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Social, Medical, and Educational Applications of IoT to Assist Visually Impaired People
General daily tasks have always been a problem for visually impaired people. Identification of daily objects becomes a hectic task. Traditional methods such as a walking stick and a guide dog have been helpful to the visually impaired for basic navigation. Such, methods have a lot of limitations and often fail under varied situations. Technologies such as Computer Vision and Pattern Recognition (CVPR), Image Processing (IP) Internet of Things (IoT), etc. have made a major contribution to overcoming the limitations. IoT brings a lot of technical and automated solutions to assist the visually impaired people. Data science and analytics are a major part of the process. Data accumulated via various sensors can be processed and used to identify obstacles and enhance basic navigation using haptic and voice feedback. Raw data goes through a series of analysis and refinement. This is then processed into a form which is understandable to the system and can be directly interpreted to perform various components of an application. These applications involve education, navigation, entertainment, security, consumer, etc. These applications are across various verticals of technologies differing in terms of hardware, software, and protocols. Various economically feasible and accurate solutions are now available. While, optimization remains an issue. These devices have generally been very helpful to ease the lives of visually impaired people. The main aim of this article is to provide essential details related to real-world applications of IoT in the field of education, healthcare, entertainment, security, navigation, and solutions to address the daily challenges faced by visually impaired people. The structure of the article includes introduction to IoT, applications of IoT in modern era is dealt in detail in Sect.10.1. Followed by hardware device and communication technologies in Sect.10.2. Section10.3 deals with state of art which focus majorly on research contributions related to applications of IoT and smart devices benefiting the lives of visually impaired. Section10.4 incorporates the future scope and concludes with a summary in Sect.10.5. The article covers more than 30 research contributions in the pastten years which includes journal papers, conference papers and patents which provide a detailed and clear view on the research being carried out in the field of IoT to help the visually impaired. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Impact of the COVID-19 outbreak on the currency exchanges of selected countries
The paper aims to analyse the impact of the COVID outbreak on the currency market. The study considers spot rates of seven major currencies (i.e., EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/CAD, USD/CHF, and CHF/JPY). To capture the impact of the outbreak on returns and the volatility of returns of seven currencies during pandemic, the study has segregated in two window periods (i.e., pre- [1st Jan 2019 to 31st Dec, 2019] and post-outbreak of COVID-19 [1st Jan, 2020 to 22nd Dec, 2020]). The study has applied various methods and models (i.e., econometric-based compounded annual growth rate [CAGR], dummy variable regression, and generalized autoregressive conditional heteroskedasticity [GARCH]). The result of the study captures the negative impact of the COVID-19 pandemic on three currencies-USD/JPY, AUD/USD, and USD/CHF-and positive significant impact on EUR/USD, GBP/USD, USD/CAD, and CHF/JPY. Investors can take short position in these while having long position in other currencies. The inferences drawn from the analysis are providing insight to investors and hedgers. Copyright 2022, IGI Global. -
Bromelain enhances digestibility of Spirulina-based fish feed
Microalgae like Spirulina (Arthrospira platensis) are protein rich and can be alternative protein sources to fishmeal and soybean meal in fish feed formulation. The present study aims to improve the protein bioavailability of Spirulina by cost-effective protein extraction followed by protease supplementation in fish feed, using in vitro studies. Different extraction procedures such as microwave-assisted, high pressure, and temperature-mediated extraction, boiling and an isoelectric precipitation were employed to study the protein yield from Spirulina powder, and this was compared with the conventional soybean meal and fishmeal conditioning during feed manufacture. Bromelain is a potent protease that has not been widely used as a feed additive with Spirulina. To study the comparative efficiency of bromelain and other proteases like papain and trypsin on Spirulina and conventional feed substrates, a protease assay was performed at different temperatures and enzyme concentrations. The digestibility of these substrates was also studied in vitro, using gut extracts from the fingerlings of Mozambique tilapia (Oreochromis mossambicus). Unlike an in vivo feeding trial, a novel method was used to study the effect of protease supplementation on the inherent digestibility of the gut with an in vitro method. Bromelain showed the highest activity on all the substrates at both the temperatures. Bromelain supplementation improved the in vitro digestibility of the Spirulina that were subjected to protein extraction, more than the un-extracted one. The results of the present in vitro study suggest that Spirulina could serve as an alternative protein source, and bromelain-based supplementation could improve the digestibility of Spirulina-based fish diets. 2021, Springer Nature B.V. -
Blockchain application with specific reference to smart contracts in the insurance sector
The term blockchain was coined in 2008 by Satoshi Nakamoto. Initially, it was used for carrying out decentralised transactions to solve the problem of fake transactions. In the past few years, this was explored extensively for cryptocurrency only, but, over some time, its potential has been explored in many areas. The major reason for the growing interest in this particular technology is that it provides a secure, reliable, and trusted platform to perform digital activities. This is executed without the involvement of any third party. Once the data is entered into the nodes, it is impossible to tamper it. Though blockchain is costly, it provides better solutions to many research problems in real time. In recent times, researchers have explored blockchain in deep and used it in many applications such as building smart contracts, supply chain management, digital identity providers, voting systems, banking, and finance applications, P2P learning, and insurance sectors. Through this chapter, the readers will get a systematic and detailed study of blockchain in the insurance sector and smart contracts and its current applications in the insurance sector. This chapter will also provide a fair idea of blockchain technology in the insurance sector and additionally its usage in specific applications. In the end, a relevant set of further reading references will be provided. 2023 River Publishers. All rights reserved. -
Wireless Communication Technologies: Roles, Responsibilities, and Impact of IoT, 6G, and Blockchain Practices
This book introduces recent wireless technologies and their impact on recent trends, applications, and opportunities. It explores the latest 6G, IoT, and Blockchain techniques with AI and evolutionary applications, showing how digital integration can be used to serve society. It explores the most important aspects of modern technologies, providing insights into the newest 6G technology and practices; covering the roles, responsibilities, and impact of IoT, 6G, and Blockchain practices to sustain the world economy. This book highlights the roles, responsibilities, and impact of IoT, 6G, and Blockchain and its practices. By describing the implementation strategies for Blockchain, IoT, and 6G, this book focuses on technologies related to the advancement in wireless ad-hoc networks and the current sustainability practices used in IoT. It offers popular use cases and case studies related to 6G, IoT, and Blockchain to provide a better understanding and covers the global approach towards the convergence of 6G, IoT, and Blockchain along with recent applications and future potential. The book is a reference for those working with 6G, IoT, AI, and its related application areas. Students at both the UG and PG levels in various departments such as manufacturing, electronics, telecommunications, computer science, other engineering fields, and information technology will be interested in this book. It is ideally designed for use by technology development, academicians, data scientists, industry professionals, researchers, and students. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Gianluigi Ferrari, and Prerna Ajmani. -
Using Sentiment Analysis to Identify Consumers Emotions in the Hotel Industry
This research attempted to present a more comprehensive overview of online user-generated data by extending far beyond quantitative analysis. We gathered a distinctive and substantial database of online user ratings for the hotel industry from numerous websites over a significant amount of time. To gauge the quality of hotel service, we divided customer reviews into two categories using the sentiment analysis technique. The impact of those factors in influencing users overall evaluation and content creation behavior is then investigated. The findings imply that different aspects of user evaluations have considerably diverse effects on how users evaluate products and what motivates them to create content. 2025 by Apple Academic Press, Inc. -
Robotic dining delight unravelling the key factors driving customer satisfaction in service robot restaurants using PLS-SEM and ML
In the past few years there has been a remarkable surge in demand for robot service restaurants. However, as both the technology and the concept of such restaurants are relatively new, there is a limited understanding of how consumers would react to this new change in the service industry. This study focuses on the key factors influencing customer satisfaction and their intention to repeat the experience by using two staged hybrid PLS-SEM and Machine Learning approaches. The finding confirms that perceived enjoyment, speed, and novelty influence customer satisfaction, whereas perceived usefulness has no influence. Additionally, the study uncovers that customer satisfaction and trust positively mediate the relationship and establish the link with repeat experience. The machine learning models (Artificial Neural Network, Support Vector Machines, Random Forest, K-Nearest Neighbors, Elastic Net) predict the intention to repeat the experience of the service robot with an overall model fit of around 57%. We also discussed several new and useful theoretical and practical implications for enhancing the customer experience during the visit to the restaurants. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Leveraging the Synergy of Edge Computing and IoT in Supply Chain Management
This article investigates the possibilities of integrating edge computing and IoT in supply chain management, as well as the adoption of disruptive technologies such as blockchain integration, digital twins, robotics, and autonomous systems. Operational efficiency can be considerably enhanced by establishing a linked and intelligent supply chain ecosystem. The benefits of this technology include increased openness, efficiency, and resilience in supply chain processes. Among the benefits include real-time product tracking, environmental sustainability, enhanced production, and cost savings. The use of blockchain technology in a three-tiered Supply Chain Network (SCN) shows promise in terms of boosting supply chain transparency and security. The SCOR model is also discussed as a comprehensive framework for optimising supply chain processes. However, concerns such as data privacy, security, and employment displacement must be solved before firms can fully reap the benefits of new technologies. Overall, embracing these innovations has the potential to revolutionise supply chain management and create trust among stakeholders. 2023 IEEE. -
Green Supply Chain Management: Attaining Sustainable Competitive Advantage
[No abstract available] -
Analytics Enabled Decision Making
Analytics is changing the landscape of businesses across sectors globally. This has led to the stimulation of interest of scholars and practitioners worldwide in this domain. The emergence of big data, has fanned the usages of machine learning techniques and the acceptance of Analytics Enabled Decision Making. This book provides a holistic theoretical perspective combined with the application of such theories by drawing on the experiences of industry professionals and academicians from around the world. The book discusses several paradigms including pattern mining, clustering, classification, and data analysis to name a few. The main objective of this book is to offer insight into the process of decision-making that is accelerated and made more precise with the help of analytics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Women Entrepreneurs: A Study of Psychological Well-being and Empowerment in Indian Social Context
Entrepreneurship is differentiated by decision-making ability, competition, economic gains, autonomy, and socioeconomic settings that provide a foundation for an individual to strive and run a venture in a highly competitive environment. In the present context, this study examines the relationship between empowerment and the psychological well-being of women entrepreneurs. This study attempted to analyze the various aspects of psychological well-being responsible for women's entrepreneurship. Exploratory design and regression analysis were used for the study. The study found that only purpose in life, personal growth and positive societal relations are significant psychological factors that influence women empowerment amongst women entrepreneurs in India. The results confirm a significant relationship between empowerment and the psychological well-being of women entrepreneurs in India. This research is apt in the present time as entrepreneurial ventures are considered to be the most critical factors that would help both urban and rural populations through the creation of jobs, rescue them from unemployment and poverty, and thereby have an impact on the development of skills, self-esteem, and self-sufficiency of women. 2023, Institute of Economic Sciences. All rights reserved. -
Trusted explainable AI based implementation for detection of neurodegenerative disorders (ND)
The potential of explainable artificial intelligence (XAI) in detection of neurodegenerative disorders (ND) holds great promise in the field of healthcare. These diseases interfere with the daily functioning and independence of a person. The current studies lack in highlighting the aspect of explainability in their predictions and the various algorithms cannot provide any plausible explanations for their predictions making it difficult for medical professionals to place trust in their findings. Thus, the proposed framework aims to bridge this gap by exploring the development of a trustworthy framework for XAI-based ND detection, focusing on key aspects that can significantly impact its effectiveness and acceptance. The framework makes use of Trust-based SHAP (SHapley Additive exPlanations) values in classification. By computing trust values, the framework ensures more reliable predictions and increases interpretability, instilling confidence in clinicians and patients. The results show that with the inclusion of the trust-driven framework, the accuracy of the algorithm increased from 93.33% in the normal circumstances to 98.21%, highlighting the efficacy of the framework as compared to the other works. This shows that a trustworthy framework for XAI-driven ND detection can reshape care by enabling early detection, personalized treatment plans and enhancing decision-making process. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Local post-hoc interpretable machine learning model for prediction of dementia in young adults
Dementia is still the prevailing brain disease with late diagnosis. There is a large increase in dementia disease among young adults. The major reason is over indulgence of young adults on social media resulting in denial of disease and delayed clinical diagnosis. Dementia is preventable and curable if diagnosed at an early stage, however, no attempts are being made to mitigate dementia in young adults. Today artificial intelligence (AI) based advanced technology with real-life consultations in clinical or remote setups are proved beneficial and is used to detect dementia. Most AI-based test is dependent on computer-aided diagnosis (CAD) tools and uses non-invasive imaging technology such as magnetic resonance imaging (MRI) data for disease diagnosis. In this paper, a local post-hoc interpretable machine learning (LPIML) model for prediction of dementia in young adults is proposed. The performance parameters are computed and compared based on accuracy, specificity, precision, F1 score and recall. The proposed work yields 98.87% training accuracy on original images and 99.31% training accuracy on morphologically enhanced images. The performance results are intrinsic and intuitive in learning the prediction results of individual case. The adoption of the proposed work will accelerate the diagnosis process in the era of digital healthcare. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
XGBoost Classification of XAI based LIME and SHAP for Detecting Dementia in Young Adults
As technology progresses on a fast pace, it is imperative that shall be used in the field of medicine for the early detection and diagnostics of dementia. Dementia affects humans by deteriorating the cognitive functions, and as such many algorithms have been used in the detection of the same but all these algorithms remain a black box to the medical fraternity which is still dubious about the nature and credibility of the prediction. To ease this issue, the use of explainable artificial intelligence has been proposed and implemented in this paper, which makes it easy to understand why and how the model is giving a particular output. In this paper the XGBoost classification algorithm has been used which give an accuracy of 93.33% and to understand these predictions, two separate algorithms namely Local Interpretable Model-agnostic Explanations (LIME) and Shapely Additive Explanations (SHAP) have been used. These algorithms are compared based on the type of explanation they provide for the same input and thus the weakness of LIME algorithm has been found out at certain intervals based on the clinically important features of the dataset. On the other hand, both the algorithms make it easy for medical practitioners to understand the dominating factors of a predicted output thereby helping to eliminate the black-box nature of dementia detection. 2023 IEEE. -
SVM Based AutoEncoder for Detecting Dementia in Young Adults
Dementia's impact on cognitive function necessitates timely diagnosis for effective intervention. Understanding the need for timely detection, the proposed work integrates SVM's decision boundary determination and autoencoder's noise reduction capabilities. The proposed work advances in dementia detection in young adult. Results indicate promising performance, with the model achieving high accuracy around 85.33%. The ROC curve illustrates a balanced trade-off between sensitivity and specificity, while the precision-recall curve highlights effective classification. Importantly, the model surpasses existing literature, underscoring its practical utility. While acknowledging limitations, such as parameter fine-tuning, this study lays the groundwork for refining and expanding this innovative methodology. In summary, this research contributes to the urgent field of early dementia detection, potentially transforming patient care and intervention strategies. 2023 IEEE. -
A comprehensive examination of factors influencing intention to continue usage of health and fitness apps: a two-stage hybrid SEM-ML analysis
This research developed a theoretical framework based on the uses and gratification theory to investigate the intention to continue usage of Health and Fitness Apps (HFAs). In addition, this study explored how health valuation moderates the relationship between determinants and users intention to continue usage. A total of 447 HFA users data was collected from Delhi NCR, India through a purposive sampling technique. Partial least square-structure equation modeling was used to test the role of potential predictors influencing users behavioral intention to continue. The machine learning algorithms were employed to identify the features of importance. The results revealed that system quality, networkability, recordability, and task technology fit have a positive influence on hedonic motivation and utilitarian motivation. While information quality influences hedonic motivation but does not affect utilitarian motivation. Health valuation positively moderates the relationship between information quality, system quality, and networkability to intention to continue usage. We also observed that hedonic motivation emerged as a key predictor of users intention to continue usage of HFAs. The results would possibly offer useful recommendations for HFA developers, marketers, and health policymakers. The quality of fitness apps should be the primary concern of app developers. Furthermore, gamification can be incorporated into HFAs as it may influence the users hedonic motivations. The research contributes by developing a uses and gratification theory tailored for the HFAs. Additionally, this research incorporates hedonic and utilitarian motivation as mediating variables and health valuation as a moderator. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Prioritizing the Essentials: The MBA Aspirants Dilemma
Objective decision-making while choosing an appropriate college for a Master in Business Administration (MBA) is only half-done. It is critical that the student be able to find the best placement at the end of the course by acquiring the most critical skills/specializations affecting placements and involves data-driven decision-making based on past placement trends. Viti and Vania have done their preliminary selection, of ABC College for their MBA course, based on the colleges credence quality. However, they are trying to understand the key success factors (KSFs) affecting placements at ABC to focus their next two years on getting most placement-ready. Having been provided with the placement details of the outgoing batch, they are looking to analyze the data to discover the most critical parameters affecting placements. NeilsonJournals Publishing 2023. -
Analytics Enabled Decision Making Tracing the Journey from Data to Decisions
In the current business environment, which is greatly dynamic and competitive, business organizations are continually striving for expanding their competence and financial performance through improving almost every facet of their business--product/service quality, customer satisfaction, customer retention, productivity, line filling strategies, and others. In this sense, success and failure of organizations depend on the extent of precision of their decisions. Organizations are engaged with data to extract insights, identify trends and make decisions at different levels; and also, many of them learn how to utilize the power of data. Analytics can enable them to derive conclusions, make predictions, and ascertain actionable insights in a contextual and time-bound manner. It helps to examine data from multiple perspectives and gives visualizations by using different frameworks and platforms such as IBM Watson, Tableau, and R. The chapter presents the role of analytics in decision-making processes and assess the effectiveness of decisions upon their implementation, so the corrective measures can also be inserted. As decision making is a continuous business process, analytics accelerates it and gives organizations a pace to keep updated with changing business scenarios. Thus, this chapter presented a decision-making framework exhibiting how decision-making functions as an ongoing process. Different contexts and cases have been used to establish the relevance of each step of the framework. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.