Communication Process of Disaster Management

The importance of effective and timely communication is critical in disaster management life cycle. With the proliferation of communication and web technologies, the challenge has now shifted from the availability of information to the efficient handling of the sheer amount of information available online. This has attracted researchers and practitioners to find ways which can facilitate individuals and organizations in their decision making while dealing with large amounts of online data. This chapter presents (1) the evolution of web technologies from Web 1.0 to Web 3.0, (2) the overview of communications tasks involved in disaster management, and (3) the literature survey on the pros and cons of Web 2.0 and Web 3.0 in disaster management. By comparing the role of Web 2.0 with Web 3.0, the chapter also attempts to explore how the communication tasks of disaster management could be improved using Web 3.0. It is anticipated that the findings of this chapter will assist the decision makers to use Web 3.0 as a strategic tool for effective communication in disaster management.

Reliable Communication Network for Emergency Response and Disaster Management in Underground Mines

Emergency response and disaster management in underground mines are very challenging due to the hostile nature. Environment monitoring in mines has been an obligatory requirement to ensure safe working conditions for miners. Reliable communication network is essential to quickly detect the underground condition especially in emergency situation and to conduct proper rescue operations. This chapter presents an overview of reliable communication network needed for emergency response and disaster management in underground mines. The chapter begins by introducing the most common accidents occurring in the mining, underground mine environment and channel properties. Subsequently, communications in underground mines, existing underground communication and tracking systems, and disaster forecasting & mine safety management are discussed. The chapter also covers post-disaster mine communications & tracking systems and optimized backbone networks for underground mines. Finally, the chapter concludes by reporting relevant research at Ryerson Communications Lab and pointing out some open issues and possible research directions.

Using Long Endurance Remotely Piloted Aircraft Systems to Support Humanitarian Logistic Operations

Whilst there has been some limited use of Remotely Piloted Aircraft Systems (RPAS) as part of the response to natural disasters, to date these have typically employed short range mini or micro systems. Using a case study of Cyclone Winston that struck Fiji in February 2016, this chapter demonstrates the potential for long endurance aircraft (LE-RPAS) to support the humanitarian logistic operations through the use of their high quality optics and communications capabilities. In doing so, it offers a high level route map for the development of the people, process and technology requirements that will be needed to underpin the future deployments of LE-RPAS in providing support to humanitarian activities.

A Simulation Methodology for Conducting Unbiased and Reliable Evaluation of MANET Communication Protocols in Disaster Scenarios

The need for a Mobile Ad-Hoc Network (MANET) in environments where there is a lack of communication infrastructure, such as disaster or emergency scenarios, is critical to save lives. MANETs can be used as an alternative network that solves the problem of communications. The selection of an appropriate MANET communication protocol is crucial for the good performance of the whole network. Due to the great variety of communication protocols available for MANETs such as routing and broadcasting protocols, the selection of the most suitable one for disaster scenarios is a relevant task. Routing protocols and broadcasting algorithms are normally evaluated and compared using simulation-based studies. However, conducting reliable and repeatable simulation studies is not a trivial task because many simulation parameters should be correctly configured. In this paper, we propose a methodology for conducting reliable simulations of MANET broadcasting algorithms in disaster scenarios. The proposed methodology is focused on the source nodes selection based on different metrics.

Smart Technologies for Emergency Response and Disaster Management

Disasters are the convergence of hazards that strikes a vulnerable community which is insufficient to withstand with its adverse effects and impact. Completely avoiding natural or anthropogenic disaster is not possible but its impact can be minimized by generating timely warning. The real-time earth observation is very important for generating such early warning. The earth observation is improving through the advancement in remote sensing technologies. Sensing technology provides real time monitoring and risk assessment. It helps in fast communication of an event occurrence. Disaster detection in urban areas is greatly improved by using remote sensing techniques. This chapter discus various devices used for real time earth monitoring of disaster events like Flood, Tsunami, Tornadoes, Droughts, Extreme Temperatures, Avalanches and Landslide. These devices gather information by continuous monitoring in their deployed location. The sensor information thus gathered must be communicated and processed to extract the disaster information.

Data Storages in Wireless Sensor Networks to Deal With Disaster Management

Sensor networks are dense wired or wireless networks used for collecting and disseminating environmental data. They have some limitations like energy that usually provide by battery and storages in order that we cannot save any generated data. The most energy consumer of sensors is transmitting. Sensor networks generate immense amount of data. They send collected data to the sink node for storage to response to users queries. Data storage has become an important issue in sensor networks as a large amount of collected data need to be archived for future information retrieval. The rapid development and deployment of sensor technology is intensifying the existing problem of too much data and not enough knowledge. Sensory data comes from multiple sensors of different modalities in distributed locations. In this chapter we investigate some major issues with respect to data storages of sensor networks that can be used for disaster management more efficiently.

Exploring Cloud-Based Distributed Disaster Management With Dynamic Multi-Agents Workflow System

Natural disaster is one of the important topics in current researches. Disaster Management System (DMS) is a complex system and needs to perform a collection of tasks collaboratively along with the potentiality to change the configurations of the system dynamically. In the research era of workflow model, existing models mainly deal with temporal and static constrains. However they cannot be used to keep pace with an uncertainly dynamic system like disaster management. Considering all these significant DMS attributes we have designed a new dynamically configurable and changeable workflow model with the support of adaptive scheduling, for both successful and failed situations, and implemented in a distributed cloud system to maintain the rescue and reorganization activities of disaster situation. In order to simplify the system architecture, we have used Multi Agent System (MAS) for our design. The proposed system achieves a comparatively higher rate of successful job completion-higher rescheduling success rate and comparatively lower dropout rate.

Application of Game Theory for Network Recovery After Large-Scale Disasters

In recent years, large-scale disasters took place frequently and always caused severe damages to the network infrastructures. Due to these damages, available network resources are usually not sufficient to meet the data transmission requirements of users after disasters. Moreover, users tend to behave selfishly by consuming as much network resources as possible. Incentive mechanisms are therefore essential for the users to voluntarily cooperate with each other and improve the system performance. In commercial networks, this can be efficiently achieved through pricing. Namely, by selecting an appropriate pricing policy, it is able to incentivize users to choose the service that best matches their data transmission demands. In this chapter, assuming that a time-dependent pricing scheme is imposed on network users, a Stackelberg leader-follower game is then formulated to study the joint utility optimization problem of the users in a disaster region subject to maximum delay and storage constrains. The equilibrium for the Stackelberg leader-follower game is also investigated.

Processing Big Data for Emergency Management

Emergencies are typically complex problems with serious consequences that must be solved in a limited amount of time to reduce any possible damage. Big data analysis leads to more assured decision making and better decisions can mean greater operational efficiencies, cost reductions and reduced risk. In this chapter, we discuss some issues on tackling emergency situation from the perspective of big data processing and management, including our approach for processing social media content. Communications during emergencies are so plentiful that it is necessary to sift through enormous data points to find information that is most useful during a given event. The chapter also presents our ongoing IT-system that processes and analyses social media data to transform the excessive volume of low information content into small volume but rich content that is useful to emergency personnel.

WiFi Fingerprint Localization for Emergency Response

As a key enabler for diversified location-based services (LBSs) of pervasive computing, indoor WiFi fingerprint localization remains a hot topic for decades. For most of previous research, maintaining a stable Radio Frequency (RF) environment constitutes one implicit but basic assumption. However, there is little room for such assumption in real-world scenarios, especially for the emergency response. Therefore, we propose a novel solution (HED) for rapidly setting up an indoor localization system by harvesting from the bursting number of available wireless resources. Via extensive real-world experiments lasting for over 6 months, we show the superiority of our HED algorithm in terms of accuracy, complexity and stability over two state-of-the-art solutions that are also designed to resist the dynamics, i.e., FreeLoc and LCS (Longest Common Subsequences). Moreover, experimental results not only confirm the benefits brought by environmental dynamics, but also provide valuable investigations and hand-on experiences on the real-world localization system.