scholarly journals Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions

Author(s):  
Thanh Thi Nguyen

Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with numerous successful stories. AI has also contributed to dealing with the coronavirus disease (COVID-19) pandemic, which has been happening around the globe. This paper presents a survey of AI methods being used in various applications in the fight against the COVID-19 outbreak and outlines the crucial roles of AI research in this unprecedented battle. We touch on a number of areas where AI plays as an essential component, from medical image processing, data analytics, text mining and natural language processing, the Internet of Things, to computational biology and medicine. A summary of COVID-19 related data sources that are available for research purposes is also presented. Research directions on exploring the potentials of AI and enhancing its capabilities and power in the battle are thoroughly discussed. We highlight 13 groups of problems related to the COVID-19 pandemic and point out promising AI methods and tools that can be used to solve those problems. It is envisaged that this study will provide AI researchers and the wider community an overview of the current status of AI applications and motivate researchers in harnessing AI potentials in the fight against COVID-19.

Author(s):  
Thanh Thi Nguyen

Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with numerous successful stories. AI has also contributed to dealing with the coronavirus disease (COVID-19) pandemic, which has been happening around the globe. This paper presents a survey of AI methods being used in various applications in the fight against the COVID-19 outbreak and outlines the crucial roles of AI research in this unprecedented battle. We touch on a number of areas where AI plays as an essential component, from medical image processing, data analytics, text mining and natural language processing, the Internet of Things, to computational biology and medicine. A summary of COVID-19 related data sources that are available for research purposes is also presented. Research directions on exploring the potentials of AI and enhancing its capabilities and power in the battle are thoroughly discussed. We highlight 13 groups of problems related to the COVID-19 pandemic and point out promising AI methods and tools that can be used to solve those problems. It is envisaged that this study will provide AI researchers and the wider community an overview of the current status of AI applications and motivate researchers in harnessing AI potentials in the fight against COVID-19.


2021 ◽  
pp. 135481662199996
Author(s):  
Ali Salman Saleh ◽  
Charbel Bassil ◽  
Arsalan Safari

Tourism in the Gulf Cooperation Council (GCC) countries has recently been considered by policymakers as a new avenue for economic diversification. Despite the considerable literature concerning the impact of tourism worldwide, only a limited number of studies have looked at the tourism sector in the GCC region or analyzed its economic, sociocultural, and environmental impacts. This article therefore conducts a systematic review of the state of the literature related to tourism in the GCC region. It provides effective insights about the current status, gaps, and challenges and proposes future research directions in this area for academics, practitioners, and policymakers with an interest in regional tourism development. The preferred reporting items for systematic reviews and meta-analyses approach was used to identify and select the papers. Some 23 papers were identified and analyzed. The majority of these studies focused on the United Arab Emirates, specifically the Dubai emirate. We found the most dominant research theme to be tourism planning.


2022 ◽  
Vol 54 (7) ◽  
pp. 1-34
Author(s):  
Sophie Dramé-Maigné ◽  
Maryline Laurent ◽  
Laurent Castillo ◽  
Hervé Ganem

The Internet of Things is taking hold in our everyday life. Regrettably, the security of IoT devices is often being overlooked. Among the vast array of security issues plaguing the emerging IoT, we decide to focus on access control, as privacy, trust, and other security properties cannot be achieved without controlled access. This article classifies IoT access control solutions from the literature according to their architecture (e.g., centralized, hierarchical, federated, distributed) and examines the suitability of each one for access control purposes. Our analysis concludes that important properties such as auditability and revocation are missing from many proposals while hierarchical and federated architectures are neglected by the community. Finally, we provide an architecture-based taxonomy and future research directions: a focus on hybrid architectures, usability, flexibility, privacy, and revocation schemes in serverless authorization.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xin Ning ◽  
Tong Liu ◽  
Chunlin Wu ◽  
Chao Wang

3D printing (3DP) is regarded as an innovation that contributes to automation in civil engineering and offers benefits in design, greenness, and efficiency. It is necessary to objectively analyze the current status and challenges associated with 3DP and identify future research directions to properly understand its construction applications. Previous research has focused more on the technical dimension of 3DP; however, the nontechnical dimension of the technology may hinder its implementation and thus must be paid particular attention to. This study presents a systematic review of the existing literature from both technical and nontechnical dimensions by combining quantitative and qualitative studies. The quantitative study was conducted using scientometric methods. The qualitative study analyzed information, including the technical research status and nontechnical challenges and trends. Two aspects of technical research status are presented, including materials and processes. In addition, nontechnical challenges and trends from the economic, environmental, social, and legislative aspects are proposed. This study provides a comprehensive agenda to advance 3DP in construction and proposes research interests, challenges, and future topics. It is intended to help construction practitioners systematically master existing processes and materials and assess the application degree and necessity of 3DP.


Author(s):  
Amal Kilani ◽  
Ahmed Ben Hamida ◽  
Habib Hamam

In this chapter, the authors present a profound literature review of artificial intelligence (AI). After defining it, they briefly cover its history and enumerate its principal fields of application. They name, for example, information system, commerce, image processing, human-computer interaction, data compression, robotics, route planning, etc. Moreover, the test that defines an artificially intelligent system, called the Turing test, is also defined and detailed. Afterwards, the authors describe some AI tools such as fuzzy logic, genetic algorithms, and swarm intelligence. Special attention will be given to neural networks and fuzzy logic. The authors also present the future research directions and ethics.


Author(s):  
Steven Walczak

Artificial intelligence is the science of creating intelligent machines. Human intelligence is comprised of numerous pieces of knowledge as well as processes for utilizing this knowledge to solve problems. Artificial intelligence seeks to emulate and surpass human intelligence in problem solving. Current research tends to be focused within narrow, well-defined domains, but new research is looking to expand this to create global intelligence. This chapter seeks to define the various fields that comprise artificial intelligence and look at the history of AI and suggest future research directions.


2020 ◽  
Vol 9 (2) ◽  
pp. 21 ◽  
Author(s):  
Martins O. Osifeko ◽  
Gerhard P. Hancke ◽  
Adnan M. Abu-Mahfouz

Smart, secure and energy-efficient data collection (DC) processes are key to the realization of the full potentials of future Internet of Things (FIoT)-based systems. Currently, challenges in this domain have motivated research efforts towards providing cognitive solutions for IoT usage. One such solution, termed cognitive sensing (CS) describes the use of smart sensors to intelligently perceive inputs from the environment. Further, CS has been proposed for use in FIoT in order to facilitate smart, secure and energy-efficient data collection processes. In this article, we provide a survey of different Artificial Intelligence (AI)-based techniques used over the last decade to provide cognitive sensing solutions for different FIoT applications. We present some state-of-the-art approaches, potentials, and challenges of AI techniques for the identified solutions. This survey contributes to a better understanding of AI techniques deployed for cognitive sensing in FIoT as well as future research directions in this regard.


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