Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929582
Nicolas Primeau, R. Abielmona, R. Falcon, E. Petriu
With the rise of more resourceful unmanned aerial vehicles (UAVs), their inclusion into robotic sensor networks (RSNs) is inevitable. The highly mobile nature of UAVs allows greater monitoring capabilities, making them most suitable for RSNs. Compared to traditional nodes in RSNs, UAVs suffer even more from communication disruptions and energy depletion, must often rapidly determine actions for themselves, and consequently require more autonomy. Prior work has been done in wireless sensor network (WSN)/aerial sensor network (ASN) coordination in a few applications such as protecting critical infrastructure, restoring communication between nodes, and healing networks, while other work has been accomplished on using the UAV network for augmenting the monitoring capabilities of WSNs. We introduce a novel methodology to integrate UAVs into RSNs for monitoring purposes by formulating the problem in the context of a risk management framework (RMF). This methodology allows a more precise risk feature classification and a more efficient task allocation for the ground network by utilizing the monitoring capabilities of the UAVs to informatively warn the RSN of any incoming events. We also present a fictitious but credible maritime smuggling scenario near the Port of Barcelona based on expert knowledge, and apply the methodology to detect and mitigate maritime smuggling. The network's behaviour is traced throughout the scenario and is repeated with civilian ships to assure that they are not flagged as smugglers. The applied methodology results in a successful classification and mitigation of the smuggling activity.
{"title":"Maritime smuggling detection and mitigation using risk-aware hybrid robotic sensor networks","authors":"Nicolas Primeau, R. Abielmona, R. Falcon, E. Petriu","doi":"10.1109/COGSIMA.2017.7929582","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929582","url":null,"abstract":"With the rise of more resourceful unmanned aerial vehicles (UAVs), their inclusion into robotic sensor networks (RSNs) is inevitable. The highly mobile nature of UAVs allows greater monitoring capabilities, making them most suitable for RSNs. Compared to traditional nodes in RSNs, UAVs suffer even more from communication disruptions and energy depletion, must often rapidly determine actions for themselves, and consequently require more autonomy. Prior work has been done in wireless sensor network (WSN)/aerial sensor network (ASN) coordination in a few applications such as protecting critical infrastructure, restoring communication between nodes, and healing networks, while other work has been accomplished on using the UAV network for augmenting the monitoring capabilities of WSNs. We introduce a novel methodology to integrate UAVs into RSNs for monitoring purposes by formulating the problem in the context of a risk management framework (RMF). This methodology allows a more precise risk feature classification and a more efficient task allocation for the ground network by utilizing the monitoring capabilities of the UAVs to informatively warn the RSN of any incoming events. We also present a fictitious but credible maritime smuggling scenario near the Port of Barcelona based on expert knowledge, and apply the methodology to detect and mitigate maritime smuggling. The network's behaviour is traced throughout the scenario and is repeated with civilian ships to assure that they are not flagged as smugglers. The applied methodology results in a successful classification and mitigation of the smuggling activity.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114455874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929606
C. Azevedo, K. Raizer, Ricardo S. Souza
Human-machine interactions are likely to require synergistic multidisciplinary research efforts for supporting a paradigm shift towards collaborative-oriented use cases. An essential aspect of collaboration is trust and in order to establish it there is need for human-machine mutual understanding (HMMU). We argue that achieving HMMU will require evolving from an approach that reduces human factors as uncontrollable environmental elements, to one that repositions human emotions not only as a central part of an integrated control paradigm, but also as interpretable and steerable through appropriate information flows and mutual learning cycles. On the strategic decision-making side, we argue conflict resolution will require anticipating multiple trade-off situations that include human factors. On the operational level, symbiotic human-machine cognitive architectures should embed detected human emotions as inputs in shared machine control models. Trust measurements will play the role of mediating task coordination by pinpointing and dynamically composing appropriate situation-aware interaction protocols. In addition to a vision for HMMU, this paper proposes a multidisciplinary research strategy that attempts to unify the isolated efforts of different communities. The proposed vision is contextualized within a high-level research roadmap to support near and long-term activities in HMMU.
{"title":"A vision for human-machine mutual understanding, trust establishment, and collaboration","authors":"C. Azevedo, K. Raizer, Ricardo S. Souza","doi":"10.1109/COGSIMA.2017.7929606","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929606","url":null,"abstract":"Human-machine interactions are likely to require synergistic multidisciplinary research efforts for supporting a paradigm shift towards collaborative-oriented use cases. An essential aspect of collaboration is trust and in order to establish it there is need for human-machine mutual understanding (HMMU). We argue that achieving HMMU will require evolving from an approach that reduces human factors as uncontrollable environmental elements, to one that repositions human emotions not only as a central part of an integrated control paradigm, but also as interpretable and steerable through appropriate information flows and mutual learning cycles. On the strategic decision-making side, we argue conflict resolution will require anticipating multiple trade-off situations that include human factors. On the operational level, symbiotic human-machine cognitive architectures should embed detected human emotions as inputs in shared machine control models. Trust measurements will play the role of mediating task coordination by pinpointing and dynamically composing appropriate situation-aware interaction protocols. In addition to a vision for HMMU, this paper proposes a multidisciplinary research strategy that attempts to unify the isolated efforts of different communities. The proposed vision is contextualized within a high-level research roadmap to support near and long-term activities in HMMU.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128510883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929594
Stephen L. Dorton, Micah Thirey
Complexity is concept that is typically used to describe the size or composition of a system and its constituent components. The cybernetics community has long recognized the need for complexity, understanding that only the variety of a system can destroy the variety of the environment and inputs to the system. Conversely, the applied psychology and decision making communities generally acknowledge that increased complexity degrades decision making performance in dynamic tasks through several mechanisms. A notional model of “Effective Variety” is discussed, which states that there is an optimal level or range of complexity for any human-machine interface that will facilitate optimal dynamic decision making performance in a human-machine team. This initial paper discusses a concept and model of Effective Variety, and focuses specifically on how interface complexity affects Situation Awareness (an antecedent to decision making performance), and areas for future research into such a theory.
{"title":"Effective Variety? for whom (or what)? A folk theory on interface complexity and situation awareness","authors":"Stephen L. Dorton, Micah Thirey","doi":"10.1109/COGSIMA.2017.7929594","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929594","url":null,"abstract":"Complexity is concept that is typically used to describe the size or composition of a system and its constituent components. The cybernetics community has long recognized the need for complexity, understanding that only the variety of a system can destroy the variety of the environment and inputs to the system. Conversely, the applied psychology and decision making communities generally acknowledge that increased complexity degrades decision making performance in dynamic tasks through several mechanisms. A notional model of “Effective Variety” is discussed, which states that there is an optimal level or range of complexity for any human-machine interface that will facilitate optimal dynamic decision making performance in a human-machine team. This initial paper discusses a concept and model of Effective Variety, and focuses specifically on how interface complexity affects Situation Awareness (an antecedent to decision making performance), and areas for future research into such a theory.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129818537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929608
Bruce J. P. Mortimer, L. Elliott
Human-robot teams can incorporate advanced technology such as distributed mobile sensor networks, integrated communications, visualization technology, and other means to acquire and assess information. These factors can greatly affect mission effectiveness, safety, and survivability, by providing critical information and suggesting courses of action. However, information overload can result. Tactical situation awareness (SA) can be improved if human-robot communications are prioritized according to importance and appropriateness for single or multi-sensory display. In this paradigm, the tasks of the human and robot are somewhat independent or autonomous, but complimentary. Handling the amount, frequency and transfer of information, from the robot to the user requires a careful systems approach, an understanding of the mission context, and multisensory information processing issues. This report highlights attention management issues identified during task reengagement and offers guidelines relevant to tactile cues within multisensory bidirectional human robot communications.
{"title":"Information transfer within human robot teams: Multimodal attention management in human-robot interaction","authors":"Bruce J. P. Mortimer, L. Elliott","doi":"10.1109/COGSIMA.2017.7929608","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929608","url":null,"abstract":"Human-robot teams can incorporate advanced technology such as distributed mobile sensor networks, integrated communications, visualization technology, and other means to acquire and assess information. These factors can greatly affect mission effectiveness, safety, and survivability, by providing critical information and suggesting courses of action. However, information overload can result. Tactical situation awareness (SA) can be improved if human-robot communications are prioritized according to importance and appropriateness for single or multi-sensory display. In this paradigm, the tasks of the human and robot are somewhat independent or autonomous, but complimentary. Handling the amount, frequency and transfer of information, from the robot to the user requires a careful systems approach, an understanding of the mission context, and multisensory information processing issues. This report highlights attention management issues identified during task reengagement and offers guidelines relevant to tactile cues within multisensory bidirectional human robot communications.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121564136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929602
Michael P. Jenkins, D. Duggan, A. Negri
The Connected Vehicles program is a multimodal US Department of Transportation (USDOT) initiative that enables safer, smarter, and greener surface transportation using dedicated wireless communication technology. Although significant efforts are being made to bring motor vehicles and transportation infrastructure onto this connected network, bicycles have been largely overlooked. Bringing cyclists onto this network will enable other connected vehicles and infrastructure to be aware of their presence, and allow cyclists to take advantage of the safety and transportation benefits of receiving information from other connected entities. To connect bicycles, we are designing a prototype Multimodal Alerting Interface with Networked Short-Range Transmissions (MAIN-ST). MAIN-ST brings cyclists onto the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) networks to enable a suite of safe cycling capabilities. This paper describes our progress accomplished over a 6-month period, and documents the feasibility of the MAIN-ST technology approach.
{"title":"Towards a connected bicycle to communicate with vehicles and infrastructure : Multimodel alerting interface with Networked Short-Range Transmissions (MAIN-ST)","authors":"Michael P. Jenkins, D. Duggan, A. Negri","doi":"10.1109/COGSIMA.2017.7929602","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929602","url":null,"abstract":"The Connected Vehicles program is a multimodal US Department of Transportation (USDOT) initiative that enables safer, smarter, and greener surface transportation using dedicated wireless communication technology. Although significant efforts are being made to bring motor vehicles and transportation infrastructure onto this connected network, bicycles have been largely overlooked. Bringing cyclists onto this network will enable other connected vehicles and infrastructure to be aware of their presence, and allow cyclists to take advantage of the safety and transportation benefits of receiving information from other connected entities. To connect bicycles, we are designing a prototype Multimodal Alerting Interface with Networked Short-Range Transmissions (MAIN-ST). MAIN-ST brings cyclists onto the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) networks to enable a suite of safe cycling capabilities. This paper describes our progress accomplished over a 6-month period, and documents the feasibility of the MAIN-ST technology approach.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123332029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929598
Kellie L. Turner, Michael E. Miller
Increasingly complex contested environments force analysts to combine many different types of intelligence data to form a more cohesive picture of the environment. Information fusion systems include computers that integrate and synthesize information from multiple sources and humans who combine that information with reasoning abilities and knowledge of past events to assess situations and predict future states. The intent of this paper is to highlight the importance of understanding human cognition and decision making by presenting the hypotheses of our current research. The purpose of the future study described in this paper is to investigate how the degree of information acquisition automation used affects the human's ability to detect patterns in data that may be needed to reach higher levels of information fusion. This study will use a 2 (task type: intuitive, analytic) × 3 (amount of automation: none, half, all), between subjects experimental design. We expect to find a significant interaction between task type and amount of automation. For tasks that induce the human's intuitive system, increasing automation is expected to disrupt the human's ability to recognize patterns. However, for tasks that induce the human's analytic system, increasing automation is expected to improve the human's ability to discern patterns. The results of this research can inform guidelines for the design of common workspaces to support human-machine teaming in future information fusion systems.
{"title":"The effect of automation and workspace design on humans' ability to recognize patterns while fusing information","authors":"Kellie L. Turner, Michael E. Miller","doi":"10.1109/COGSIMA.2017.7929598","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929598","url":null,"abstract":"Increasingly complex contested environments force analysts to combine many different types of intelligence data to form a more cohesive picture of the environment. Information fusion systems include computers that integrate and synthesize information from multiple sources and humans who combine that information with reasoning abilities and knowledge of past events to assess situations and predict future states. The intent of this paper is to highlight the importance of understanding human cognition and decision making by presenting the hypotheses of our current research. The purpose of the future study described in this paper is to investigate how the degree of information acquisition automation used affects the human's ability to detect patterns in data that may be needed to reach higher levels of information fusion. This study will use a 2 (task type: intuitive, analytic) × 3 (amount of automation: none, half, all), between subjects experimental design. We expect to find a significant interaction between task type and amount of automation. For tasks that induce the human's intuitive system, increasing automation is expected to disrupt the human's ability to recognize patterns. However, for tasks that induce the human's analytic system, increasing automation is expected to improve the human's ability to discern patterns. The results of this research can inform guidelines for the design of common workspaces to support human-machine teaming in future information fusion systems.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114452710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929591
A. Smirnov, N. Shilov, O. Gusikhin
Cyber-physical-human systems find new applications in various areas of human lives. The paper proposes usage of a system of this class to achieve a synergy between the connected car and e-tourism ideas. The developed approach is presented with more attention paid to the situational awareness and behavioral awareness. The approach is illustrated via a case study aimed to organization of infomobile support of tourists taking a ride in a car with a driver. The connected car technologies are used to integrate car information system with tourist's personal information device to deliver speech, image and video-based tour guiding synchronized with the ride.
{"title":"Cyber-physical-human system for connected car-based e-tourism : Approach and case study scenario","authors":"A. Smirnov, N. Shilov, O. Gusikhin","doi":"10.1109/COGSIMA.2017.7929591","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929591","url":null,"abstract":"Cyber-physical-human systems find new applications in various areas of human lives. The paper proposes usage of a system of this class to achieve a synergy between the connected car and e-tourism ideas. The developed approach is presented with more attention paid to the situational awareness and behavioral awareness. The approach is illustrated via a case study aimed to organization of infomobile support of tourists taking a ride in a car with a driver. The connected car technologies are used to integrate car information system with tourist's personal information device to deliver speech, image and video-based tour guiding synchronized with the ride.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117300056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929588
Arezoo Sarkheyli-Hägele, D. Söffker
Situation recognition is a significant part of supervision to advance human operator decision making. It is a process for identification of occurred situations as the result of a sequence of actions. Situation recognition process could be individualized for an assistance system by considering exclusive behaviors of human operators individually. Accordingly, the assistance system should be provided with an online learning process to explore new experiences by modeling and labeling the occurred situations and adapt the knowledge base. In this paper, an improved Case-Based Reasoning (CBR) approach is proposed and applied for lane-change driving situation recognition. The proposed CBR is able to model event-discrete situations using Situation-Operator Modeling (SOM) approach. In addition, human operator experiences are learned online and reused for situation recognition by integration of fuzzy logic. Additional processes need to be carried out in the proposed fuzzy-SOM based CBR to support online learning for data reduction and knowledge indexing. As an experiment, the proposed approach is implemented to recognize lane-change situations for a driving assistance system. According to fundamental evaluation results, the proposed approach is able to improve lane-change situations recognition performance for individual human operators.
{"title":"Online learning for an individualized lane-change situation recognition system applied to driving assistance","authors":"Arezoo Sarkheyli-Hägele, D. Söffker","doi":"10.1109/COGSIMA.2017.7929588","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929588","url":null,"abstract":"Situation recognition is a significant part of supervision to advance human operator decision making. It is a process for identification of occurred situations as the result of a sequence of actions. Situation recognition process could be individualized for an assistance system by considering exclusive behaviors of human operators individually. Accordingly, the assistance system should be provided with an online learning process to explore new experiences by modeling and labeling the occurred situations and adapt the knowledge base. In this paper, an improved Case-Based Reasoning (CBR) approach is proposed and applied for lane-change driving situation recognition. The proposed CBR is able to model event-discrete situations using Situation-Operator Modeling (SOM) approach. In addition, human operator experiences are learned online and reused for situation recognition by integration of fuzzy logic. Additional processes need to be carried out in the proposed fuzzy-SOM based CBR to support online learning for data reduction and knowledge indexing. As an experiment, the proposed approach is implemented to recognize lane-change situations for a driving assistance system. According to fundamental evaluation results, the proposed approach is able to improve lane-change situations recognition performance for individual human operators.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133912650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929585
M. J. Bentley, Alan C. Lin, D. Hodson
US Air Force satellite ground stations require significant manpower to operate. To improve operating efficiencies, the Air Force seeks to incorporate more automation into routine satellite operations. Interaction with autonomous systems includes not only daily operations, but also the development, maintainability, and the extensibility of such systems. This paper presents challenges to Air Force satellite automation: 1) existing architecture of legacy systems, 2) space segment diversity, and 3) unclear definition and scoping of the term “automation.” Using a qualitative case study approach, we survey comparable non-satellite operation domains (Industrial Control Automation and Software Testing) that have successfully integrated automation, and other satellite operation enterprises (NASA Goddard, Naval Research Laboratory, European Ground Station National Institute for Space Research in Brazil) to identify common themes and best practices. From this insight, we recommend that future satellite operation ground stations encourage the use of layered architectures, abstract satellite operation processes, and integrate simulators in future systems as concrete implementations of this common operating platform.
{"title":"Overcoming challenges to air force satellite ground control automation","authors":"M. J. Bentley, Alan C. Lin, D. Hodson","doi":"10.1109/COGSIMA.2017.7929585","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929585","url":null,"abstract":"US Air Force satellite ground stations require significant manpower to operate. To improve operating efficiencies, the Air Force seeks to incorporate more automation into routine satellite operations. Interaction with autonomous systems includes not only daily operations, but also the development, maintainability, and the extensibility of such systems. This paper presents challenges to Air Force satellite automation: 1) existing architecture of legacy systems, 2) space segment diversity, and 3) unclear definition and scoping of the term “automation.” Using a qualitative case study approach, we survey comparable non-satellite operation domains (Industrial Control Automation and Software Testing) that have successfully integrated automation, and other satellite operation enterprises (NASA Goddard, Naval Research Laboratory, European Ground Station National Institute for Space Research in Brazil) to identify common themes and best practices. From this insight, we recommend that future satellite operation ground stations encourage the use of layered architectures, abstract satellite operation processes, and integrate simulators in future systems as concrete implementations of this common operating platform.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116349353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/COGSIMA.2017.7929583
Alex Plachkov, V. Groza, D. Inkpen, E. Petriu, R. Abielmona, M. Harb, R. Falcon
Enhanced Course of Action (CoA) generation is a fundamental component of effective risk management and mitigation. This paper presents an extension of a system capable of integrating physics-based (hard) and people-generated (soft) data, for the purpose of achieving increased situational assessment and automatic CoA generation upon risk identification. The system's capabilities are enhanced through added support for managing multiple, concurrently unfolding risky events (situations) with the goal of attaining superior resource management and thus reducing the overall security operation costs. The CoA generation process is evaluated through a series of performance measures. The proposed conceptualization is validated via an elaborate experiment situated in the maritime world.
{"title":"Soft-data-driven resource management for concurrent maritime security operations","authors":"Alex Plachkov, V. Groza, D. Inkpen, E. Petriu, R. Abielmona, M. Harb, R. Falcon","doi":"10.1109/COGSIMA.2017.7929583","DOIUrl":"https://doi.org/10.1109/COGSIMA.2017.7929583","url":null,"abstract":"Enhanced Course of Action (CoA) generation is a fundamental component of effective risk management and mitigation. This paper presents an extension of a system capable of integrating physics-based (hard) and people-generated (soft) data, for the purpose of achieving increased situational assessment and automatic CoA generation upon risk identification. The system's capabilities are enhanced through added support for managing multiple, concurrently unfolding risky events (situations) with the goal of attaining superior resource management and thus reducing the overall security operation costs. The CoA generation process is evaluated through a series of performance measures. The proposed conceptualization is validated via an elaborate experiment situated in the maritime world.","PeriodicalId":252066,"journal":{"name":"2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124973898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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