5,527 research outputs found

    Fireground location understanding by semantic linking of visual objects and building information models

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    This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

    How much does a man cost? A dirty, dull, and dangerous application

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    Thesis (M.A.) University of Alaska Fairbanks, 2017This study illuminates the many abilities of Unmanned Aerial Vehicles (UAVs). One area of importance includes the UAV's capability to assist in the development, implementation, and execution of crisis management. This research focuses on UAV uses in pre and post crisis planning and accomplishments. The accompaniment of unmanned vehicles with base teams can make crisis management plans more reliable for the general public and teams faced with tasks such as search and rescue and firefighting. In the fight for mass acceptance of UAV integration, knowledge and attitude inventories were collected and analyzed. Methodology includes mixed method research collected by interviews and questionnaires available to experts and ground teams in the UAV fields, mining industry, firefighting and police force career field, and general city planning crisis management members. This information was compiled to assist professionals in creation of general guidelines and recommendations for how to utilize UAVs in crisis management planning and implementation as well as integration of UAVs into the educational system. The results from this study show the benefits and disadvantages of strategically giving UAVs a role in the construction and implementation of crisis management plans and other areas of interest. The results also show that the general public is lacking information and education on the abilities of UAVs. This education gap shows a correlation with negative attitudes towards UAVs. Educational programs to teach the public benefits of UAV integration should be implemented

    Multi-robot team formation control in the GUARDIANS project

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    Purpose The GUARDIANS multi-robot team is to be deployed in a large warehouse in smoke. The team is to assist firefighters search the warehouse in the event or danger of a fire. The large dimensions of the environment together with development of smoke which drastically reduces visibility, represent major challenges for search and rescue operations. The GUARDIANS robots guide and accompany the firefighters on site whilst indicating possible obstacles and the locations of danger and maintaining communications links. Design/methodology/approach In order to fulfill the aforementioned tasks the robots need to exhibit certain behaviours. Among the basic behaviours are capabilities to stay together as a group, that is, generate a formation and navigate while keeping this formation. The control model used to generate these behaviours is based on the so-called social potential field framework, which we adapt to the specific tasks required for the GUARDIANS scenario. All tasks can be achieved without central control, and some of the behaviours can be performed without explicit communication between the robots. Findings The GUARDIANS environment requires flexible formations of the robot team: the formation has to adapt itself to the circumstances. Thus the application has forced us to redefine the concept of a formation. Using the graph-theoretic terminology, we can say that a formation may be stretched out as a path or be compact as a star or wheel. We have implemented the developed behaviours in simulation environments as well as on real ERA-MOBI robots commonly referred to as Erratics. We discuss advantages and shortcomings of our model, based on the simulations as well as on the implementation with a team of Erratics.</p

    Optimization of CO2 production rate for firefighting robot applications using response surface methodology

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    A carbon dioxide gas-powered pneumatic actuation has been proposed as a suitable power source for an autonomous firefighting robot (CAFFR), which is designed to operate in an indoor fire environment in our earlier study. Considering the consumption rate of the pneumatic motor, the gas-powered actuation that is based on the theory of phase change material requires optimal determination of not only the sublimation rate of carbon dioxide but also the sizing of dry ice granules. Previous studies that have used the same theory are limited to generating a high volume of carbon dioxide without reference to neither the production rate of the gas nor the size of the granules of the dry ice. However, such consideration remains a design requirement for efficient driving of a carbon dioxide-powered firefighting robot. This paper investigates the effects of influencing design parameters on the sublimation rate of dry ice for powering a pneumatic motor. The optimal settings of these parameters that maximize the sublimation rate at the minimal time and dry ice mass are presented. In the experimental design and analysis, we employed full-factorial design and response surface methodology to fit an acceptable model for the relationship between the design factors and the response variables. Predictive models of the sublimation rate were examined via ANOVA, and the suitability of the linear model is confirmed. Further, an optimal sublimation rate value of 0.1025 g/s is obtained at a temperature of 80°C, the mass of 16.1683 g, and sublimation time of 159.375 s

    A Real Option Dynamic Decision (rodd) Framework For Operational Innovations

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    Changing the business operations and adopting new operational innovations, have become key features for a business solution approach. However, there are challenges for developing innovative operations due to a lack of the proper decision analysis tools, lack of understanding the impacts transition will have on operational models, and the time limits of the innovation life cycle. The cases of business failure in operational innovation (i.e. Eastman Kodak Company and Borders Group Inc.,) support the need for an investment decision framework. This research aims to develop a Real Option Dynamic Decision (RODD) framework for decision making, to support decision makers for operational innovation investments. This development will help the business/organization to recognize the need for change in operations, and quickly respond to market threats and customer needs. The RODD framework is developed by integrating a strategic investment method (Real Options Analysis), management transition evaluation (Matrix of Change), competitiveness evaluation (Lotka-Volterra), and dynamic behavior modeling (System Dynamics Modeling) to analyze the feasibility of the transformation, and to assess return on investment of new operation schemes. Two case studies are used: United Parcel Service of America, Inc., and Firefighting Operations to validate the RODD framework. The results show that the benefits of this decisionmaking framework are (1) to provide increased flexibility, improved predictions, and more information to decision makers; (2) to assess the value alternative option with regards to uncertainty and competitiveness; (3) to reduce complexity; and (4) to gain a new understanding of operational innovations

    AEGIS App: Wildfire Information Management for Windows Phone Devices

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    AbstractNovel technological advances in mobile devices and applications can be exploited in wildfire confrontation, enabling end-users to easily conduct several everyday tasks, such as access to data and information, sharing of intelligence and coordination of personnel and vehicles. This work describes an innovative mobile application for wildfire information management that operates on Windows Phone devices and acts as a complementary tool to the web-based version of the AEGIS platform for wildfire prevention and management. Several tasks can be accomplished from the AEGIS App, such as routing, spatial search for closest facilities and firefighting support infrastructures, access to weather data and visualization of fire management data (water sources, gas refill stations, evacuation sites etc.). An innovative feature of AEGIS App is the support of these tasks by a digital assistant for artificial intelligence named Cortana (developed by Microsoft for Windows Phone devices), that allows information utilization through voice commands. The application is to be used by firefighting personnel in Greece and is potentially expected to contribute towards a more sophisticated transferring of information and knowledge between wildfire confrontation operation centers and firefighting units in the field

    Fire Safety Analysis of a Railway Compartment using Computational Fluid Dynamics

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    Trains are considered to be the safest on-land transportation means for both passengers and cargo. Train accidents have been mainly disastrous, especially in case of fire, where the consequences are extensive loss of life and goods. The fire would generate smoke and heat which would spread quickly inside the railway compartments. Both heat and smoke are the primary reasons of casualties in a train. This study has been carried out to perform numerical analysis of fire characteristics in a railway compartment using commercial Computational Fluid Dynamics code ANSYS. Non-premixed combustion model has been used to simulate a fire scenario within a railway compartment, while Shear Stress Transport k-ω turbulence model has been used to accurately predict the hot air turbulence parameters within the compartment. The walls of the compartment have been modelled as no-slip stationary adiabatic walls, as is observed in real life conditions. Carbon dioxide concentration (CO2), temperature distribution and air flow velocity within the railway compartment has been monitored. It has been observed that the smoke above the fire source flows to both sides of the compartment. The highest temperature zone is located downstream the fire source, and gradually decreases with the increase in the distance from the fire source. It can be seen that CFD can be used as an effective tool in order to analyse the evolution of fire in railway compartments with reasonable accuracy. The paper also briefly discusses the topical reliability issues

    Occupational Athletes: An Integrated Approach to Firefighting Performance

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    Introduction: Over the past 20 years, the injury rates among firefighters have captured the interest of sport scientists. In order to prevent firefighter injuries, however, scholars must first gain a better understanding of firefighting performance (Smith, 2011). This has been a challenge, since to date sport scientists have focused primarily on the physical aspects of firefighting performance and have overlooked the multidimensional nature of firefighting performance (Gnacinski, Meyer, & Ebersole, in press). In the sport arena, sport scientists often use theoretical models to conceptualize the multiple demands experienced by an athlete. Guided by an integrated model of sport performance, the Meyer Athlete Performance Management Model (MAPM; Meyer, Merkur, Ebersole, & Massey, in press), the purposes of the current study were to: (a) describe the physical and psychological characteristics of cadets, recruits, and active firefighters; (b) compare physical and psychological characteristics of cadets, recruits, and active firefighters; and (c) provide evidence-based recommendations for the development of integrated firefighting training programs. Methods: Male cadets (n = 11), recruits (n = 27), and active firefighters (n = 15) completed a battery of physical (i.e., aerobic fitness, muscular strength and endurance, body composition, functional movement, muscular power) and psychological (i.e., personality, self-efficacy, intrinsic motivation, anxiety, psychological skills use) assessments. Results: No significant differences emerged between groups for any of the physical or psychological characteristics assessed with the exception of several psychological skills used during training. Specifically, cadets and active firefighters reported using self-talk, emotional control, and attentional control more than recruits (ps \u3c .001), active firefighters reported using automaticity more so than recruits (p = .003), and cadets reported using activation more so than recruits (p = .001). Discussion: Results of the current study supported the use of an integrated model of sport performance to conceptualize firefighting performance. Results of the current study also provided directions for firefighting training programs and future research

    Agent-Driven Representations, Algorithms, and Metrics for Automated Organizational Design.

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    As cooperative multiagent systems (MASs) increase in interconnectivity, complexity, size, and longevity, coordinating the agents' reasoning and behaviors becomes increasingly difficult. One approach to address these issues is to use insights from human organizations to design structures within which the agents can more efficiently reason and interact. Generally speaking, an organization influences each agent such that, by following its respective influences, an agent can make globally-useful local decisions without having to explicitly reason about the complete joint coordination problem. For example, an organizational influence might constrain and/or inform which actions an agent performs. If these influences are well-constructed to be cohesive and correlated across the agents, then each agent is influenced into reasoning about and performing only the actions that are appropriate for its (organizationally-designated) portion of the joint coordination problem. In this dissertation, I develop an agent-driven approach to organizations, wherein the foundation for representing and reasoning about an organization stems from the needs of the agents in the MAS. I create an organizational specification language to express the possible ways in which an organization could influence the agents' decision making processes, and leverage details from those decision processes to establish quantitative, principled metrics for organizational performance based on the expected impact that an organization will have on the agents' reasoning and behaviors. Building upon my agent-driven organizational representations, I identify a strategy for automating the organizational design process~(ODP), wherein my ODP computes a quantitative description of organizational patterns and then searches through those possible patterns to identify an (approximately) optimal set of organizational influences for the MAS. Evaluating my ODP reveals that it can create organizations that both influence the MAS into effective patterns of joint policies and also streamline the agents' decision making in a coordinate manner. Finally, I use my agent-driven approach to identify characteristics of effective abstractions over organizational influences and a heuristic strategy for converging on a good abstraction.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113616/1/jsleight_1.pd
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