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

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

THE NEXT GENERATION OF WILDLAND FIREFIGHTING TOOLS: USING UAV SWARMS FOR FIRE ATTACK

Wildland fires pose a direct threat to homeland security because of the severe personal, economic, and social stress they cause to those affected. As unmanned aerial vehicle (UAV) swarms become more ubiquitous in use, they will likely find a place as a frontline firefighting aerial asset, increasing the operational pace of aerial suppression flights and consequently increasing the safety of firefighters. This thesis explored the concept of using UAV swarms as a method for fire attack by comparing theoretical swarms to a conventional aerial asset within a realistic fire scenario and then using a systems engineering approach to define pressure points for implementing UAV swarms in the wildland space. The findings of this research support continued development of UAV swarms and clearly define areas that must be addressed before implementing large-scale UAV swarm flights. The firefighting UAV swarm system shows great promise due to its relative portability and ability to provide an aerial firefighting option to areas without ready access to conventional firefighting aircraft. It will be critical, however, to address logistical and communications constraints of UAV swarm systems before implementation to ensure positive outcomes.Civilian, Portland Fire and RescueApproved for public release. Distribution is unlimited

Integrating virtual reality and Building Information Modeling for improving highway tunnel emergency response training

During the last two decades, managers have been applying Building Information Modeling (BIM) to improve the quality of management as well as operation. The effectiveness of applications within a BIM environment is restrained by the limited immersive experience in virtual environments. Defined as the immersive visualization of virtual scenes, Virtual Reality (VR) is an emerging technology that can be actively explored to expand BIM to more usage. This paper highlights the need for a structured methodology for the integration of BIM/VR and gives a generic review of BIM and VR in training platforms for management in infrastructures. The rationales for fire evacuation training were formed based on the review. Then, methods of configuring BIM + VR prototypes were formulated for emergency response in highway tunnels. Furthermore, a conceptual framework integrating BIM with VR was proposed to enable the visualization of the physical context in real-time during the training. The result indicated that, extended to the training system of highway management via the “hand” of BIM, the VR solution can benefit more areas, such as the cost of fire evacuation drills in highway tunnels and the tendency of accidents to occur in the emergency response

Integrated automotive exhaust engineering : uncertainty management

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2006.Includes bibliographical references (p. 104-108).The global automotive industry has entered a stagnating period. Automotive OEMs and their tier suppliers are struggling for business growth. One of the most important strategies is to improve the engineering efficiency in the product development process. The engineering uncertainties have been identified as the main obstacles in the Lean Engineering practices. This study will be focused on the engineering development process of ArvinMeritor Emission Technologies. The lean engineering principles and techniques are applied to the current product development process. The Value Stream Mapping and Analysis method is used to identify the information flow inside the current engineering process. Based on the value stream map, the uncertainties at various development stages in the process are identified. The Design Structure Matrix is used to identify any unplanned design iteration, which results in lower engineering efficiency. The House of Quality is used to prioritize the importance of the iterations. The suggested excel program can effectively evaluate the effect of task duration, probability, impact and learning curve assumption.(cont.) In order to quantitatively predict the effects of the uncertainties, a System Dynamic model is specifically developed for the current engineering of Emission Technologies. The results clearly indicate the control factors for on-time delivery, efficient resource allocation, and cost reduction. This study has integrated the techniques from system engineering, system project management, and system dynamics. An improved automotive exhaust engineering process is proposed.by Xitian Fang and Deming Wan.S.M

Fire Service - Management and Command of Major Incidents

This study has concentrated upon the decision-making processes used at major incidents by the fire service in the United Kingdom rather than the more routine decisions made on the fireground. This partly because major incidents are safety critical events, involving complex technical or communication issues involving large volumes of information and many agencies, and also because the decisions made and judgements exercised have to demonstrate a robustness in application that will withstand considerable external scrutiny, since often major incidents involve losses that are subject to insurance or legal investigations. The research undertaken indicates that improvements are possible. The research places the current decision system in context. It does this by considering the cultural traditions of the fire service together with the managerial and organisational arrangements that set the parameters within which judgements and decisions will be made. This approach provides an insight as to how the fire service functions at operations and importantly the relationship between those decisions and time pressured environment in which they are often reached. Practical case studies that were attended by the author as the senior fire service commander are used to illustrate these features and help provide useful learning outcomes. This foundation is then used to consider in detail the whole decision support system employed and to offer objective improvements. Explanation of the operational practice employed is assisted by the provision of a number of tables and figures that illustrate the critical parts of the decision system, such as information trees and components and observed inter-agency issues, which are summarised in a systethatic decision process. Having collated and reviewed these findings it is postulated that command competency and situational awareness, the essential pre-requisites, can be improved through use of a new paradigm that emphasises the better use of data derived from a wider range of sources than are currently used. To assist in gaining this improvement greater integration of technology is suggested and options that exploit technology, such as electronic data communications, sensing devices, robotics and visualisátion, explored. Additional to the main study a number of allied supportive areas of research have been undertaken. These have included issues like fire service culture, public reaction to a serious fire, emergency action procedures, and toxic plume modelling and fireball impacts together with brief commentaries on September 11th and the future fire service in the United Kingdom. This research contributes to a relatively new area of study, the fire service decision process used to command and control resources, at major incidents

Cybersecurity of COSPAS-SARSAT and EPIRB: threat and attacker models, exploits, future research

COSPAS-SARSAT is an International programme for "Search and Rescue" (SAR) missions based on the "Satellite Aided Tracking" system (SARSAT). It is designed to provide accurate, timely, and reliable distress alert and location data to help SAR authorities of participating countries to assist persons and vessels in distress. Two types of satellite constellations serve COSPAS-SARSAT, low earth orbit search and rescue (LEOSAR) and geostationary orbiting search and rescue (GEOSAR). Despite its nearly-global deployment and critical importance, unfortunately enough, we found that COSPAS-SARSAT protocols and standard 406 MHz transmissions lack essential means of cybersecurity. In this paper, we investigate the cybersecurity aspects of COSPAS-SARSAT space-/satellite-based systems. In particular, we practically and successfully implement and demonstrate the first (to our knowledge) attacks on COSPAS-SARSAT 406 MHz protocols, namely replay, spoofing, and protocol fuzzing on EPIRB protocols. We also identify a set of core research challenges preventing more effective cybersecurity research in the field and outline the main cybersecurity weaknesses and possible mitigations to increase the system's cybersecurity level

VR-Based Safety Training Program for High-Rise Building Construction

The rates of fatal and non-fatal accidents within the construction industry across the globe are surging despite the massive efforts that are being exerted toward maintaining a safe working environment. Past research has proved that the provision of effective safety training programs is a primary course of action that should be taken to minimize construction accidents, fatalities, and both fatal and nonfatal injuries. However, in acknowledging the limitations of traditional safety training programs within the construction industry, several researchers have addressed the urge to incorporate novel training practices that are based on the modern virtual reality (VR) technology to promote “learning by doing” and “experiential learning” in their educational approaches. Nevertheless, there is a lack of incorporating major learning theories as a solid foundation for the design and development of VR-based training programs. Also, there is a lack of comprehensive VR-based safety training programs that specifically address the safety of high-rise building construction. This research aims to develop a comprehensive, fully immersive, and interactive VR-based safety training program that addresses the hazards and risks pertaining to the construction of high-rise buildings based on major learning theories in an attempt to enhance the learning outcomes of construction workers and safety officers. To conclude, the framework developed proved its efficiency and effectiveness in achieving the desired learning outcomes using VR-based training programs

Joint altitude and hybrid beamspace precoding optimization for UAV-enabled multiuser mmWave MIMO System

The combination of unmanned aerial vehicles (UAVs) and millimeter wave (mmWave) multiple-input multiple-out (MIMO) system is regarded as a key enabling technology for beyond 5G networks, as it provides high data rate aerial links. However, establishing UAV-enabled mmWave MIMO communication is quite challenging due to the high hardware cost in terms of radio frequency (RF) chains. As a cost-effective alternative, a beamspace precoding with discrete lens arrays (DLA) architecture has received considerable attention. However, the underlying optimal design in beamspace precoding has not been fully exploited in UAV-enabled communication scenario. In this paper, the joint design of the UAV's altitude and hybrid beamspace precoding is proposed for the UAV-enabled multiuser MIMO system, in which the DLA is exploited to reduce the number of the RF chain. In the proposed scheme, the optimization problem is formulated as a minimum weighted mean squared error (MWMSE) method. Then an efficient algorithm with the penalty dual decomposition (PDD) is proposed that aims to jointly optimize the altitude of UAV, beam selection and digital precoding matrices. Simulation results confirm the comparable performance of the proposed scheme and perform close to full-digital beamforming in terms of achievable spectral efficiency

Data acquisition filtering focused on optimizing transmission in a LoRaWAN network applied to the WSN forest monitoring system

Developing innovative systems and operations to monitor forests and send alerts in dangerous situations, such as fires, has become, over the years, a necessary task to protect forests. In this work, a Wireless Sensor Network (WSN) is employed for forest data acquisition to identify abrupt anomalies when a fire ignition starts. Even though a low-power LoRaWAN network is used, each module still needs to save power as much as possible to avoid periodic maintenance since a current consumption peak happens while sending messages. Moreover, considering the LoRaWAN characteristics, each module should use the bandwidth only when essential. Therefore, four algorithms were tested and calibrated along real and monitored events of a wildfire. The first algorithm is based on the Exponential Smoothing method, Moving Averages techniques are used to define the other two algorithms, and the fourth uses the Least Mean Square. When properly combined, the algorithms can perform a pre-filtering data acquisition before each module uses the LoRaWAN network and, consequently, save energy if there is no necessity to send data. After the validations, using Wildfire Simulation Events (WSE), the developed filter achieves an accuracy rate of 0.73 with 0.5 possible false alerts. These rates do not represent a final warning to firefighters, and a possible improvement can be achieved through cloud-based server algorithms. By comparing the current consumption before and after the proposed implementation, the modules can save almost 53% of their batteries when is no demand to send data. At the same time, the modules can maintain the server informed with a minimum interval of 15 min and recognize abrupt changes in 60 s when fire ignition appears.This work has been supported by SAFe Project through PROMOVE—Fundação La Caixa. The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for finan cial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). Thadeu Brito is supported by FCT PhD Grant Reference SFRH/BD/08598/2020, and Beatriz Flamia Azevedo is supported by FCT PhD Grant Reference SFRH/BD/07427/2021.info:eu-repo/semantics/publishedVersio