scholarly journals Post Disaster Situation Awareness and Decision Support Through Interactive Crowdsourcing

2016 ◽  
Vol 159 ◽  
pp. 167-173 ◽  
Author(s):  
Moumita Basu ◽  
Somprakash Bandyopadhyay ◽  
Saptarshi Ghosh
Keyword(s):  
Decision Support ◽  
Situation Awareness ◽  
Disaster Situation ◽  
Post Disaster

Models of decision support in socio-cyber-physical systems

2019 ◽  
pp. 55-70 ◽  
Author(s):  
A. V. Smirnov ◽  
T. V. Levashova
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Situation Awareness ◽  
Cyber Physical Systems ◽  
Emergent Behavior ◽  
Emergent Properties ◽  
Decision Making Process ◽  
Physical Systems ◽  
Decision Support Models ◽  
Common Goals

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.

scholarly journals A Decision-support Tool for Post-disaster Debris Operations

2015 ◽  
Vol 107 ◽  
pp. 154-167 ◽  
Author(s):  
Álvaro Lorca ◽  
Melih Çelik ◽  
Özlem Ergun ◽  
Pınar Keskinocak
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Support Tool ◽  
Disaster Debris ◽  
Post Disaster

Citizen-to-Citizen Resource Sharing in Emergency Response

Crowdsourcing ◽  
2019 ◽  
pp. 578-605
Author(s):  
Soon Ae Chun ◽  
Jaideep S. Vaidya ◽  
Vijayalakshmi Atluri ◽  
Basit Shafiq ◽  
Nabil R. Adam
Keyword(s):  
Citizen Participation ◽  
Emergency Response ◽  
Situation Awareness ◽  
Resource Sharing ◽  
Large Scale ◽  
Situational Awareness ◽  
Government Agencies ◽  
Mobile Crowdsourcing ◽  
Disaster Situation ◽  
The Government

During large-scale manmade or natural disasters, such as Superstorm Sandy and Hurricanes Harvey and Irma, collaborations among government agencies, NGOs, and businesses need to be coordinated to provide necessary resources to respond to emergency events. However, resources from citizens themselves are underutilized, such as their equipment or expertise. The citizen participation via social media enhanced the situational awareness, but the response management is still mainly handled by the government or government-sanctioned partners. By harnessing the power of citizen crowdsourcing, government agencies can create enhanced disaster situation awareness and facilitate effective utilization of resources provided by citizen volunteers, resulting in more effective disaster responses. This chapter presents a public engagement in emergency response (PEER) framework that provides an online and mobile crowdsourcing platform for incident reporting and citizens' resource volunteering as well as an intelligent recommender system to match-make citizen resources with emergency tasks.

Citizen-to-Citizen Resource Sharing in Emergency Response

2018 ◽  
pp. 130-164 ◽  
Author(s):  
Soon Ae Chun ◽  
Jaideep S. Vaidya ◽  
Vijayalakshmi Atluri ◽  
Basit Shafiq ◽  
Nabil R. Adam
Keyword(s):  
Citizen Participation ◽  
Emergency Response ◽  
Situation Awareness ◽  
Resource Sharing ◽  
Large Scale ◽  
Situational Awareness ◽  
Government Agencies ◽  
Mobile Crowdsourcing ◽  
Disaster Situation ◽  
The Government

During large-scale manmade or natural disasters, such as Superstorm Sandy and Hurricanes Harvey and Irma, collaborations among government agencies, NGOs, and businesses need to be coordinated to provide necessary resources to respond to emergency events. However, resources from citizens themselves are underutilized, such as their equipment or expertise. The citizen participation via social media enhanced the situational awareness, but the response management is still mainly handled by the government or government-sanctioned partners. By harnessing the power of citizen crowdsourcing, government agencies can create enhanced disaster situation awareness and facilitate effective utilization of resources provided by citizen volunteers, resulting in more effective disaster responses. This chapter presents a public engagement in emergency response (PEER) framework that provides an online and mobile crowdsourcing platform for incident reporting and citizens' resource volunteering as well as an intelligent recommender system to match-make citizen resources with emergency tasks.

A Comparison of Alternatives for Automated Decision Support in a Multi-Task Environment

1997 ◽  
Vol 41 (1) ◽  
pp. 190-194 ◽  
Author(s):  
Jean MacMillan ◽  
Stephen E. Deutsch ◽  
Michael J. Young
Keyword(s):  
Decision Support ◽  
Situation Awareness ◽  
Traffic Control ◽  
Work Environments ◽  
Task Environment ◽  
Control Environment ◽  
Task Management ◽  
The Status ◽  
Effective Decision ◽  
Effective Decision Support

Complex, multi-task work environments that require humans to “juggle” many simultaneous tasks are becoming more widespread. How can automated capabilities best support the operator in these environments? We grouped the cognitive workload associated with multi-task management into two broad areas: 1) creating, maintaining, and updating an awareness of the status of all of the active tasks, and 2) choosing actions from among these active tasks based on overall goals. We then developed automated decision support for each of these aspects of workload and assessed which type of support was more effective in improving performance. Our findings indicate that, in a simulated air traffic control environment, the effort associated with creating and maintaining situation awareness was overwhelmingly responsible for the operator's workload. The results suggest that effective decision support in this environment should focus on helping the operator maintain awareness of the changing status of the active tasks, not on setting priorities or choosing among alternative tasks.

Impact of Blue Force Tracking on Combat Identification Judgments

2012 ◽  
Vol 55 (1) ◽  
pp. 75-89 ◽  
Author(s):  
David J. Bryant ◽  
David G. Smith
Keyword(s):  
Decision Support ◽  
Situation Awareness ◽  
Performance Standards ◽  
Positional Information ◽  
False Alarms ◽  
Time Data ◽  
Position Information ◽  
Person Perspective ◽  
Force Tracking ◽  
Gaming Environment

Objective: We examined the effectiveness of blue force tracking (BFT) decision support for dismounted infantry soldiers. Background: Technologies to support combat identification (CID) are rapidly evolving and may be deployable to dismounted soldiers in the future. BFT systems are designed to mitigate the risk of fratricide by supplying positional information regarding friendly units to enhance situation awareness. Method: Participants played the role of a dismounted infantry soldier in a first-person perspective gaming environment and made engagement decisions for a series of simulated targets, half of which were enemies and half of which were friends. Results: Participants performed better overall when they were able to use a BFT system than when they performed the task without assistance. When a 10-s latency was added to the updating of position information in the BFT, participants made significantly more false alarms (engaged a friendly target) regardless of whether they knew about the latency. Conclusion: The results indicate the promise of a personal BFT device to reduce the likelihood of fratricide by dismounted infantry soldiers. The results, however, also indicate that the effectiveness of such a device can be dramatically reduced when it does not provide real-time data. Application: Potential applications of this research include development of performance standards for BFT devices and assessment of decision support for dismounted soldiers.

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