scholarly journals Utility of Digital Technology in Tackling the COVID-19 Pandemic: A Current Review

2020 ◽  
Author(s):  
Prashanth Kulkarni ◽  
Shruthi Kodad ◽  
Manjappa Mahadevappa ◽  
Sushanth Kulkarni
Keyword(s):  
Public Health ◽  
Digital Technology ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Vital Role ◽  
Current Review ◽  
Coronavirus Infection ◽  
Block Chain ◽  
Public Health Strategies ◽  
A Current

The Coronavirus Disease (COVID-19) pandemic has rampaged across the globe, creating a major public health emergency and economic crisis. In this pandemic, digital technology tools such as Artificial Intelligence (AI), big-data analytics, block chain technology, robotics and drone technology are playing a vital role and are increasingly being utilised by many countries for devising major public health strategies. This article discusses the utility of digital technology in combating coronavirus infection and also highlights the current limitations and future prospects of these tools.

scholarly journals Big Data, Decision Models, and Public Health

2020 ◽  
Vol 17 (18) ◽  
pp. 6723
Author(s):  
Chien-Lung Chan ◽  
Chi-Chang Chang
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Decision Models ◽  
Medical Decision ◽  
Mining Machine ◽  
Special Issue ◽  
Trade Offs

Unlike most daily decisions, medical decision making often has substantial consequences and trade-offs. Recently, big data analytics techniques such as statistical analysis, data mining, machine learning and deep learning can be applied to construct innovative decision models. With complex decision making, it can be difficult to comprehend and compare the benefits and risks of all available options to make a decision. For these reasons, this Special Issue focuses on the use of big data analytics and forms of public health decision making based on the decision model, spanning from theory to practice. A total of 64 submissions were carefully blind peer reviewed by at least two referees and, finally, 23 papers were selected for this Special Issue.

scholarly journals Civil Society Organizations and Global Health

2021 ◽  
Vol 21 (3) ◽  
pp. 135-152
Author(s):  
Soma Hewa
Keyword(s):  
Public Health ◽  
Civil Society ◽  
Sri Lanka ◽  
Rockefeller Foundation ◽  
Community Support ◽  
Vital Role ◽  
Civil Society Organizations ◽  
Epidemic Disease ◽  
Wide Range ◽  
Public Health Strategies

Civil society organizations are playing a vital role in capacity building at the grassroots level around the world. Rockefeller philanthropy pioneered this civic responsibility, both at home and abroad, in controlling epidemic disease and developing public health. Since its inception in 1913, the Rockefeller Foundation had been involved in a wide range of public health programs in Sri Lanka (previously known as Ceylon), which was regarded as the key to the Foundation’s activities in Asia. Rockefeller philanthropy arrived in Sri Lanka during the European colonial rule in the early twentieth century and received a hostile reception from the colonial administration. The Foundation’s officials acted cautiously and listened to local citizens in developing public health strategies. Such efforts succeeded not only in combating disease and promoting health, but also achieving sustained community support. This paper is a critical inquiry of the program and its role in the development of a modern public health network in Sri Lanka.

scholarly journals Privacy-aware Big Data Analytics as a service for public health policies in smart cities

2018 ◽  
Vol 39 ◽  
pp. 68-77 ◽  
Author(s):  
Marco Anisetti ◽  
Claudio Ardagna ◽  
Valerio Bellandi ◽  
Marco Cremonini ◽  
Fulvio Frati ◽  
...  
Keyword(s):  
Public Health ◽  
Big Data ◽  
Data Analytics ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Health Policies ◽  
Public Health Policies

Human-Computer Interaction With Big Data Analytics

2022 ◽  
pp. 1578-1596
Author(s):  
Gunasekaran Manogaran ◽  
Chandu Thota ◽  
Daphne Lopez
Keyword(s):  
Big Data ◽  
Human Computer Interaction ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Vital Role ◽  
Data Systems ◽  
Real Time Analysis ◽  
Big Data Systems ◽  
Almost All ◽  
Computer Interaction

Big Data has been playing a vital role in almost all environments such as healthcare, education, business organizations and scientific research. Big data analytics requires advanced tools and techniques to store, process and analyze the huge volume of data. Big data consists of huge unstructured data that require advance real-time analysis. Thus, nowadays many of the researchers are interested in developing advance technologies and algorithms to solve the issues when dealing with big data. Big Data has gained much attention from many private organizations, public sector and research institutes. This chapter provides an overview of the state-of-the-art algorithms for processing big data, as well as the characteristics, applications, opportunities and challenges of big data systems. This chapter also presents the challenges and issues in human computer interaction with big data analytics.

Big Data Analytics Platforms for Electric Vehicle Integration in Transport Oriented Smart Cities

2020 ◽  
pp. 833-854
Author(s):  
Md Muzakkir Hussain ◽  
M.M. Sufyan Beg ◽  
Mohammad Saad Alam ◽  
Shahedul Haque Laskar
Keyword(s):  
Big Data ◽  
Electric Vehicle ◽  
Carbon Footprint ◽  
Smart Grids ◽  
Data Analytics ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Vital Role ◽  
Key Players ◽  
Distinguishing Features

Electric vehicles (EVs) are key players for transport oriented smart cities (TOSC) powered by smart grids (SG) because they help those cities to become greener by reducing vehicle emissions and carbon footprint. In this article, the authors analyze different use-cases to show how big data analytics (BDA) can play vital role for successful electric vehicle (EV) to smart grid (SG) integration. Followed by this, this article presents an edge computing model and highlights the advantages of employing such distributed edge paradigms towards satisfying the store, compute and networking (SCN) requirements of smart EV applications in TOSCs. This article also highlights the distinguishing features of the edge paradigm, towards supporting BDA activities in EV to SG integration in TOSCs. Finally, the authors provide a detailed overview of opportunities, trends, and challenges of both these computing techniques. In particular, this article discusses the deployment challenges and state-of-the-art solutions in edge privacy and edge forensics.

scholarly journals IoT Puts a New Spin on Bearings

2018 ◽  
Vol 140 (07) ◽  
pp. 42-47 ◽  
Author(s):  
Alan S. Brown
Keyword(s):  
Digital Technology ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Low Cost ◽  
Big Data Analytics ◽  
The Internet ◽  
Manufacturing Companies ◽  
Bearing Life ◽  
Mechanical Devices ◽  
The Internet Of Things

As anyone who ever had a bearing fail knows, durability counts. However some bearing makers believe that predictability is more important than longer bearing life. By harnessing the Internet of Things (IoT) and other Industry 4.0 technologies—low-cost sensors, Big Data analytics, and machine learning—manufacturing companies want to catapult one of the world’s oldest mechanical devices into the digital future. In fact, bearings are emerging as a poster child for Industry 4.0. Yet this heady mixture of digital technology and physical products is also disrupting how companies monitor, operate, and service rotating equipment; the way they sell and service products; and who they partner with and compete against. This article delves into how bearing makers are embracing this disruption.

scholarly journals Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework

2020 ◽  
Vol 17 (17) ◽  
pp. 6161 ◽  
Author(s):  
Qiong Jia ◽  
Yue Guo ◽  
Guanlin Wang ◽  
Stuart J. Barnes
Keyword(s):  
Public Health ◽  
Big Data ◽  
Data Analytics ◽  
Close Contact ◽  
Big Data Analytics ◽  
Contact Screening ◽  
Negative Impacts ◽  
Effective Use ◽  
And Control ◽  
Clear Information

Major public health incidents such as COVID-19 typically have characteristics of being sudden, uncertain, and hazardous. If a government can effectively accumulate big data from various sources and use appropriate analytical methods, it may quickly respond to achieve optimal public health decisions, thereby ameliorating negative impacts from a public health incident and more quickly restoring normality. Although there are many reports and studies examining how to use big data for epidemic prevention, there is still a lack of an effective review and framework of the application of big data in the fight against major public health incidents such as COVID-19, which would be a helpful reference for governments. This paper provides clear information on the characteristics of COVID-19, as well as key big data resources, big data for the visualization of pandemic prevention and control, close contact screening, online public opinion monitoring, virus host analysis, and pandemic forecast evaluation. A framework is provided as a multidimensional reference for the effective use of big data analytics technology to prevent and control epidemics (or pandemics). The challenges and suggestions with respect to applying big data for fighting COVID-19 are also discussed.

scholarly journals Digitization, Epistemic Proximity, and the Education System: Insights from a Bibliometric Analysis

2021 ◽  
Vol 14 (6) ◽  
pp. 267
Author(s):  
Ugo Fiore ◽  
Adrian Florea ◽  
Claudiu Vasile Kifor ◽  
Paolo Zanetti
Keyword(s):  
Education System ◽  
Computational Intelligence ◽  
Digital Technology ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Support Organizations ◽  
Scopus Database ◽  
Similarities And Differences

Advances in IoT, AI, Cyber-Physical Systems, Computational Intelligence, and Big Data Analytics require organizations and workforce to be able and willing to learn how to interact with digital technology. In organizations, coordination and cooperation between actors with expertise in business and technology is fundamental, but integration is hard without understanding the terminology and problems of the interlocutor. Epistemic proximity becomes prominent, underlining the importance of an education focused on flexibility, willingness to cope with the unknown, and interdisciplinarity. The main goal of this work is to provide a perspective on how the education system is evolving to support organizations in the digitization era through a quantitative analysis of literature. More than 170,000 papers were selected from the Scopus database, matching a wide set of keywords related with innovation, problem solving, and organizational change. Patterns in the co-occurrence of keywords were studied. In addition, similarities and differences in the distribution of relevant themes across disciplinary areas, as well as their evolution since 2000, were analyzed. Academic interest is found to be generally increasing over the years in all disciplines, although considerable fluctuations can be observed. This variation is found to be nonuniform in the macroareas.

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