scholarly journals IoT Technologies during and Beyond COVID-19: A Comprehensive Review

2021 ◽  
Vol 13 (5) ◽  
pp. 105
Author(s):  
Mohamed Yousif ◽  
Chaminda Hewage ◽  
Liqaa Nawaf
Keyword(s):  
Social Impact ◽  
Contact Tracing ◽  
Privacy And Security ◽  
Comprehensive Review ◽  
Iot Applications ◽  
Depth Analysis ◽  
Challenges And Opportunities ◽  
Potential Applications ◽  
Readiness Level ◽  
Improved Performance

The COVID-19 pandemic provided a much-needed sanity check for IoT-inspired frameworks and solutions. IoT solutions such as remote health monitoring and contact tracing provided support for authorities to successfully manage the spread of the coronavirus. This article provides the first comprehensive review of key IoT solutions that have had an impact on COVID-19 in healthcare, contact tracing, and transportation during the pandemic. Each sector is investigated in depth; and potential applications, social and economic impact, and barriers for mass adaptation are discussed in detail. Furthermore, it elaborates on the challenges and opportunities for IoT framework solutions in the immediate post-COVID-19 era. To this end, privacy and security concerns of IoT applications are analyzed in depth and emerging standards and code of practices for mass adaptation are also discussed. The main contribution of this review paper is the in-depth analysis and categorization of sector-wise IoT technologies, which have the potential to be prominent applications in the new normal. IoT applications in each selected sector are rated for their potential economic and social impact, timeline for mass adaptation, and Technology Readiness Level (TRL). In addition, this article outlines potential research directions for next-generation IoT applications that would facilitate improved performance with preserved privacy and security, as well as wider adaptation by the population at large.

A Study of the Cryptographic Technologies on Big Data Privacy and Security in E-Commerce

2019 ◽  
Vol 16 (8) ◽  
pp. 3587-3590
Author(s):  
Raheem Mafas ◽  
Manoj Jayabalan
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
State Of The Art ◽  
Not Given ◽  
Privacy And Security ◽  
Comprehensive Review ◽  
Goods And Services ◽  
Big Data Privacy ◽  
Reasonable Cost ◽  
Challenges And Opportunities

In this era, big data is the most common buzzword across different industries due to its capabilities of collecting, processing, storing and analysing data. The advancement of the E-Commerce paved the way for merchants and customers to meet online to satisfy their requirements by exchanging goods and services at a reasonable cost. The challenges and opportunities for big data on the emphasis of data privacy and security is a widely discussed topic among businesses especially E-Commerce merchants. There are several reviews available on emphasizing big data opportunities and challenges with regard to privacy and security. However, a comprehensive review on E-Commerce highlighting thematically on the tools and technologies is not given enough consideration. Therefore, the purpose of this study is to review the state-of-the-art technologies towards privacy and security in the E-Commerce platforms. The identified cryptographic technologies were also discussed with the rational standpoint to understand the viability to apply in the E-Commerce operations. The study concludes with an enlightening path from which the E-Commerce merchants can be vigilant on data privacy and security in future.

scholarly journals Privacy and Security for Resource-Constrained IoT Devices and Networks: Research Challenges and Opportunities

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1935 ◽  
Author(s):  
Shancang Li ◽  
Houbing Song ◽  
Muddesar Iqbal
Keyword(s):  
Cyber Physical Systems ◽  
Resource Constrained ◽  
Privacy And Security ◽  
Physical Systems ◽  
Iot Applications ◽  
Wide Range ◽  
Challenges And Opportunities ◽  
Iot Devices ◽  
Application Requirements ◽  
The Internet Of Things

With the exponential growth of the Internet of Things (IoT) and cyber-physical systems (CPS), a wide range of IoT applications have been developed and deployed in recent years. To match the heterogeneous application requirements in IoT and CPS systems, many resource-constrained IoT devices are deployed, in which privacy and security have emerged as difficult challenges because the devices have not been designed to have effective security features.

Comprehensive Review on Flexoelectric Energy Harvesting Technology: Mechanisms, Device Configurations, and Potential Applications

2021 ◽  
Author(s):  
Alekhika Tripathy ◽  
Balasubramaniam Saravanakumar ◽  
Smita Mohanty ◽  
Sanjay K. Nayak ◽  
Ananthakumar Ramadoss
Keyword(s):  
Energy Harvesting ◽  
Comprehensive Review ◽  
Potential Applications

scholarly journals “Seeing Is Believing”—In-Depth Analysis by Co-Imaging of Periodically-Poled X-Cut Lithium Niobate Thin Films

Crystals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 288
Author(s):  
Sven Reitzig ◽  
Michael Rüsing ◽  
Jie Zhao ◽  
Benjamin Kirbus ◽  
Shayan Mookherjea ◽  
...  
Keyword(s):  
Lithium Niobate ◽  
Second Harmonic ◽  
Imaging Techniques ◽  
Piezoresponse Force Microscopy ◽  
Periodically Poled ◽  
Near Surface ◽  
Domain Structures ◽  
Depth Analysis ◽  
Improved Performance ◽  
Quantum Optical

Nonlinear and quantum optical devices based on periodically-poled thin film lithium niobate (PP-TFLN) have gained considerable interest lately, due to their significantly improved performance as compared to their bulk counterparts. Nevertheless, performance parameters such as conversion efficiency, minimum pump power, and spectral bandwidth strongly depend on the quality of the domain structure in these PP-TFLN samples, e.g., their homogeneity and duty cycle, as well as on the overlap and penetration depth of domains with the waveguide mode. Hence, in order to propose improved fabrication protocols, a profound quality control of domain structures is needed that allows quantifying and thoroughly analyzing these parameters. In this paper, we propose to combine a set of nanometer-to-micrometer-scale imaging techniques, i.e., piezoresponse force microscopy (PFM), second-harmonic generation (SHG), and Raman spectroscopy (RS), to access the relevant and crucial sample properties through cross-correlating these methods. Based on our findings, we designate SHG to be the best-suited standard imaging technique for this purpose, in particular when investigating the domain poling process in x-cut TFLNs. While PFM is excellently recommended for near-surface high-resolution imaging, RS provides thorough insights into stress and/or defect distributions, as associated with these domain structures. In this context, our work here indicates unexpectedly large signs for internal fields occurring in x-cut PP-TFLNs that are substantially larger as compared to previous observations in bulk LN.

scholarly journals The Impact of COVID-19 on Hospitality Industry in Greece and Its Treasured Santorini Island

2021 ◽  
Vol 13 (14) ◽  
pp. 7906
Author(s):  
Nikola Medová ◽  
Lucie Macková ◽  
Jaromir Harmacek
Keyword(s):  
Social Impact ◽  
Tourism Sector ◽  
Challenges And Opportunities ◽  
Multiple Variables ◽  
Hospitality Sector ◽  
Tourism And Hospitality ◽  
The Impact ◽  
Further Development

This paper focuses on the dynamic of the recent upheaval in the tourism and hospitality sector due to the COVID-19 epidemic in Greece and Santorini island. It uses the case study of a country one-fourth of whose GDP consists of tourism. We compare the available statistical data showing the change in variables in the previous years with 2020 and look into the new challenges and opportunities posed by the drop in the numbers of visitors and flights. We focus mainly on the economic and social impact on the destination and possible future scenarios for further development in the area. Data show a significant effect of the pandemic on multiple variables, such as the long-term trend of the importance of tourism sector in GDP in Greece, the number of flights and visitors to Greece and Santorini island, and the contribution of tourism and travel to GDP. Based on the available data, we also construct three foresight scenarios that describe the possible futures for Santorini island in terms of the pandemic evolution. These scenarios may help various stakeholders and policymakers to be better prepared for different developments that may appear.

Artificial intelligence research in agriculture: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amit Sood ◽  
Rajendra Kumar Sharma ◽  
Amit Kumar Bhardwaj
Keyword(s):  
Artificial Intelligence ◽  
Peer Review ◽  
Diffusion Of Innovation ◽  
Comprehensive Review ◽  
Content Type ◽  
Design Elements ◽  
Extant Literature ◽  
Use Of Technology ◽  
Challenges And Opportunities ◽  
Market Factors

PurposeThe purpose of this paper is to provide a comprehensive review on the academic journey of artificial intelligence (AI) in agriculture and to highlight the challenges and opportunities in adopting AI-based advancement in agricultural systems and processes.Design/methodology/approachThe authors conducted a bibliometric analysis of the extant literature on AI in agriculture to understand the status of development in this domain. Further, the authors proposed a framework based on two popular theories, namely, diffusion of innovation (DOI) and the unified theory of acceptance and use of technology (UTAUT), to identify the factors influencing the adoption of AI in agriculture.FindingsFour factors were identified, i.e. institutional factors, market factors, technology factors and stakeholder perception, which influence adopting AI in agriculture. Further, the authors indicated challenges under environmental, operational, technological, economical and social categories with opportunities in this area of research and business.Research limitations/implicationsThe proposed conceptual model needs empirical validation across countries or states to understand the effectiveness and relevance.Practical implicationsPractitioners and researchers can use these inputs to develop technology and business solutions with specific design elements to gain benefit of this technology at larger scale for increasing agriculture production.Social implicationsThis paper brings new developed methods and practices in agriculture for betterment of society.Originality/valueThis paper provides a comprehensive review of extant literature and presents a theoretical framework for researchers to further examine the interaction of independent variables responsible for adoption of AI in agriculture.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2020-0448

Theory of change: Driving a digital school in rural Pakistan

First Monday ◽  
2021 ◽  
Author(s):  
Ashir Ahmed ◽  
Jason Sargent
Keyword(s):  
Young Children ◽  
Developing Country ◽  
Rural Areas ◽  
Digital Literacy ◽  
Social Impact ◽  
Theory Of Change ◽  
Study Approach ◽  
Rural Pakistan ◽  
Depth Analysis ◽  
Innovative Tool

This paper reports the findings of the initial phase of a longitudinal study that aims to investigate barriers to digital literacy in rural Pakistan. The research employs the Theory of Change to plan various stages of a digital literacy program for young children living in a remote area of Pakpattan, Pakistan. A Digital Access Vehicle (DAVe) was deployed as an innovative tool to introduce digital literacy for those who were unable to travel to the project’s NGO partner headquarters to access DAVe’s array of digital technologies. An interpretive case study approach is used to perform in-depth analysis of the subject under investigation by conducting one-on-one interviews and focus groups with key informants. The contributions of this research are twofold: (a) it operationalizes the Theory of Change to systematically plan a social impact project in a resource-constrained developing country; and (b) it creates a better understanding of barriers hindering digital literacy of young children in rural areas of a developing country such as Pakistan.

High national acceptance for COVID-19 contact tracing technologies in Taiwan (Preprint)

2021 ◽  
Author(s):  
Paul M. Garrett ◽  
Yuwen Wang ◽  
Joshua P. White ◽  
Yoshihisa Kashima ◽  
Simon Dennis ◽  
...  
Keyword(s):  
Technology Acceptance ◽  
Contact Tracing ◽  
Virus Spread ◽  
Security Measures ◽  
Contributing Factors ◽  
Privacy And Security ◽  
Social Distancing ◽  
The Public ◽  
Privacy Measures ◽  
Credible Intervals

BACKGROUND Governments worldwide have introduced COVID-19 tracing technologies. Taiwan, a world leader in controlling the virus’ spread, has introduced the Taiwan ‘Social Distancing App’ to facilitate COVID-19 contact tracing. However, for these technologies to be effective, they must be accepted and used by the public. OBJECTIVE Our study aimed to determine public acceptance for three hypothetical tracing technologies: a centralized Government App, a decentralized Bluetooth App (e.g., Taiwan’s Social Distancing App), and a Telecommunication tracing technology; and model what factors contributed to their acceptance. METHODS Four nationally representative surveys were conducted in April 2020 sampling 6,000 Taiwanese residents. Perceptions and impacts of COVID-19, government effectiveness, worldviews, and attitudes towards and acceptance of one-of-three hypothetical tracing technologies were assessed. RESULTS Technology acceptance was high across all hypothetical technologies (67% - 73%) and improved with additional privacy measures (82% - 88%). Bayesian modelling (using 95% highest density credible intervals) showed data sensitivity and perceived poor COVID-19 policy compliance inhibited technology acceptance. By contrast, technology benefits (e.g., returning to activities, reducing virus spread, lowering the likelihood of infection), higher education, and perceived technology privacy, security, and trust, were all contributing factors to overall acceptance. Bayesian ordinal probit models revealed higher COVID-19 concern for other people than for one’s self. CONCLUSIONS Taiwan is currently using a range of technologies to minimize the spread of COVID-19 as the country returns to normal economic and social activities. We observed high acceptance for COVID-19 tracing technologies among the Taiwanese public, a promising and necessary finding for the successful introduction of Taiwan’s new ‘Social Distancing App’. Policy makers may capitalize on this acceptance by focusing attention towards the App’s benefits, privacy and security measures, making the App’s privacy measures transparent to the public, and emphasizing App uptake and compliance among the public. CLINICALTRIAL Not applicable.

Procedural extensions of SQL

2021 ◽  
Vol 14 (8) ◽  
pp. 1378-1391
Author(s):  
Surabhi Gupta ◽  
Karthik Ramachandra
Keyword(s):  
Real World ◽  
Experimental Evaluation ◽  
New Work ◽  
Research Challenges ◽  
Depth Analysis ◽  
Challenges And Opportunities ◽  
Procedural Code

Procedural extensions of SQL have been in existence for many decades now. However, little is known about their magnitude of usage and their complexity in real-world workloads. Procedural code executing in a RDBMS is known to have inefficiencies and limitations; as a result there have been several efforts to address this problem. However, the lack of understanding of their use in real workloads makes it challenging to (a) motivate new work in this area, (b) identify research challenges and opportunities, and (c) demonstrate impact of novel work. We aim to address these challenges with our work. In this paper, we present the results of our in-depth analysis of thousands of stored procedures, user-defined functions and triggers taken from several real workloads. We introduce SQL-ProcBench , a benchmark for procedural workloads in RDBMSs. SQL-ProcBench has been created using the insights derived from our analysis, and thus represents real workloads. Using SQL-ProcBench, we present an experimental evaluation on several database engines to understand and identify research challenges and opportunities. We emphasize the need to work on these interesting and relevant problems, and encourage researchers to contribute to this area.

IIOT and Real Time Data Analytics - Maximizing the Impact on Safety and Productivity

2021 ◽  
Author(s):  
Ryan Daher ◽  
Nesma Aldash
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Data Analytics ◽  
Contact Tracing ◽  
Time Data ◽  
Seamless Integration ◽  
Location Services ◽  
Industrial Internet ◽  
Potential Applications ◽  
The Impact

Abstract With the global push towards Industry 4.0, a number of leading companies and organizations have invested heavily in Industrial Internet of Things (IIOT's) and acquired a massive amount of data. But data without proper analysis that converts it into actionable insights is just more information. With the advancement of Data analytics, machine learning, artificial intelligence, numerous methods can be used to better extract value out of the amassed data from various IIOTs and leverage the analysis to better make decisions impacting efficiency, productivity, optimization and safety. This paper focuses on two case studies- one from upstream and one from downstream using RTLS (Real Time Location Services). Two types of challenges were present: the first one being the identification of the location of all personnel on site in case of emergency and ensuring that all have mustered in a timely fashion hence reducing the time to muster and lessening the risks of Leaving someone behind. The second challenge being the identification of personnel and various contractors, the time they entered in productive or nonproductive areas and time it took to complete various tasks within their crafts while on the job hence accounting for efficiency, productivity and cost reduction. In both case studies, advanced analytics were used, and data collection issues were encountered highlighting the need for further and seamless integration between data, analytics and intelligence is needed. Achievements from both cases were visible increase in productivity and efficiency along with the heightened safety awareness hence lowering the overall risk and liability of the operation. Novel/Additive Information: The results presented from both studies have highlighted other potential applications of the IIOT and its related analytics. Pertinent to COVID-19, new application of such approach was tested in contact tracing identifying workers who could have tested positive and tracing back to personnel that have been in close proximity and contact therefore reducing the spread of COVID. Other application of the IIOT and its related analytics has also been tested in crane, forklift and heavy machinery proximity alert reducing the risk of accidents.

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