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The purpose of this paper is to develop a blockchain-based data capture and transmission system that will collect real-time power consumption data from a household electrical appliance and transfer it securely to a local server for energy analytics such as forecasting.

The data capture system is composed of two current transformer (CT) sensors connected to two different electrical appliances. The CT sensors send the power readings to two Arduino microcontrollers which in turn connect to a Raspberry-Pi for aggregating the data. Blockchain is then enabled onto the Raspberry-Pi through a Java API so that the data are transmitted securely to a server. The server provides real-time visualization of the data as well as prediction using the multi-layer perceptron (MLP) and long short term memory (LSTM) algorithms.

The results for the blockchain analysis demonstrate that when the data readings are transmitted in smaller blocks, the security is much greater as compared with blocks of larger size. To assess the accuracy of the prediction algorithms data were collected for a 20 min interval to train the model and the algorithms were evaluated using the sliding window approach. The mean average percentage error (MAPE) was used to assess the accuracy of the algorithms and a MAPE of 1.62% and 1.99% was obtained for the LSTM and MLP algorithms, respectively.

A detailed performance analysis of the blockchain-based transmission model using time complexity, throughput and latency as well as energy forecasting has been performed.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

The purpose of this study was to explore the potential benefits of Coriandrum sativum (C. sativum) on anxiety, depression, sleep quality and memory among students.

This randomized controlled trial involved university students aged 18–25 years, who had no known allergies to C. sativum or were using psychotropic medication. After giving informed consent, participants were randomly assigned using a computer-generated random sequence to either 500 mg C. sativum seeds or a placebo. Primary outcomes measured changes in memory (prospective and retrospective memory questionnaire [PRMQ]), anxiety and depression (Hospital Anxiety and Depression Scale), while secondary outcomes assessed sleep quality (Pittsburgh sleep quality inventory [PSQI]).

A sample of 86 students with a mean age of 20.05 ± 1.6 years was selected for the study. Initial assessments ensured no significant differences in demographic or study variables between the control and intervention groups. Statistical analysis revealed significant improvements in memory (PRMQ: p = 0.006), anxiety (Hospital Anxiety Scale: p = 0.04) and depression (Hospital Depression Scale: p = 0.002), as well as in sleep quality (PSQI: p = 0.03) in the group receiving C. sativum compared to the control group.

This research offers initial insights into the potential benefits of C. sativum intake, specifically its role in enhancing memory performance and mitigating anxiety among student populations. The results present a compelling case for further research in this domain to solidify these preliminary conclusions.

The purpose of this study is to analyze the determinants influencing Japanese consumers’ behavior toward the purchase of 5G smartphones.

Empirical data was collected through an online survey of 320 Japanese respondents from ages 20 to 59. Data was analyzed by exploratory factor analysis, confirmatory factor analysis and multiple regression analysis.

The results indicate that hedonic value, user interface and price value (PV) positively influence attitude toward 5G smartphone purchase, while utilitarian value does not. In addition, the mediation effect of social influence (SI) is found to increase those positive effects. Male and female consumers displayed differences in the determinants, showcasing the effect of gender on attitude and behavior.

To the best of the authors’ knowledge, this study is the first research to analyze Japanese consumers’ behaviors’ toward 5G smartphone purchase. Past research for 3G/4G smartphones supported that usefulness positively influenced consumers’ behavior toward smartphones, so usefulness of 5G (e.g. high speed) was expected to be a factor to influence consumer behaviors’ toward 5G smartphones. However, this research reveals that a simple tagline emphasizing such usefulness may not be convincing enough to promote the 5G smartphones to Japanese consumers. Alternatively, the research indicates that introducing the concepts of joyfulness, improved HV and greater PV of the 5G smartphone could attract more consumers in Japan. In addition, SI could enhance the perception of the various benefits of 5G smartphones.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

The purpose of this paper is to explain how enterprise resource planning (ERP) implementation evolves by cloud computing in different industries with different delivery models of cloud ERP. This paper also investigates infrastructure as a service (IaaS) as a delivery approach for cloud ERP. Case research on IaaS is rarely found in the literature. In addition, this paper intends to reveal how this transformation from on-premises to the cloud would influence the ERP implementation process.

A multiple-case study is conducted to identify the different deployed models of cloud ERP systems in the implementation projects. The influences of emerging cloud computing technology on ERP implementation are investigated by interviewing consultants related to the projects.

The findings illustrate that not only software as a service (SaaS) but also IaaS and platform as a service cloud computing services are widely applied in cloud ERP implementation. This study also indicates that certain technical limitations of cloud ERP might have a positive effect on the outcome of ERP implementation.

This study investigates how cloud computing influences ERP implementation from different aspects. The result identifies both SaaS and IaaS as two different approaches widely adopted in cloud ERP implementation. Besides, this study has discussed in-depth and analyzed these two cloud ERP paradigms in five factors, including functionality, performance, portability, security, cost and customization. The classification and suggestions are original to the literature.

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.

The purpose of this study is to analyze the robot trends of the next generation.

This paper is divided into two sections: the key modern technology on which Europe's robotics industry has built its foundation is described. Then, the next key megatrends were analyzed.

Artificial intelligence (AI) and robotics are technologies of major importance for the development of humanity. This time is mature for the evolution of industrial and service robots. The perception of robot use has changed from threading to aiding. The cost of mass production of technological devices is decreasing, while a rich set of enabling technologies is under development. Soft mechanisms, 5G and AI have enabled us to address a wide range of new problems. Ethics should guide human behavior in addressing this newly available powerful technology in the right direction.

The paper describes the impact of new technology, such as AI and soft robotics. The world of work must react quickly to these epochal changes to enjoy their full benefits.

The purpose of this paper is to examine the implications of the COVID-19 pandemic on internal auditing as the pandemic forced individual internal auditors and audit teams to conduct the work remotely.

Five in-depth semi-structured interviews of internal audit experts that work in German retail and manufacturing industry were conducted between February and April 2021.

The authors find that the importance of audit technologies did not change significantly due to the pandemic, as audit technologies were already an integral part of internal audits. Interestingly, the transition to remote audits occurred with remarkable speed and efficiency. The presence of well-functioning information and communication technologies emerges as a critical facilitator for effective remote communication, collaboration and data exchange. However, audit technologies can only partially replace physical on-site examinations and human interaction. The main challenges of remote audits are related to the auditing of non-digitalized processes and the inherent limitations of auditee interviews and interactions.

The authors' interview approach does not allow to cover variations between industries and between countries. While internal audit experts provided notably consistent responses during the interviews, acknowledging that the sample size is very small is important.

The COVID-19 pandemic serves as a catalyst for increased digitalization and technology adoption within the realm of internal auditing. A hybrid approach combining the benefits of on-site and remote audits is expected to prevail in the future.

The paper is among the first to document the effects of the COVID-19 pandemic on the work of internal auditing using field-based research methods.

This paper aims to draw lessons for telecommunications (telecom) network deployment in India, from a study of policy and regulatory approaches taken by other federal administrations in streamlining processes for site clearances, grant of rights of way (RoW) and approvals for local infrastructure deployment and sharing. With the urgent need for setting up small cells and rapid fiberisation of networks in the 5G era, the importance of such processes has gained prominence.

The authors adopt qualitative thematic content analysis with three-tier coding and classification to identify themes in archival and current documentary data and information obtained from subject-matter experts in the countries studied.

Formulation and implementation of telecom policy is led by national governments. However, national telecom administrations, in recognition of new needs, have co-opted states and local authorities as partners in development of telecom networks, providing the overall framework, guidance and appropriate incentives where required.

This cooperative model could work well in India, where telecom policy making and regulation is the prerogative of the central government, but administration of RoW and local clearances for cable laying, tower siting and associated infrastructure activities for expanding telecom networks are left to decentralised decision-making in the states and local bodies.

This research attempts to sytematise, thematise and draw cross-country comparisons to inform regulatory and administrative policy for 5G infrastructure rollout in India.