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Nowadays, we are witnessing a shift in the way emergencies are being managed. On the one hand, the availability of big data and the evolution of geographical information systems make it possible to manage and process large quantities of information that can hugely improve the decision-making process. On the other hand, digital humanitarianism has s...
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... this section, we briefly review the NIST Big Data Reference Architecture (NBDRA), shown in Figure 1. It is the proposal that has achieved the most support from the academy and industry, being developed by a working group launched in 2013 with over six hundred participants from industry, academia, and government. ...
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... Величезні масштаби наслідків аварій, катастроф і стихійних лих, що нерідко мають місце, а також небезпек, що виникають при веденні військових дій і терористичних актах визначають необхідність створення державних систем захисту населення і територій від надзвичайних ситуацій. Ефективне запобігання і ліквідація наслідків надзвичайних ситуацій вимагає зосередження зусиль усієї держави, організації взаємодії різних органів управління, сил і засобів, а в ціломуформування та реалізації державної політики у цій галузі [2]. Отже, забезпечення безпеки та захисту населення, об'єктів економіки та національного надбання держави від негативних наслідків надзвичайних ситуацій розглядається як невід'ємна частина державної політики, національної безпеки та державного управління, яка є однією з найважливіших функцій органів державної влади всіх рівнів. ...
The article deals with civil security ensuring problem in Ukraine. The problem urgency of the population and territories protecting from emergency situations is due to a significant number of natural and man-made accidents and disasters, social upheavals that lead to numerous victims and substantial economic losses, as well as the presence of threats and military conflicts on our country's territory. A general description of various types of emergency situations is provided. It was determined that the leading causes of emergency situations are accidents and disasters at industrial facilities and transport, natural disasters, diseases and injuries among people, agricultural animals and plants, armed conflicts and other social and political nature factors. The authors analyzed the civil security current state in the Ukraine territory. Statistical data on dead and injured numbers as a result of emergency situations by nature of origin (man-made, natural, social, military) and level of spread (state, regional, local, facility) are presented. It is noted that 66 emergency situations were registered during the past year, as a result of which 7 thousand 4 people died and 11 thousand 72 people were injured. Special attention is paid to emergency situations of a military nature of the state level. It was established that the primary efforts of the State Emergency Service of Ukraine units for the past year were focused on eliminating the consequences of Russia's armed aggression against Ukraine and providing assistance to the population. The need to improve measures to ensure civil safety and prompt response to emergency situations and events was emphasized. It was concluded that the effective prevention and emergency situations consequences liquidation requires the concentration of efforts of the entire state, the organization of various management bodies, forces and means interaction, and in general, the formation and implementation of state policy in this field. Keywords: civil security, emergency, danger, protection, military operations.
... The absence of a clear and general understanding of the concepts and facts that significantly increase awareness and capacity building is considered to be one of the most significant barriers to usage of DTSCs to manage disasters. This may be partially ascribed to the problem's inherent complexity and the wide range of spatial and temporal scales on which its manifestations take place [176]. ...
Natural hazard-induced disasters have caused catastrophic damage and loss to buildings, infrastructure, and the affected communities as a whole during the recent decades and their impact is expected to further escalate in the future. Thus, there is a huge demand for disaster risk management using digitalisation as a key enabler for effective and efficient disaster risk management systems. It is widely accepted that digital and intelligence technologies can help solve key aspects of disaster risk management such as disaster prevention and mitigation, and rescue and recovery. Digital Twin (DT) is one of the most promising technologies for multi-stage management which offers significant potential to advance disaster resilience. Smart Cities (SCs) use pervasive information and communications technology to monitor activities in the city. With increasingly large applications of DTs combined with big data generated from sensors in a SC, it is now possible to create Digital Twin Smart Cities (DTSCs). Despite the increasing prevalence of DTSC technologies and their profound impact on disaster risk management, a systematic and longitudinal view of the evolution to the current status of DTSC for disaster risk management does not exist. This review analyses 312 titles and abstracts and 72 full papers. To begin with, a scientific review of DT and SC is undertaken, where the evolution of DTSCs is reviewed. In addition, the intelligence technologies used in DTSCs for disaster risk management are assessed and their benefits are evaluated. Furthermore, the evolution and technical feasibility of DTSC-driven disaster risk management is evaluated by assessing current applications of DTSCs in disaster risk management. It was found that despite the significant potential benefits offered by DTSCs, they also add a new layer of complexities and challenges inherent to these technologies to the already complex web of complexities involved in disaster risk management. These challenges can be addressed by understanding how the process of utilising DTSCs in disaster risk reduction and sustainability is designed, which is essential for comprehending what DTSCs may offer, how it is implemented, and what it means to all involved stakeholders. This paper contributes to the knowledge by improving the understanding of the current status of DTSC technologies and their impact on disaster risk management, and articulating the challenges in implementing DTSC, which inspires the professional community to advance these technologies to address them in future research.
... On their part, Yu et al. (2018) consider that big data is nothing but a reference to scientific and engineering methods and tools through which hugely enormous data can be analyzed, processed, managed, and stored. The term "big data" is also used to describe a large amount of data in the networked, digitized, sensorladen, information-driven world (Iglesias et al. 2020). It is a new technology that can effectively solve the vast amounts of data collection, storage, and display (Lu and Zhang 2016;Yu et al. 2018). ...
... The nature and volume of information that can be availed by the media, public institutions, individuals, and volunteer organizations have dramatically increased because of new technologies. The rise of sensor networks, social media, satellite remote sensing, and linked devices has contributed to a data influx beyond traditional technologies' capacity to acquire, process, and understand (Iglesias et al. 2020). Big Data has undoubtedly expanded the possibilities for natural emergency management because of its numerous alternatives for visualizing, evaluating, and anticipating emergencies. ...
Odonata (dragonflies and damselflies) are good indicators of climate change effects due to their fast response to climatic variables such as temperature, humidity and amount of rainfall. This study aims to investigate the effect of three scenario of climate change at a regional scale (New Aquitaine region, France) on 59 odonata species distribution using species distribution modeling methods. Those results allow to identify species that will be the most impacted by climate change but also to evaluate changes in odonata diversity across the study area, through the calculation of diversity indices for each climate scenario. 24–33% of the species are predicted loss between 75 and 100% of suitable habitat by 2100 under two scenarios. Predicted distribution map can be use by managers, and stakeholders to target areas to be protect in priority. Different approaches can be pursued: protections of areas that are suitable or will be suitable in the future for rare species and/or target areas that will be suitable for high number of species leading to a higher diversity. By protecting wetland suitable for diverse odonata species, other wetland affiliated species such as amphibians, birds, and plants might benefits from those actions.KeywordsClimate changeOdonataSpecies distribution modelsDiversity
... Nowadays when any kind of disaster occurs, the related type of data i.e., photos, videos, text, audio, etc., can easily be accessedfrom social media, as social media is a primary mode ofinstant communication. Organizations like disaster management systems and emergency response systems validate such types of data based on the validation services [1]. Most of the data available on social media is irrelevant and redundant. ...
Disaster is a big issue that seriously disrupts and affects the community or society. The impact of a disaster causes a short and long period of time. To analyze the impacts of disasters there are lots of available related datasets. Data analytics methods have the potential to assess the impacts of different types of disasters. Collectively data analytics and machine learning techniques play an important role in transforming and being able to make decisions about our social, economic, mental, and psychological things. The objective of this paper is to assess the impacts of disasters from immediate term to long-term, provide crucial help to the emergency management workforce, and policy decisions making based on the latest available datasets. With the help of the various data agencies, extraction of information and activities carried out, we can determine the effects on disaster victims, their community and impacts on society in general. The analysis provides the statistics that can guide our emergency service about the status of facilities that can further support the survivors, and other related information. Detailed assessment i.e., structural survey and hazard mapping provide specific information about reconstruction and mitigation to monitor the situation, needs of the victims, and supporting entities. The assessment is based on the type of disaster that happened and its impact after a few years. In the current technological advancement of data analytics and machine learning algorithms, the prediction of the long-term effects of a disaster can be performed. Analyzing the impacts over a long period of time is also dependent on the growth of actively cared datasets gathering bodies like agencies, government, NGOs, media, etc., where prediction of short-term and long-term impacts is dependent on the available datasets. Available datasets are preprocessed using data analytics tools and implementation of training and testing for the purpose of predictions and recommendations. As a huge amount of data sets are available through different sources the classification of the datasets can also be performed resulting fast and accurate processing. Model validation techniques play an important role to check the validation, test result, and related outcomes. In this paper advanced machine learning and data analytics tools i.e., XG boost, modified SVM, and modified RF are used for better prediction. The analysis of the short-term effects of disasters has already been suggested and recommended by the various conventional approaches. Here the focus is to analyze and detect the long-term effects of a disaster along with recommendations and models preparing for good decision-making. Therefore, planning should be focused on assessing the impacts from short-term to long-term. The findings of the paper would be helpful to the agencies, local & national authorities, and the government by recommending action plans and their future effects for a longer period in case of disaster.
... For good quality data as well as domain-specific resources to be available a shift toward inclusive preparedness is necessary. As foregrounded by Iglesias et al. (2020), the full potential of combining automated big data processing for specific purposes (here digital humanitarianism), has not been reached yet. The tension between potential and effective solutions in crisis settings opens the doors to additional technology that cuts across the various dimensions of cross-organisational collaboration. ...
... For Iglesias et al. (2020), translations done using crowdsourcing or automatic methods are core tasks that belong to an elaborate framework for data activity geared towards improved access to information. Other scholars, such as Greenwood et al. (2017), O'Brien et al. (2018), and Nurminen and Koponen (2020), also agree that access to information is a human right and that MT can help ensure accessibility of multilingual information for previously underserved groups. ...
Deploying technologies in support of translation/interpreting during cri-ses in multilingual settings poses serious deontological and ethical challenges. Most arise from ethical concerns around the adoption of technologies that can be only partially controlled. We discuss automated translation processes in relation to four dimensions of preparedness, crowdsourcing and data mining, local vs global crises, and multimodal demands of communication. We start by considering automation processes in which MT is embedded as a tool to support crisis communication, we consider ethical risks pertaining reliance on and understanding of MT potential. We then focus on the ethical complexity of multimodal processes of communication that hinge on crowdsourcing practices, that collate users' data, and that complement other automation processes. We move on to correlate these explicit ethical dimensions , with successful applications of MT engines to respond to local and global crises, and reflect on the ethical need to enshrine these in other practices that make translation into a risk reduction tool. We eventually zoom in on areas that are yet to exploit fully current automation processes, yet have already encountered ethical dilemmas when delivering information in multimodal format. We look at ways in which current automation processes can be successfully exploited, while we also warn to revise practices in which too much is expected by MT and automation processes thus heightening rather than reducing risks when communicating in multilingual crises. We conclude the chapter by connecting our ethical considerations on the role of MT and automation to debates around linguistic equality and social justice.
... At present, there are still many deficiencies and problems in the construction of safety and disaster prevention system in the society, which are manifested in the dislocation and disconnection between the existing disaster prevention and safety system and the actual needs of the society in the aspects of reducing disaster risk, analyzing the structural level of disaster causes and the quality of real-time data of the system [6]. Such dislocation and disconnection lead to the problems that the final application system fails to meet the expected goals when the relevant institutions or departments study such systems [7][8][9]. ...
Safety integrated disaster prevention system, as a guarantee of national safety, especially to reduce the serious consequences of disasters, promote the steady development of the economic and social level, has important practical value for the comprehensive study of safety and disaster prevention system. However, the current application and update of such systems by relevant government agencies and the social level cannot effectively follow the development needs of the society and the industry, and there is an urgent need for effective reform. Based on this, this paper first analyzes the problems existing in the research and construction system of big data technology in the security and integrated disaster prevention system, and then gives the construction strategy of the research system of safety and disaster prevention in view of these problems.
... The final goal of the system is to provide to the emergency operators selected images that, after an automatic geo-validation performed by a matching procedure with street view data, can be used to have a quick overview of the event thus better organize the rescue operations. The ASMIS system presents several novelties compared to the current state-of-theart in the field of emergency management systems based on computer vision [10] and social data [11][12][13][14][15]: ...
In recent years, social platforms have become integrated in a variety of economic, political and cultural domains. Social media have become the primary outlets for many citizens to consume news and information, and, at the same time, to produce and share online a large amount of data and meta-data. This paper presents an innovative system able to analyze visual information shared by citizens on social media during extreme events for contributing to the situational awareness and supporting people in charge of coordinating the emergency management. The system analyzes all posts containing images shared by users by taking into account: (a) the event class and (b) the GPS coordinates of the geographical area affected by the event. Then, a Single Shot Multibox Detector (SSD) network is applied to select only the posted images correctly related to the event class and an advanced image processing procedure is used to verify if these images are correlated with the geographical area where the emergency event is ongoing. Several experiments have been carried out to evaluate the performance of the proposed system in the context of different emergency situations caused by earthquakes, floods and terrorist attacks.
... In cases where such early interventions are absent, like with the COVID-19 outbreak that had not been anticipated, the consequences in all spheres are dire and with far-reaching outcomes. However, as posited by Iglesias, Favenza, and Carrera (2020), maximum leverage of Big Data analytics, together with other modern technologies like AI and ML, has the potential to ensure that disaster responses are activated. This could be true even in the current case of COVID-19, as the already available data from different sources could help plan to prevent further spread, help in vaccine inoculation drives, and prevent further spread (Alsunaidi et al., 2021;. ...
Urban Climate Adaptation and Mitigation offers evidence-based, scientific solutions for improving a city's ability to prepare, recover and adapt to global climate-related events. Bringing together a wide variety of research disciplines to addresses the linkages to climate change adaptation and mitigation topics with planning, transportation and waste management, the book informs different types of stakeholders on how they can enhance their preparation abilities to enable real-time response methods. Application-focused throughout, this book explores the complexities of urban systems and subsystems to support researchers, planners and decision-makers in their efforts toward developing more climate-resilient smart cities.
... In cases where such early interventions are absent, like with the COVID-19 outbreak that had not been anticipated, the consequences in all spheres are dire and with far-reaching outcomes. However, as posited by Iglesias, Favenza, and Carrera (2020), maximum leverage of Big Data analytics, together with other modern technologies like AI and ML, has the potential to ensure that disaster responses are activated. This could be true even in the current case of COVID-19, as the already available data from different sources could help plan to prevent further spread, help in vaccine inoculation drives, and prevent further spread (Alsunaidi et al., 2021;Sharifi et al., 2021). ...
Amidst increasing trends in climate-induced adverse events, building urban resilience
has become a priority for many cities around the world. Due to historical emissions, even
under the most stringent climate mitigation scenarios, there is now consensus that the frequency and intensity of climate-induced adverse events such as floods, torrential rains,
storms and cyclones, sea-level rise, and extreme heat events will increase in the coming decades. The devastating climate impacts and unregulated economic growth policies will also accelerate the degradation of natural ecosystems that provide multiple provisioning, regulating, supporting, and cultural ecosystem services to humans. Furthermore, unregulated
human–environment interactions and increasing encroachment on natural ecosystems
may lead to the spread of infectious diseases and epidemics that can significantly disrupt
human life, as shown during the COVID-19 pandemic
... For instance, it was recorded that smart urban governance has the potential to help save each urban resident approximately 100 h per year, which when monetized, could translate to approximately $1377 per person per year in America, or £904 in the United Kingdom [15]. This, however, is much less significant than other direct benefits such as improved liveability status [16][17][18], improved emergency preparedness and response [19], and improved infrastructural development [20] thanks to emerging technologies. Smart urban governance is further seen to be instrumental in the achievement of urban sustainable agendas, as captured in the Sustainable Development Goal 11 [21]. ...
The concept of smart cities peaked in 2015, bringing an increased influx of ‘smart’ devices in the form of the Internet of Things (IoT) and sensors in cities. As a result, interest in smart urban governance has become more prevalent in administrative, organisational, and political circles. This is sustained by both local and global demands for an increased contribution to the goals of sustainability through urban governance processes in response to climate change urgencies. Cities generate up to 70% of global emissions, and in light of societal pressures for more inclusivity and democratic processes, the need for sound urban governance is merited. Further knowledge on the theme of smart urban governance is required to better understand the trends and knowledge structures and better assist policy design. Therefore, this study was undertaken to understand and map the evolution of the concept of smart urban governance through a bibliometric analysis and science mapping techniques using VOSviewer. In total, 1897 articles were retrieved from the Web of Science database over 5 decades, from 1968 to 2021, and divided into three subperiods, namely 1978 to 2015, 2016 to 2019, and 2020 to early 2022. Results indicate that the overall emerging themes across the three periods highlight the need for citizen participation in urban policies, especially in relation to smart cities, and for sustained innovation for e-participation, e-governance, and policy frameworks. The results of this study can aid both researchers exploring the concept of urban governance and policy makers rendering more inclusive urban policies, especially those hosting technological and digital domains.
