Abstract: Quantitative evaluations are valuable in the strive for improvements and asserting quality. However, the field of Command & Control (C2) evaluations are hard to navigate, and it is difficult to find the correct measurement for a specific situation. A comprehensive Scoping Study was made concerning measurements of C2 performance and effectiveness. A lack of an existing appropriate framework for discussing C2 evaluations led to the development of the Crisis Response Management (CRM) Matrix. This is an analysis tool that assigns measurements into categories, and each category display unique strengths, weaknesses and trends. The analysis yielded results proving to be too rich for a single article, thusly, this is the first of two articles covering the results. In this article, the Practitioners Guide focus on results valuable for someone interested in evaluating C2. Each evaluation has specific requirements that, for best result, ought to be reflected in the chosen measurement.

Abstract: In disaster situations like earthquakes and hurricanes, people have difficulties accessing shelter and requesting help. Many smartphone applications provide behavioral advice or means to communicate during such situations. However, to what extent a person is affected by a disaster is often unclear, as these applications rely on the user's subjective assessment. Therefore, detecting a user's situation is key to provide more meaningful information in such applications and to allows first responders to better assess incoming messages. We propose a predictive model that recognizes four normal and ten disaster-related activities achieving an average f1-score of up to 90.1\%, solely based on sensor readings of the subject's mobile device. We conduct an extensive measurement-based evaluation to assess the impact of individual model parameters on the prediction accuracy. Our model is orientation-independent, position-independent, and subject-independent, making it an ideal foundation for future context-aware emergency applications.

Abstract: Prehospital command and control (PS) is a structure for handling medical accidents in Sweden. It includes terminology, command structure, roles, and performance indicators. The concept is taught and trained at the Centre for Teaching and Research in Disaster Medicine and Traumatology (KMC). The concept is trained using a mixture of lectures, simulation based exercises, and scenario designed by the participants. The scenarios are ran in Emergo Train System (ETS), a versatile and flexible table-top simulation platform, where medical command and control can be trained and evaluated. The purpose of this study was to develop structure for feedback and reflection by using a measure of shared understanding. The empirical study presents how the Shared Priorities instrument can be used to provide structured feedback for training. The paper is concluded with a discussion on how the empirical findings can be integrated in training prehospital medical command and control.

Abstract: Sensitive products supply chain and supply chain facing crisis management share several aspects. In both cases, several decision makers have to choose the best options most of the time under pressure, often in emergency and need to access numerous information from the field. This shared monitoring aspect put forward the visualization need to consider in each decision all the crisis potential impacts. Unfortunately, for the transportation steps we focus on, the current transport management systems do not reach these requirements. In this paper, focusing on supply chains during crisis situations, we present a new monitoring system with adapted functionalities. The added value is to connect in real time and relevant way the data from the field to the information on a shared model used to make reliable decisions. We use the French Blood Establishment supply chain to illustrate the proposition.

Abstract: In a disaster, the main agencies of healthcare and relief are usually health and disaster management organisations. Although these two disciplines share the same vision of care provision to disaster victims, experience shows that poor communication between them can negatively impact the collaboration needed to ensure the quality and coordinated delivery of effective healthcare. This paper presents the current findings of an on-going investigation to determine and reduce the barriers to smooth and effective communication and information exchange.

Abstract: Huge amounts of data that are generated on social media during emergency situations are regarded as troves of critical information. The use of supervised machine learning techniques in the early stages of a disaster is challenged by the lack of labeled data for that particular disaster. Furthermore, supervised models trained on labeled data from a prior disaster may not produce accurate results, given the inherent variation between the current and the prior disasters. To address the challenges posed by the lack of labeled data for a target disaster, we propose to use a hybrid feature-instance adaptation approach based on matrix factorization and the k nearest neighbors algorithm, respectively. The proposed hybrid adaptation approach is used to select a subset of the source disaster data that is representative for the target disaster. The selected subset is subsequently used to learn accurate Naive Bayes classifiers for the target disaster.

Abstract: Smart Service Queensland (SSQ) is the 'front door' to the Queensland State Government in Australia, providing services and information for citizens and businesses. Services are delivered through online channels, call centres and face-to-face service centres. Rostering to adequately staff the call centres during business as usual demand is well supported using existing workforce planning tools and content management systems alongside real-time telephonic monitoring. However, during times of large scale emergency events, such as floods and tropical cyclones, effective workforce planning heavily relies upon experienced SSQ personnel constantly monitoring and updating call centre staffing levels leading up to and during the disaster event to ensure customer demands are met. Achieving the right balance of call centre servicing without over provisioning is a challenging task. We present a prototype analytics tool that supports the SSQ Forecast Analyst responsible for workforce planning during disaster events and provides initial results of modelling caller behavior during two recent tropical cyclones. The tool provides a single point of reference to a wide collection of relevant datasets, including population demographics and details of the natural and built environment, data feeds describing the emergency event under investigation, relevant social media posts and call centre operations metrics. The tool is an early proof of concept demonstrator highlighting the utility of data integration, web mapping, real-time event monitoring, and predictive modelling.

Abstract: The American Society of Civil Engineers (ASCE) Report Card for America's Infrastructure gave bridges a C+ (mediocre) grade in 2017. Approximately, 1 in 5 rural bridges are in critical condition, which presents serious challenges to public safety and economic growth. Fortunately, during a series of workshops on this topic organized by the authors, it has become clear that Big Data could provide a timely solution to these critical problems. In this work in progress paper we describe a conceptual framework for developing SMart big data pipelines for Aging Rural bridge Transportation Infrastructure (SMARTI). Our framework and associated research questions are organized around four ingredients: o Next-Generation Health Monitoring: Sensors; Unmanned Aerial Vehicle/System (UAV/UAS); wireless networks o Data Management: Data security and quality; intellectual property; standards and shared best practices; curation o Decision Support Systems: Analysis and modeling; data analytics; decision making; visualization, o Socio-Technological Impact: Policy; societal, economic and environmental impact; disaster and crisis management.

Abstract: Japanese society is aging rapidly, so an increasing number of households currently consists of only elderly single people or couples. We propose a system that uses LINE (a mobile communication application) for sending notices containing information from local governments to elderly or physically disabled people, as well as for efficient monitoring by local governments and social workers of the health conditions and statuses of such people. Our system can be used by anyone who has a smartphone with LINE installed. We have also conducted an operational test of a prototype of our system.

Abstract: Natural and manmade disasters pose a myriad of challenges, which are more severe for individuals with disabilities. Ordinarily to perform daily activities, the disabled get support from assistive technological devices and services; these are commonly disrupted during and after disasters. A proposed solution to support those with visual impairment is a cost-effective wearable 'Smart Cap'. The Smart Cap provides narratives about the surrounding environment while establishing communication between the user (the visually impaired) and a rich online reservoir of knowledge base system capable of vocalising narratives. As a proof-of-concept, this study is implemented using Raspberry Pi, the Amazon Web Services and a P-Cap fitted with a camera. The aim of this research work is to provide an assistive technology to help the visually impaired navigate their way out of any potentially disastrous situation like other citizens would. The proposed system and its usage in disaster situations is an innovative, cost-effective solution specifically addressing the needs of visually impaired persons.

Abstract: Nepal is one of the most popular travel destinations because of its natural beauty and Himalayas. Tourism industry contributes significantly to the nation's GDP. However, the 2015 earthquake has created great havoc causing loss of more than 9,000 lives, damaging many buildings including World heritage sites and trekking trails. Despite a substantial amount of foreign aid, overall recovery programs have not been effective. This empirical study focuses on the use of ICT tools for the recovery works in the tourism industry and uses mixed methods engaging tourism associations and organisations. Four 'areas of concerns' regarding ICT use, are identified by using the qualitative analysis and validated through a survey of 198 tourism organisations. The findings show that the earthquake has significantly impacted the industry and the government has not adequately used ICTs in the recovery activities. This study strongly advocates using ICT tools for the post-disaster tourism resilience.

Abstract: In 2015 Wellington joined the 100 Resilient Cities Organization and began a new chapter in its resilience journey. This journey has seen a strategic focus on the use of data to enable better emergency response and to integrate and inform decision making at all levels. The strategic focus in the resilience strategy of integrating data into governance, adaptation, recovery and community engagement has helped Wellington manage the effects of the 2016 Kaikoura Earthquake, lead engagement on sea level rise and integrate resilience building measures into the city's built environment and communities. This strategic intent has driven the renewal of a city data capability to provision the Risk Reduction, Readiness, Response and Recovery of the city.