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Using Observers for Model Based Data Collection in Distributed Tactical Operations
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
2008 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Modern information technology increases the use of computers in training systems as well as in command-and-control systems in military services and public-safety organizations. This computerization combined with new threats present a challenging complexity. Situational awareness in evolving distributed operations and follow-up in training systems depends on humans in the field reporting observations of events. The use of this observer-reported information can be largely improved by implementation of models supporting both reporting and computer representation of objects and phenomena in operations.

This thesis characterises and describes observer model-based data collection in distributed tactical operations, where multiple, dispersed units work to achieve common goals. Reconstruction and exploration of multimedia representations of operations is becoming an established means for supporting taskforce training. We explore how modelling of operational processes and entities can support observer data collection and increase information content in mission histories. We use realistic exercises for testing developed models, methods and tools for observer data collection and transfer results to live operations.

The main contribution of this thesis is the systematic description of the model-based approach to using observers for data collection. Methodological aspects in using humans to collect data to be used in information systems, and also modelling aspects for phenomena occurring in emergency response and communication areas contribute to the body of research. We describe a general methodology for using human observers to collect adequate data for use in information systems. In addition, we describe methods and tools to collect data on the chain of medical attendance in emergency response exercises, and on command-and-control processes in several domains.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2008. , 75 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1386
Keyword [en]
Observers, model-based data collection, distributed tactical operations, taskforce training, communication analysis, reconstruction & exploration, extended link analysis, timed checkpoints, network based observer tool
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-15620Local ID: LiU-Tek-Lic-2008:44ISBN: 978-91-7393-751-1 (print)OAI: oai:DiVA.org:liu-15620DiVA: diva2:126777
Presentation
2008-12-18, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (Swedish)
Opponent
Supervisors
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2009-05-15Bibliographically approved
List of papers
1. Monitoring and Visualisation Support for Management of Medical Resources in Mass-Casualty Incidents
Open this publication in new window or tab >>Monitoring and Visualisation Support for Management of Medical Resources in Mass-Casualty Incidents
(English)Manuscript (Other (popular science, discussion, etc.))
Abstract [en]

Improving command and control of rescue operations requires methods to elucidate the dynamic interaction between different teams in a rescue force in a stressful situation. To this end, we present a method to monitor and visualise the utilisation of medical resources in mass-casualty incidents. The flow of casualties is monitored at specific checkpoints where each individual is assigned a time stamp. This process generates a timeline for each casualty which shows, in great detail, how he or she was transferred through the chain of medical attendance. These timelines can be combined to model the flow of casualties from the location of the incident, through various aid stations and assembly areas, to hospitals. The resulting flow model can be visualised using a software tool. We have applied the method to training exercises where we used it both to support debriefing after the exercise and to facilitate subsequent, in-depth analysis. We conclude by exploring ways to use time-stamped checkpoints as a means of supporting the management of medical resources in real emergency operations.

Keyword
Rimed checkpoints, timelines, utilisation of medical resources, flow of casualties, emergency response training, mission training, exercise analysis and evaluation
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-15616 (URN)
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2010-01-14Bibliographically approved
2. Monitoring and Analysis of Command Post Communication in Rescue Operations
Open this publication in new window or tab >>Monitoring and Analysis of Command Post Communication in Rescue Operations
2001 (English)In: Safety Science, ISSN 0925-7535, E-ISSN 1879-1042, Vol. 39, no 1-2, 51-60 p.Article in journal (Refereed) Published
Abstract [en]

The performance of a command post staff has a decisive effect on the outcome of a rescue operation when it comes to co-ordination and management of various rescue forces. Monitoring and documentation of the internal work and communication processes that take place in a command team can increase the ability to investigate and understand cause–effect relationships between incoming field reports, operational procedures, decisions, commands and the rescue response in the field. To this end we present a method and a software tool that enable an observer to monitor and record communication events in a command post staff. The method extends link analysis by introducing time stamping and classification of events. Thus, extended link analysis enables both cumulative measures and detailed temporal analysis of staff communication. The software tool supports configuration, monitoring, time stamping and classification of communication events. It can export data in standard formats for statistical analysis and visualisation.

Keyword
Command post analysis, Command post communication, Extended link analysis (ELA), MIND, Link Analyzer
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-15617 (URN)10.1016/S0925-7535(01)00025-X (DOI)
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2017-12-14
3. Data Collection in Rescue Operations
Open this publication in new window or tab >>Data Collection in Rescue Operations
2002 (English)In: The International Emergency Management Society 9th Annual Conference Proceedings, 2002, 136-147 p.Conference paper, Published paper (Other academic)
Abstract [en]

Rescue operations are complex distributed activities. First response, incident command and rear support have to be coordinated under time pressure and safety critical conditions. Analysing an operation and learning from the experience is problematic because spatially separated units, heterogeneous systems and fragmentary information make it difficult for participants, managers and researchers to grasp the ramifications of a complex scenario. In training, multimedia representations of rescue operations support after-action reviews, post-mission analyses and distance learning by providing coherent and persistent representations of exercises. In this paper we investigate how methods and tools developed in a training context can be adapted to support reconstruction and exploration of real rescue operations as a basis for experience-based learning and operational development. Especially, we study the requirements and limitations on data collection in real rescue operations in relation to emergency-response training. We elaborate on the consequences of the differences in data collection abilities for documenting an involved scenario, analysing the facts of the event and communicating the results and findings.

Keyword
Rescue operations, data collection, debriefing, AAR, learning
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-15618 (URN)
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2009-04-14
4. Supporting Observers in the Field to Perform Model Based Data Collection
Open this publication in new window or tab >>Supporting Observers in the Field to Perform Model Based Data Collection
(English)Manuscript (Other academic)
Abstract [en]

Computerized support systems enhancing taskforce performance are being increasingly used in different organizations in the military, emergency response and crisis management fields. Computerized command and control (C2) systems and systems supporting concept development and experimentation (CD&E), training and capability development mostly handle data logged by technical systems, devices and sensors. Organizational demands for improved mission capabilities and reduced budgets impose new requirements on system performance and data content. More information needs to be provided by humans in the field, reporting observations from the evolving course of events in order to enhance possibilities for operational analyses and continuous development of organizational abilities. In this paper, we introduce model-based data collection (MBDC) and describe a method that can improve human datacollection abilities and data quality when using human observers as data collecting sensors in distributed tactical operations. Furthermore, we introduce a tool that can support observers in the field. The network-based observer tool (NBOT) can support human observers in determining what to report, and how and when to report the observation. It is possible to configure NBOT to meet different requirements, for example from a consideration of information needs, the field environment and available budget. We present results and findings from three different use cases.

National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-15619 (URN)
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2010-01-14

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