Browse Items (2832 total)
Sort by:
-
Future Battlefield System Using Graph Database and Internet of Things (IoT)
The Internet of Things (IoT) concept is rapidly evolving and is expected to influence each field of the computational realm. These advances have an impact on any nations defence force. The defense industrys solution mostly depends on detectors and their installations. The major goal of sensory statistics is to provide information that may be used for strategic choices and evaluation in future battling fields. Each piece of statistics, from documenting a soldiers essential health metrics to its ammunition, weapons, and position circumstance, has a function and is especially important to the strategic commander stationed in the control unit. This research proposes an innovative approach that combines the IoTs with the growing graph database to produce a contextual consciousness regarding each characteristic of the personnel on the battlefield. We show a projected future battlefield application condition in which we explore the graph database for contextual consciousness patterns to gain a strategic benefit over our competitors. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
Concerns in IoT Environments: Adoption, Architecture, and Innovation of Enterprise IoT Systems
The Internet of Things (IoT) has received a lot of interest in recent times. IoT depicts the upcoming internet and is defined as an environment of linked gadgets, computational processes, and other items that collaborate to transmit information or data with greater ease and economic advantages. Nevertheless, because of the presence of numerous concerns, IoT adoption, architecture, and innovation continue concerns. As a result, the purpose of this study was to identify and analyze the concerns in the adoption, architecture, and innovation of IoT systems in construction enterprises in the Indian environment. The research analysis and professional comments have been employed to identify the barriers to IoT adoption, architecture, and innovation. This research may assist professionals and policymakers in addressing barriers to successful IoT adoption and spread. At last, findings and potential research possibilities are provided. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
Monitoring the Development of the IoT Concept in Various Application Domains
For several decades, the concept and technology of combining actuators and sensors into a system to monitor and operate tangible structures distantly was understood and developed. Nevertheless, slightly over a decade back, the notion of the Internet of Things (IoT) emerged and was utilized to merge such techniques into a prevalent architecture. The study outlines and addresses IoT conceptual structures suggested as part of continuing standardization attempts, layout problems regarding IoT hardware and software parts, and delegates of IoT application domains like healthcare, smart cities, the farming industry, and nano-scale uses. The research verifies the argument that an agreement on the precise scope of the IoTs will likely be formed, as enabling innovation evolves and novel application domains have been presented. Current modifications, nevertheless, are a bit muted, and their variants on application domains have been distinct, with statistics and information technologies serving a significant part in the IoT environment. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
Research on Big Data for Industry 4.0 Cyber-Physical Systems
The objective of the revolution known as Industry 4.0 seeks to optimize goods creation based on consumer requirements, specifications for quality, and financial viability. Big data collected by the Internet of Things (IoT)-based commercial Cyber-Physical Systems (CPS) plays an essential part in boosting platform operation efficiency to promote throughput with improved consumer encounters in Industry 4.0. This study shows big databases derived from IoT-based Optical-Wireless CPS (OWCPSs) for optimizing the functioning of maintenance networks in the electronics-manufacturing Industry 4.0. This research collected and analyzed big databases including five parameters: data delivery, delay, overload, throughput, and package error percentage in OWCPSs. The information gathered is important for optimizing the functioning of service systems in the production of electronic goods Industry 4.0. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
An Empirical Research of AI Approaches in Electronic Engineering
The function of artificial intelligence (AI) in electronic engineering has been suggested to overcome the issue of an elevated structure error rate in electronic engineering. Using LPWAN innovation in AI as an instance, an innovative structure is presented to increase the safety of the Internet of Things wireless communication infrastructure. The business, processing of information, terminal accessibility, and communication innovation layers make up the majority of the framework. The empirical findings indicate that the structures setup transmits four types of data transfer directions every 30 seconds, and the receiver port constantly gathers the aforementioned command information for 4 hours, contrasted to the conventional framework (15.6 percent), and the package loss rate is 4 percent, significantly enhancing the systems throughput and processing performance. The developed framework is more stable, has a lower bit error rate, and may assist wireless communication effectively. It has been demonstrated that the novel design, using LPWAN innovation as an instance, has a big total capacity as well as a good performance of its electronic engineering connection. The structure number error rate is considerably lowered, and the signal structure number is highly accurate as an outcome. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
Electronic Voting Systems Using a Blockchain-Based Encrypted Identity Management
The use of electronic voting technologies has grown in popularity as a way to make elections more secure and accessible. The implementation of blockchain-based encrypted identity management in electronic voting is explored in this study, which also offers a solid option to improve the reliability and credibility of voting systems. This study explores the possibilities for anonymous and transparent electronic voting while preserving voter privacy and anonymity by incorporating blockchain technology. It has always been challenging to create an electronic voting system that properly satisfies the requirements of administrators. This problem is now being resolved by blockchain technologies, which provide a distributed database with irreversible, encrypted identity management and secure transactions. A fascinating advancement in the realms of data innovation, dependability, and transparency is distributed ledger technology. Distributed ledger technology is commonly used in public blockchain. Virtually limitless potential for earning from sharing economies are provided by blockchain technology. This project aims to determine whether blockchain technology can be used to create electronic voting devices are used as a service. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
Role of Additive Manufacturing and Thermal Spray Processed Materials in Electric Vehicle (EV) and Hybrid Electric Vehicle (HEV) Applications
Additive manufacturing (AM) significantly contributes to the development of electric vehicles (EVs) and hybrid electric vehicles (HEVs), providing lightweight, complex, and customized components. This study explores AMs role in advancing EV and HEV technology, with a special focus on integrating thermal spray coatings (TSCs) to enhance component performance. By employing TSCs in AM-fabricated components, manufacturers can improve surface characteristics, wear resistance, and corrosion protection critical factors for long-lasting EV/HEV systems. The synergy between AM and TSC enhances key parts such as battery enclosures, thermal management systems, and structural frameworks by optimizing their thermal insulation, durability, and energy efficiency. Additionally, AM enables efficient material use and lightweighting, which reduces vehicle weight and enhances energy conservation, addressing industry needs for sustainable solutions. This chapter reviews the current applications and future potential of TSC in AM components, highlighting its role in meeting the rigorous demands of the automotive sector. Findings suggest that combining AM and TSC opens pathways for advanced, sustainable EV and HEV designs, aligning with the global shift toward cleaner energy and resource-efficient manufacturing. 2026 selection and editorial matter, R. Suresh, C. Durga Prasad, Satish Kumar, K.N. Bharath, and Ajith G. Joshi; individual chapters, the contributors. -
DIGITIZATION AS A TOOL FOR CONSERVATION AND SUSTAINABILITY OF THE BUILT HERITAGES: A DISTANT DREAM OR AN EXISTING REALITY?
The idea of built heritage is as old as human civilization, and its objective stretches far beyond our understanding of the past. These built heritages as artifacts express humanitys history, diverse cultures, skills, and experiences exchanged and shared across generations. They provide specific characteristics for places, making them the material manifestation of social, economic, political, territorial, and environmental values. Unfortunately, natural and man-made disasters have been posing repetitive threats to the sustainability of these built heritages. Therefore, there has been a growing interest in and calls for the conservation and protection of these built heritages. As we have ushered in the era of technical advancements, the world is abuzz with the word digitization. The continual adaptation of digital technologies in various spheres of life and the growing popularity of digital devices have revolutionized consumption patterns in recent times. Conse quently, the use of digital technologies to conserve and promote monuments has gained prevalence in various parts of the West. Further, in recent times, this trend seems to be catching on in developing countries like India as well. However, given the novelty of the concept, the adoption and accep tance of the concept of digitized monuments are still surrounded by many unanswered questions. The study aims to reveal the opinions of the tourists visiting the various built heritage sites and understand their experiences with digital heritage and its influence on the tourist experience while visiting a built heritage monument. The chapter also tries to dive deep into their thoughts and understanding of the influence of digitization in promoting sustainable consumption. In an attempt to achieve the aforementioned objective of the study, the data would be collected from the urban populace of India. A qualitative approach has been adopted to conduct the study, and semi-structured inter view forms consisting of open-ended questions have been used to collect the data. MAXQDA software would be employed to analyze the responses collected and draw conclusions from the data collected. The study intends to bring out the opinion of tourists in regard to the digitization of built heritage in India. As the trend of digitization of built heritage is still in its nascent stage in India, only a few heritage monuments have been digitized in recent times. 2025 by Apple Academic Press, Inc. -
Advancing Interpretable Machine Learning: Principles, Challenges, and Practical Insights
[No abstract available] -
Role of Augmented Reality (AR) in Promoting Media Literacy and Sustainability Awareness: A Mixed Method Approach
Augmented reality (AR) has emerged as a transformative tool in education, offering immersive experiences that enhance engagement and understanding across various domains. This study explores the potential of AR in promoting media literacy and sustainability awareness, two critical competencies in the modern information landscape. Through a mixed-methods approach, the research investigates how AR interventions can improve individuals ability to critically assess media content while simultaneously raising awareness about environmental sustainability. The study employs pre- and post-test evaluations, focus groups, and user interaction data to measure changes in media literacy and sustainability awareness among participants exposed to AR-based educational content. Findings indicate that AR significantly enhances media literacy by enabling users to better identify fake news, understand media bias, and critically evaluate information sources. The implications of these findings suggest that AR is not only a powerful tool for enhancing media literacy and sustainability awareness but also a catalyst for promoting informed, responsible, and proactive citizenship in the digital age. 2026 selection and editorial matter, Sonal Trivedi, Vishal Jain, Balamurugan Balusamy, Subhendu Pani, and Danish Ather. -
Integrating cyber-physical systems with intelligent transportation: Challenges and opportunities
Cyber-physical systems (CPS) are revolutionizing the transportation sector, wherein physical processes are combined with computational systems to create efficient, reliable, and safe transportation solutions. This chapter discusses the ways in which CPS impact contemporary transportation development. The theoretical and practical aspects of CPS have been considered as they follow with the intelligent traffic management systems and driverless cars within this scope of work. The first half of the chapter is then applied to architectural design in CPS, discussing how elements of the physical worldinteraction with cars and roads, for exampleare coupled with cyber systems, such as cloud computing, IoT, and communication networks. Important technical breakthroughs in these areas highlight the key aspects that make real-time decision-making and optimization of systems possible: 5G, edge computing, and artificial intelligence. The chapter also reviews simulation-based techniques in analyzing vehicle behavior and traffic flow, which encompasses insights into how CPS might improve traffic safety and efficiency. Simulations can study very complex transportation scenarios like collision avoidance and control of traffic without the need for real data. The chapter discusses cybersecurity risks, legal issues, and the need for standardized infrastructure to support intelligent transportation systems. It also focuses on the challenges presented by laws and policies in the field of CPS. The interaction of drivers, passengers, and traffic operators with these devices further helps grasp the human factor as well as the experience of a CPS user. The final section of the chapter discusses future directions of CPS research and development, specifically regarding how blockchain technology and quantum computing might advance transportation networks. This chapter will, therefore, give the reader a holistic understanding of how CPS may change the face of transportation in the future by bringing its non-data-driven components to the fore. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Building resilient and sustainable operations through cloud security
With the evolution of the digital era, organizations are increasingly employing cloud computing for enhanced scalability, operational effectiveness, and innovation. With this rapid evolution in cloud technology comes vulnerability to advanced and dynamic cybersecurity threats for enterprises. This chapter discusses the idea of cloud security intelligence (CSI) as a strategic method for developing sustainable and resilient cloud operations. CSI employs state-of-the-art technologies such as artificial intelligence (AI), machine learning (ML), real-time monitoring, and automation for threat detection, investigation, and threat management proactively. The chapter discusses the very essence of CSI, i.e., collecting data, threat detection, incident response, and ubiquitous monitoring, and reflects how CSI contributes to regulatory compliance, business resilience, cost reduction, and sustainability of the environment. Through real-life instances of CSI deployment in healthcare, finance, and e-commerce spaces, the chapter illustrates the paradigm-breaking function of CSI in the organizational security stance. Furthermore, it brushes upon current issues of CSI deployment and maps future directions involving AI, blockchain, Internet of Things (IoT), and quantum-safe encryption. Last but not least, CSI also offers itself not merely as a technical solution but as a strategic enabler of secure, compliant, and sustainable digital realms. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Building resilient and sustainable operations through cloud security
With the evolution of the digital era, organizations are increasingly employing cloud computing for enhanced scalability, operational effectiveness, and innovation. With this rapid evolution in cloud technology comes vulnerability to advanced and dynamic cybersecurity threats for enterprises. This chapter discusses the idea of cloud security intelligence (CSI) as a strategic method for developing sustainable and resilient cloud operations. CSI employs state-of-the-art technologies such as artificial intelligence (AI), machine learning (ML), real-time monitoring, and automation for threat detection, investigation, and threat management proactively. The chapter discusses the very essence of CSI, i.e., collecting data, threat detection, incident response, and ubiquitous monitoring, and reflects how CSI contributes to regulatory compliance, business resilience, cost reduction, and sustainability of the environment. Through real-life instances of CSI deployment in healthcare, finance, and e-commerce spaces, the chapter illustrates the paradigm-breaking function of CSI in the organizational security stance. Furthermore, it brushes upon current issues of CSI deployment and maps future directions involving AI, blockchain, Internet of Things (IoT), and quantum-safe encryption. Last but not least, CSI also offers itself not merely as a technical solution but as a strategic enabler of secure, compliant, and sustainable digital realms. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Integration of cyber-physical systems with wearable devices:A new paradigm for patient monitoring
The healthcare sector has witnessed significant changes as cyber-physical systems (CPS) bring embedded technologies that are developed from human and physical surroundings to smart objects. Wearable technologies such as wearable fitness trackers, biosensors, and smartwatches stand as good examples of smart healthcare that may improve decision-making and real-time patient monitoring. Through advances in personal health technology, mobile medication, and smart sensing, these technologies aid the medical treatment of the patient. Such advancements enable monitoring and programming health data streams continually, which supports early diagnosis and better care. However, challenges persist in integrating machine learning into health wearables; it still poses a limitation, improving algorithm accuracy and reliability so that the use can be widespread. Advances in skin-based, textile-based, and biofluidic designs have allowed medical wearables to monitor neuro, cardiovascular, and metabolic disorders, which are being further extended to drug delivery systems. The present study identifies gaps and advances in the field using secondary data from articles, journals, and research papers. It highlights future research directions on the clinical applications of wearable technology and its role in routine safety and health monitoring. Findings have indicated that regulated data privacy, equity, and fairness must be pursued to fully realize CPS-enabled wearables in terms of a healthcare revolution. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Implementing smart cyber-physical systems in industrial and urban applications: A practical approach
World urbanization, at an accelerated rate, leads to a growing need for innovative cities that consider advances in AI and cyber-physical systems (CPS). A smart city is a development of a traditional environment of an urban setting, enhancing it with information and communication technology (ICT) and CPS to improve the quality of life, sustainability, and efficiency of the inhabitants. This chapter will cover the major constituents, challenges, and opportunities associated with the development of smart cities from the historically congested and ad hoc planned cities. A smart city connects a digitally empowered environment through sensors, processors, and communication systems integrated into urban infrastructures, allowing continuous monitoring of public health, mobility, energy consumption, and so on. The combination of AI and data analytics with smart city technologies will help optimize services in cities, reduce environmental effects, and accelerate socioeconomic development and decision-making. Improvement to cities is still a debatable issue, and there are additional obstacles to be overcome, such as infrastructural inadequacy, budgetary constraints, and technical issues. Realization of the full potential of smart cities will occur through successful resolution of the aforementioned issues. All the issues of this chapter can be addressed by adopting a multidisciplinary approach emphasizing sustainable designs, publicprivate sector partnerships, and regulatory frameworks. If ignored, such problems will definitely lead to adverse effects on implementation, an increase in socioeconomic inequality, and damage to the environment. This chapter relies on the secondary methodology of research and assimilates knowledge from journal articles, literature, and earlier research regarding smart cities, CPS, and AI applications. It defines current trends, recognizes long-standing problems, and suggests ways to bridge them, along with some directions for future research. This will help in understanding the ability of AI to make smart city adaptation strong concerning population growth, health crises, and climate change. It will also strengthen and connect the urban landscape of the future. Thus, by solving these problems and their consequent impacts, smart cities can totally transform urban life. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Quantum-inspired algorithms for cognitive computing: Enhancing cloud-based problem-solving
The convergence of quantum-inspired algorithms and cloud-based frameworks represents a transformative shift in computational capabilities tailored to the human-centric goals of Industry 5.0. Unlike Industry 4.0, which focused on automation and digitization, Industry 5.0 emphasizes intelligent systems that complement human decision-making. Quantum-inspired algorithms, derived from the principles of superposition and entanglement, offer superior capabilities in optimization and pattern recognition without requiring quantum hardware. When integrated with scalable and distributed cloud computing infrastructures, these algorithms enable high-performance cognitive computing, tackling previously intractable problems across domains. This chapter explores the theoretical foundation and practical implementation of such systems, including quantum-inspired neural networks (QiNNs), quantum-inspired immune algorithms (QiIAs), and quantum-inspired particle swarm optimization (QPSO). These models exhibit enhanced accuracy and efficiency in applications like pattern recognition, anomaly detection, and multiobjective optimization. Real-world case studies in finance, cybersecurity, healthcare, and smart grid management highlight their impact on risk modeling, threat mitigation, and decision support systems. The chapter further proposes a cloud integration framework, addressing challenges in scalability, performance, and security. Implementation strategies and architectural designs are discussed with a focus on dynamic resource management, real-time analytics, and secure deployment. The synthesis of these technologies marks a significant advancement toward achieving adaptive, intelligent, and secure computational ecosystems, aligned with the values and vision of Industry 5.0. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Next-gen cloud intelligence: Cognitive computing for a sustainable digital future
Cognitive cloud computing is an innovative paradigm that links intelligent systems with cloud infrastructure having distributed and scalable capabilities. Next-generation cloud intelligence is explored with regard to the foundational principles, enabling technologies, and emerging applications. It focuses on cognition cloud systems to maximize energy efficiency, improve predictive analytics, and encourage human-centric computing for various domains such as education, healthcare, finance, and environmental management, including sustainability. Some of the enabler technologies for AI are natural language processing, computer vision, and speech recognition, and the advancement of AI integration, neuromorphic computing, and quantum-enhanced models. The coming of bloc, edge, and the cognitive security mechanisms make it the basis for an invulnerable, transparent, and context-aware system. The chapter also explores green data centers, energy-efficient algorithms, and circular economy principles. The ethical development of cognitive cloud systems is critically analyzed, and data privacy, algorithmic bias, explainability, and regulatory frameworks are considered as challenges for their ethical development. In general, the contribution of this work is to provide a complete framework for the analysis of the impact that cognitive computing can have to make over cloud-based ecosystems as intelligent, adaptable, and eco-friendly platforms through the means of digital infrastructure and AI-driven services. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
A sustainable approach to cloud computing: A comprehensive analysis of load balancing techniques in cognitive environments
Cloud computing is one of the rising eras in big-scale computing, where information is processed in big information centers. One of the demanding situations with that is to accomplish load balancing of all the nodes. In addition, it's essential for proper utilization of assets and division of the work. This indicates that effective allocation and usage of the computing resources among clients in sharing mode leads to satisfactory users as well as good utilization of resources. Balancing the load in huge data-centric systems and networks is required to achieve the stated goal. The load balancing problem is considered as an optimization problem, and the rules for a load provide the number of compensations (scalability enabling, bottleneck avoidance) and resource consumption. A number of proposed algorithms exist for the load balancing problem in the cloud environment. Efforts have been made in this chapter to examine and review a few of the weight balancing algorithms in cloud computing. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors.