Exploring the benefits and challenges of Internet of Things (IoT) during Covid-19: a case study of Bangladesh

Performance management algorithm of financial shared service center based on Internet of Things public cloud privacy protection

The Internet of Things (IoT) refers to the use of various communication technologies to achieve the interconnection of everything in cyberspace, and to achieve smart home and intelligent transportation, thus generating unprecedented amounts of data. In the financial sharing center, all businesses can extract effective data from these massive databases for analysis, and use data analysis tools to collect business, financial, human, process, knowledge and social data. At present, various types of IT (Internet Technology) systems have been widely used in financial sharing centers. However, a large number of sensitive data have also been generated. In order to protect these sensitive data, there is a high requirement for the personal information of IT system operation and financial sharing center personnel. In order to protect user data privacy, the optimal and most effective use of IT systems is an important issue that must be considered in privacy management. At present, there are many algorithms to protect data and privacy, but the effect is not ideal. Considering the balance between privacy issues, this paper proposed a K-means clustering algorithm based on IoT public cloud privacy protection technology to analyze the performance management of financial sharing center. The research results showed that before the improvement, the average number of employees who were dissatisfied with the post training ability and information platform construction ability of the financial sharing center was 57.9 and 57.8% respectively, more than half of them. After the improvement of IoT based public cloud privacy protection, the average number of employees dissatisfied with the post training ability and information platform construction ability of the financial sharing center was 5 and 3.9%, far less than the data prior to the improvement. It showed that IoT public cloud privacy protection was conducive to the performance management of the financial sharing center, and the relationship between the two was positive.

A Statistical Synopsis of COVID-19 Components and Descriptive Analysis of Their Socio-Economic and Healthcare Aspects in Bangladesh Perspective

The aim of the work is to analyze the socio-economic and healthcare aspects that arise in the contemporary COVID-19 situation from Bangladesh perspective. We elaborately discuss the successive COVID-19 occurrences in Bangladesh with consequential information. The components associated with the COVID-19 commencement and treatment policy with corresponding features and their consequences are patently delineated. The effect of troublesome issues related to the treatment is detailed with supporting real-time data. We elucidate the applications of modern technologies advancement in epidemiological aspects and their existent compatibility in Bangladesh. We statistically analyze the real-time data through figurative and tabular approaches. Some relevant measures of central tendency and dispersion are utilized to explore the data structure and its observable specifications. For a clear manifestation, Z- scores of the COVID-19 components are analyzed through the Box-Whisker plot. We have discovered that the gathered data exhibit features that are unsatisfactory for the normal distribution, are highly positively skewed, and are predominated by the earliest occurrences. Infections and deaths were initially lower than the global average, but they drastically rose in the first quarter of 2021 and persisted for the remainder of the year. Substantial preventive results were produced by the region-wisetime-worthy moves. In the fourth quarter of 2021, the infections and deaths noticeably decreased, and the number of recoveries was highly significant. In the middle of 2022, a lethal rise in infections was observed in Bangladesh and that was quickly stabilized, and the pandemic ingredients were under control. According to our assessment, some concluding remarks are made at the end of this work.

Perception study of perceived value and social influence of digital health services in Indonesia

BACKGROUND

Healthtech has become a nascent sector of the internet economy since the emergence of the COVID-19 pandemic in 2020. Telemedicine features are facilitated, such as teleconsultation, e-diagnosis, e-prescribing, and e-pharmacy. However, the intention to use digital health services in Indonesia is still underdeveloped though the sales of other risk-free e-commerce products are high enough.

OBJECTIVE

This study aims to assess the human perception of perceived value and social influences regarding the intention to use digital health services.

METHODS

Google Forms web link is employed to disseminate a set of 4-Point Likert scale questionnaires. In total, 364 complete responses are collected. A descriptive approach is employed to process the data using Microsoft Excel and SPSS software. Validity and reliability are quantified using the item total-correlation method and Cronbach's Alpha coefficient.

RESULTS

Only 87 respondents (24%) ever used digital health services, of which Halodoc (92%) is the most preferred application, and teleconsultation became the most popular service to access. Out of four, the average score is 3.16 for perceived value and 2.86 for the social influence dimension.

CONCLUSION

Most respondents, not dependent on user experience, perceive more values obtained using digital health services, such as time and money savings, convenience, flexible order time, undiscovered identity, adventurous experience, and enjoyment. Another finding of this research proves that some social influences from family, friends, and mass media also bring effect to amplify the intention to use. A low level of trust is assumed to be the cause of a small number of users.

Investigating the impact of IoT-Based smart laboratories on students' academic performance in higher education

The enormous developments in technology have transformed the way we interact with the world around us. Among the extensive yet advanced technological interventions, one of the sophisticated expansions is the appearance of the Internet of Things, a tool for developing connections of physical objects to the virtual world using small-sized sensors and certain internet protocols to lessen human interventions. The domain of education has also adopted these technological services to move from traditional methods to sophisticated and advanced teaching and learning approaches to cope with learning needs and raise quality. This paper intends to conceptualize the impact of integrating IoT in higher education to increase students' academic performance in the engineering domain through the integration of smart laboratories. Several international studies were selected and thoroughly reviewed using the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analysis to build sophisticated insights regarding the topic in terms of its conceptual as well as practical foundations. The key insights gathered through reviewed studies indicate that the Internet of things-based laboratories have significant advantages in uplifting students' academic performance through interaction, motivation, creativity, and practical learning. The integration of the Internet of things in higher educational institutes improves students' academic performance because it allows them to engage in authentic tasks and experience practical and active learning.

An Improved Epidemiological Model for the Underprivileged People in the Contemporary Pandemics

In this work, we introduce an improved form of the basic SEIRD model based on Python simulation for the troublesome people who are oblivious about the contemporary pandemics due to diverse social impediments, especially those economically underprivileged. In the extant epidemiological models, some unorthodox issues are yet to be considered, such as poverty, illiteracy, and carelessness towards health issues, significantly influencing the data modeling. Our focus is to overcome these issues by adding two more branches, for instance, uncovered and apathetic people, which significantly influence the practical purposes. For the data simulation, we have used the Python-based algorithm that trains the desired system based on a set of real-time data with the proposed model and provides predicted data with a certain level of accuracy. Comparative discussions, statistical error analysis, and correlation-regression analysis have been introduced to validate the proposed epidemiological model. To show the numerical evidence, the investigation comprised the figurative and tabular modes for both real-time and predicted data. Finally, we discussed some concluding remarks based on our findings.

Evaluating the Potential and Challenges of IoT in Education and Other Sectors during the COVID-19 Pandemic: The Case of Bangladesh

The Internet of Things (IoT) adoption affects different sectors immensely, especially during Covid-19. This study mainly examines the benefits and challenges experienced in Bangladesh's education, and corporate and service sectors while using IoT services during COVID-19. Data collection was performed using a convenient random sampling method and distributing questions online. Two hundred sixty completed responses were analyzed, where 40% of responses were from the education sector, and 60% were from the corporate and service sector. The research method was quantitative and empirical. The study reveals that people find saving time the most potential in education sector, whereas, in the corporate and service sector, the topmost benefit of using IoT services is that it helps strictly maintain physical distance. Conversely, the most significant challenges people face in both sectors are that the IoT increases social distance and reduces individual communication. Nevertheless, people in both sectors have a positive attitude towards using IoT in the future. The findings have practical implications for business professionals, academic scholars, and other associated parties keen to identify IoT impact during the pandemic.