degree video to a remote location built from commercial-of-the-shelf hardware. This paper describes related efforts, the HomCam prototype, its visual display, and an initial test of network performance. This prototype demonstrates some of the challenges of remote situation awareness and contributes to designers’ implementation of related systems.

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