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Energy Intelligence: The Smart Grid Perspective
Smart grids enable a two-way data-driven flow of electricity, allowing systematic communication along the distribution line. Smart grids utilize various power sources, automate the process of energy distribution and fault identification, facilitate better power usage, etc. Artificial Intelligence plays an important role in the management of power grids, making it even smarter. With the help of Artificial Intelligence and Internet of Things, smart grids can optimize the energy consumption, provide continuous feedback on usage, and monitor live usage statistics, thereby making the energy intelligent. Smart grids require specific hardware to continuously monitor and adapt to the requirements of the system. By enabling energy intelligence, we empower building-level and city-level optimizations that make use of green energy, thereby contributing more toward sustainable development. Thus, the multifaceted energy management system uses sustainable and renewable energy sources, combined with smart devices to provide a two-way communication system to optimize the end-to-end distribution of energy, beneficial to both suppliers and consumers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
Energy-efficient smart cities with green internet of things
With governments of different countries having a vision of smart cities, the technology adoption and implementation are at its peak and the current increase in the usage of advanced technology for a smart city has led to an increase in the carbon imprint across the globe, which needs immediate attention for the environment sustainability. Although the Internet of things (IoT)-enabled devices have changed our world by bringing an ease to our lifestyle, it has to be kept under consideration that they also have adverse effects on the environment. Over the past few years, enabling energy conservation via Internet of Things in the growth of smart cities has received a great deal of attention from researchers and industry experts and has paved the way for an emerging field called the green IoT. There are different dimensions of IoT, in which an effective energy consumption is needed to encourage a sustainable environment. This conceptual paper focuses on the key concept of green IoT and sustainability, knowledge of Smart cities' readiness to Green IoT (G-IoT)-enabled sustainable practices, and identifying the Green IoT sustainability practices for smart cities. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Engaged institution model: A faculty perspective
This paper attempts to build the engaged institution model from faculty perspective. Data was collected from 200 faculty members across disciplines, who were engaged in community engagement and social responsibility activities in one or the other ways. On analysis of the data, it was found that Instruction and Research, Facilitator, Scholarship factors contribute towards community engagement activities in higher educational institutions and that these factors contribute towards Faculty engagement, Student engagement and Community Engagement. All these factors create Engagement institution model. This work has an implications on theory, practice and policy. Service learning, as a pedagogical tool if implemented in HEIs can effectively bring all the influencing factors together and can help in creating an engaged institution. 2024, IGI Global. All rights reserved. -
Engineering applications of artificial intelligence
Artificial intelligence (AI) has evolved rapidly over the past few decades, permeating various aspects of our lives and transforming industries. This chapter explores the emerging applications of AI across diverse fields, including healthcare, finance, transportation, education, and entertainment. In healthcare, AI is revolutionizing diagnostics, drug discovery, personalized medicine, and patient care. In finance, AI-powered algorithms are enhancing trading strategies, risk assessment, fraud detection, and customer service. The transportation sector is witnessing advancements in autonomous vehicles, traffic management, and logistics optimization through AI technologies. AI is also reshaping education with adaptive learning platforms, personalized tutoring, and educational analytics. Moreover, in the entertainment industry, AI is driving content creation, recommendation systems, and virtual experiences. Despite the remarkable progress, challenges such as ethical concerns, bias mitigation, data privacy, and regulatory frameworks need to be addressed for the responsible deployment of AI. 2024, IGI Global. All rights reserved. -
Engineering applications of blockchain in this smart era
The advent of blockchain technology has revolutionized various industries, offering novel solutions to age-old problems. In this smart era, characterized by interconnected devices and burgeoning digital ecosystems, blockchain stands out as a transformative force. This chapter explores the emerging applications of blockchain technology in this paradigm shift towards smart systems. One prominent application of blockchain lies in the domain of decentralized finance (DeFi). Blockchain facilitates peer-to-peer transactions, eliminating the need for intermediaries like banks. Smart contracts, powered by blockchain, automate and execute agreements, enabling programmable finance, lending, and asset management. Moreover, blockchain's transparency and immutability enhance trust in financial transactions, fostering financial inclusion and security. In the realm of SCM, blockchain offers unprecedented transparency and traceability. By recording every transaction on an immutable ledger, blockchain enables users to track the journey of products from raw materials to end consumers. 2024, IGI Global. All rights reserved. -
Enhanced Data Security Architecture in Enterprise Networks
Encryption and storing important information is one of the risky and most challenging tasks. It is the need of the hour in todays fast growing technological transformations that the world is undergoing. A simple Enterprise network is the communication backbone of any organization. It mostly provides better information storage and efficient retrieval, which helps the organization to function smoothly, without having to think twice about their crucial datas security aspects. The information technology paradigm, cloud computing is used to help the organization to focus on its core business. In cloud computing is dealing with many services. That service is used for provide Platform service with infrastructure and software service. This paper, promotes the idea of combining various security and encryption algorithms to connect different enterprise networks using cloud computing, security layer concepts and giving no room for hackers to intrude into the confidential system of data. Springer Nature Switzerland AG 2020. -
Enhanced Stock Market Prediction Using Hybrid LSTM Ensemble
Stock market value prediction is the activity of predicting future market values so as to increase gain and profit. It aids in forming important financial decisions which help make smart and informed investments. The challenges in stock market predictions come due to the high volatility of the market due to current and past performances. The slightest variation in current news, trend or performance will impact the market drastically. Existing models fall short in computation cost and time, thereby making them less reliable for large datasets on a real-time basis. Studies have shown that a hybrid model performs better than a stand-alone model. Ensemble models tend to give improved results in terms of accuracy and computational efficiency. This study is focused on creating a better yielding model in terms of stock market value prediction using technical analysis, and it is done by creating an ensemble of long short-term memory (LSTM) model. It analyzes the results of individual LSTM models in predicting stock prices and creates an ensemble model in an effort to improve the overall performance of the prediction. The proposed model is evaluated on real-world data of 4 companies from Yahoo Finance. The study has shown that the ensemble has performed better than the stacked LSTM model by the following percentages: 21.86% for the Tesla dataset, 22.87% for the Amazon dataset, 4.09% for Nifty Bank and 20.94% for the Tata dataset. The models implementation has been justified by the above results. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Enhancements of women's entrepreneurship: A theme-based study
Woman entrepreneurs are defined as a group of women who initiate, organize, and run a business concern, from a situation where a woman was not even allowed to get out of their home, to today, running most of the successful brands of the world, contributing a major part to the economic growth, and breaking the stereotypes by providing a reality check to the male dominance. There has been a wide range of public policies enrolled out to facilitate and encourage the growth of women's entrepreneurship. A few such policies from India have proved to be successful, which will be outlined in this book chapter. From the past times of not gaining adequate recognition for their support, women have emerged successful in overcoming hardships such as lack of visibility, lack of training and educative support about public policies provided by governments to women entrepreneurs, fewer opportunities, and walking out of the social stigma. 2023, IGI Global. All rights reserved. -
Enhancing academic credential verification through blockchain technology adoption in university academic management systems
Blockchain technology has emerged as promising solution in various sectors, including higher education. This research investigates the impact of usage of blockchain technology in student credential verification within university academic management system. This study employs a descriptive research through quantitative analysis of data collected from universities that have integrated or planning to integrate blockchain technology into their academic management systems. Key parameters examined include awareness and familiarity with blockchain, extent of blockchain usage, user experience and satisfaction, the perceived impact and benefits. The findings suggest that blockchain technology positively influences academic credential verification process, streamlining data sharing and reducing administrative burdens. As blockchain continues to transform the academic management landscape, this study offers timely guidance for stakeholders navigating the intersection of technology and education. 2024, IGI Global. All rights reserved. -
Enhancing business capabilities through digital transformation, upscaling, and upskilling in the era of Industry 5.0: A literature review
This literature review aims to understand the recent developments in the field of upscaling and upskilling in the digital transformation of business, from an Industry 5.0 prospective. It used a comprehensive search of relevant peer-reviewed journal articles, industry reports, and online sources to gather the relevant data. The findings indicate that upscaling is essential for industry 5.0, and that businesses should invest in upskilling and upscaling programs to meet the changing demands of the digital economy. This literature review provides a comprehensive analysis of the current state of upscaling and upskilling in the digital transformation of business and provides insights into the future direction of this field. It also highlights the importance of collaboration between businesses, governments, and educational institutions to ensure that the workforce is prepared for the future of work. 2024, IGI Global. All rights reserved. -
Enhancing Customer Satisfaction and Sales in Retail Environments: A Personalized Augmented Reality Approach for Dynamic Product Recommendations
This article explores the potential transformative impact of integrating augmented reality (AR) technology with personalized product recommendations in the retail industry. By leveraging ARs ability to overlay digital information onto the physical world, retailers can offer tailored suggestions based on individual preferences, past purchases, and real-time contextual cues, thereby enhancing customer satisfaction and driving sales. Through a comprehensive literature review and empirical analysis, the study investigates user experience, adoption factors, and the long-term effectiveness of AR-deep learning integration in retail settings. Findings reveal significant improvements in customer satisfaction, sales performance, inventory management, and employee productivity with the implementation of AR-Deep Learning technology. Additionally, the article presents an innovative framework that seamlessly integrates AR and deep learning models, demonstrating high accuracy in object recognition, real-time interaction, and enhanced user experience across various industries. While highlighting the studys limitations and areas for further research, this article underscores the importance of customer-centric strategies and technological innovation in optimizing the retail experience and driving business growth. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Enhancing instructional effectiveness using the metaverse: An empirical analysis of the role of attitude and experience of participants
The Metaverse has been gaining importance, with businesses looking to adopt the same for processes rangingfrom onboarding to customer experience. The current study has been conducted to evaluate the impact of learner characteristics on motivation to participate in metaverse-based training programs across various organizations. Based on literature and theory, two main characteristics were identified: attitude towards the metaverse and experience with the technology. Data for the study was collected using a structured questionnaire and 103 responses were collected from employees belonging to various organizations in India. The analysis and interpretation of the data was done using statistical techniques through the tool of SPSS. The study found out that both the learner characteristics have a strong positive relationship with each other, and attitude towards metaverse has a stronger relationship with learner motivation than the experience of use. The findings suggest organizations focus more on the manner in which they should introduce metaverse at the workplaces and need to keep the employee attitude towards any kind of change; more of a technological change in mind when they are strategizing to implement metaverse-based training programs. 2024, IGI Global. All rights reserved. -
Enhancing language teaching materials through artificial intelligence: Opportunities and challenges
Incorporating artificial intelligence (AI) into language education signifies a paradigm shift that promotes originality and inclusiveness. The partnership between AI developers and educators effectively tackles obstacles and establishes a foundation for continuous progress. Anticipating the future, the progression of AI holds the potential to deliver intricate customization, customizing educational encounters to suit the unique requirements of each individual. Responsible incorporation of AI into teaching methodologies transforms them into a collaborative model that empowers educators to engage in individualized interactions. Ethics remain of the utmost importance, encompassing bias mitigation and privacy. In essence, the integration of AI into language education signifies an impending era in which the combined powers of technology and human proficiency foster the development of capable individuals who are prepared to navigate an interconnected, digitally globalized society. 2024, IGI Global. All rights reserved. -
Enhancing neurocognitive skills for effective leadership and decision-making
In today's dynamic workplace, human resource development and management (HRDM) professionals face multifaceted challenges requiring advanced cognitive abilities. This book chapter explores the critical interplay between leadership skills, decision-making, and executive functions (EFs) in HRDM. It sheds light on their pivotal role in shaping workplace dynamics and organizational outcomes. Focusing on skills such as emotional intelligence, cognitive flexibility, and continuous learning, the chapter delves into their neurocognitive underpinnings, particularly within the prefrontal cortex. It discusses strategies for enhancing EFs, including reflective practice, empathy training, and mindfulness, and emphasizes the concept of neuroplasticity in fostering continuous learning and adaptation within HRDM. By integrating insights from neuroscience into HR practices, the chapter offers valuable guidance for HR professionals seeking to optimize organizational performance, enhance leadership qualities, and drive effective decision-making processes. 2024 by IGI Global. All rights reserved. -
Enhancing Patient Safety and Efficiency in Intravenous Therapy: A Comprehensive Analysis of Smart Infusion Monitoring Systems
Intravenous (IV) fluids, comprising vitamin-rich solutions, are administered to address patient electrolyte imbalances and dehydration through IV infusion therapy. Infusion pumps are integral for precise medication dosage delivery in this common medical procedure, generally posing low risks. These fluids are stored in polypropylene bags connected to patients through tubes. However, when the IV bag empties, the patients blood may flow backward into the IV tube due to higher blood pressure, known as diffusion, potentially leading to complications like air embolism-life-threatening if air enters the bloodstream through the IV line, obstructing blood flow to vital organs. Smart IV Bags emerged as a solution to mitigate such risks, eliminating the need for manual IV bag monitoring while preventing reverse blood flow. This research comprehensively assesses various IoT-enabled IV Bag monitoring systems, comparing their strengths, weaknesses, and unique features. Key evaluation criteria include component efficiency, real-world applicability, accuracy, latency, and technical specifications. The aim is to provide an objective evaluation of each Smart Intravenous Liquid Monitoring System to inform future developments in this field. A systematic approach ensures the selection of systems that best meet specific requirements in diverse healthcare environments. 2024 Scrivener Publishing LLC. -
Enhancing social cognition in individuals with ADHD: An eastern approach
With the increasing prevalence of ADHD in the global front, it is essential to explore different effective methods for providing support and intervention. The difficulties with social cognition are reflected in their limitations in emotional self-regulation, emotion recognition, and empathy. Though several interventions exist for ADHD, many at times, the effectiveness of eastern approaches are overlooked due to the limited awareness about its nature. Research suggests that systematic and regular practice of yoga helps to improve attention, control emotion, and reduce restlessness among them. Several asanas are found to be especially helpful for managing ADHD symptoms including cobra (bhujangasana) pose, cat-cow pose (bitilasana marjaryasana), downward-facing dog (adho mukha shvanasana), tree pose (vrikshasana), mountain pose (tadasana), among many others. The chapter gives a comprehensive summary on the application of yoga techniques on the improvement of social cognition in individuals with ADHD. 2024, IGI Global. -
Enhancing the digital consumer experience: The role of artificial intelligence
In the era of rapid technological advancement, the integration of artificial intelligence (AI) and digital consumerism has created new trends in business. Consumers are able to communicate with brands in new ways owing to developments in digital media. AI-powered recommendation systems, chatbots and virtual assistants are the main drivers of this change. It allows businesses to offer product recommendations, customer support, and personalized content to increase user engagement and satisfaction. This chapter provides real-world examples of AI applications across industries, highlighting success stories of companies using AI to create better value and customer satisfaction. Finally, the integration of artificial intelligence and digital customer experience has the potential to transform the future of e-commerce, marketing, and customer service, opening new horizons for both businesses and consumers. 2024, IGI Global. All rights reserved. -
Enhancing well-being: Exploring the impact of augmented reality and virtual reality
Virtual reality (VR) and augmented reality (AR) can revolutionize how individuals experience and perceive the world. Effective and engaging wellness practices are made possible by these technologies personalized, immersive experiences. The organization endeavors to foster empathy and understanding by attending to physical, mental, emotional, and social health. Nevertheless, ethical deliberations are of the utmost importance, including privacy, proper data handling, and secure data access. Education, support, and accessibility are critical determinants of user acceptance. Additional areas that warrant further investigation include treatment efficacy, diversity, long-term effects, and ongoing progress. A more inclusive, engaging, and productive approach to individual and communal health is anticipated due to the expanding use of AR and VR in well-being. 2024, IGI Global. All rights reserved. -
Ensemble Model of Machine Learning for Integrating Risk in Software Effort Estimation
The development of software involves expending a significant quantum of time, effort, cost, and other resources, and effort estimation is an important aspect. Though there are many software estimation models, risks are not adequately considered in the estimation process leading to wide gap between the estimated and actual efforts. Higher the level of accuracy of estimated effort, better would be the compliance of the software project in terms of completion within the budget and schedule. This study has been undertaken to integrate risk in effort estimation process so as to minimize the gap between the estimated and the actual efforts. This is achieved through consideration of risk score as an effort driver in the computation of effort estimates and formulating a machine learning model. It has been identified that risk score reveals feature importance and the predictive model with integration of risk score in the effort estimates indicated an enhanced fit. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Ensembled convolutional neural network for multi-class skin cancer detection
A skin cancer diagnosis is critically important in medical image processing. The role of dermoscopy and dermatologists is inevitable in skin cancer diagnosis. But, considering the time constraints on diagnosing patients on time, even medical experts need computer-assisted methods to automate the diagnosis process with a higher accuracy rate and with good performance. Such computer-assisted methods with induced artificial intelligence (AI) algorithms are gaining significance. The challenging task of medical image processing is finding benign/malignant pigmented skin lesions after the input image of patients. To identify this difference, AI-based classification algorithms shall be deployed. During the implementation of such algorithms, several performance aspects are evaluated. Once the best such algorithm is identified and evaluated for its performance attributes, it shall be deployed to assist dermatologists. This book chapter explains such a novel multiclass skin cancer classification algorithm. The proposed algorithm uses the best of the attributes and parameters of a deep convolutional neural network (CNN) to give the best-ever enactment among similar existing algorithms. The result achievement of the developed deep CNN based multi-class skin cancer classification algorithm (DCNN-MSCCA) is demonstrated using the HAM10000 dataset. To establish the significance of the developed algorithm, the performance parameters of the DCNN-MSCCA are compared with a few existing significant algorithms. The maximum accuracy of DCNN-MSCCA in predicting the exact multi-class skin cancer is 95.1%. This book chapter explains the implementation details of DCNN-MSCCA using python and libraries supporting CNN. 2024 River Publishers.