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Mental Workload Estimation Using EEG
Mental workload contributes considerably to the outcome or the performance of any task. The concern of human workload increases during a human-machine collaboration task or in a multitasking environment. This paper presents a comparative study of machine learning algorithms used to estimate workload using Electroencephalography (EEG) data. An open-access EEG dataset acquired during a 'simultaneous capacity (SIMKAP) experiment' and 'no task' is used to create and validate models for binary classification of workload as present and absent respectively. The paper presents an implementation of various classification models that use EEG data to predict the workload. In this paper, implementation for KNN classifier (57.3%), Random Forest classifier (57.19%), MLP network classifier (58.2%), CNN+ LSTM network classifier (58.68%), and LSTM network classifier (61.08%) has been reported. The paper can be further extended to study operator workload in real-time using a brain-computer interface paradigm for any kind of task in a real-world application. The workload classification can be further used in human-machine tasks to decide task allocation between the system to achieve optimal performance in a complex critical system. 2020 IEEE. -
Impact of Homophily on Patient Empowerment: A Study of Online Patient Support Groups
Internet facility has led to emergence of patient support groups. These have gained prominence as these fulfils important benefits to patients. One such benefit is patient empowerment. These online groups provide opportunity to patients to interact with similar ailments and predicaments and who can understand the pain and discomfort felt by the patient. This provides validation for the patient and patients experiences. How does this homophily impacts patient empowerment? This question has been explored in this study. The methodology is based on an online survey of patients visiting such online platforms. In all 701 patients provided the data. Independent variable (homophily) and dependent variable (patient empowerment) have been measured using a 7-point Likert scale. Findings provide that both are weakly correlated, but this correlation is significant. Regression analysis led to a regression model that is fit statistically. This provides basis to encourage patients to visit online support groups. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Impact of Perceived Social Support on Patient Empowerment: A Study of Online Patient Support Groups
Disease-specific online patient support groups have emerged predominantly in last 30years, and these are being visited by a large number of patents. These platforms obviously bring important benefits to the patients visiting them. An important variable is the perceived social support that patients feel they derive while interacting with healthcare providers and fellow patients over there. Patient empowerment is another variable, and which has been found to be a critical factor in overall well-being of patients. How does the perceived social support felt by patients visiting an online patient support group impact their perceived empowerment? This paper explores this question. Research design is associative, and for which the data has been procured online from the patients visiting online patient support groups. The questionnaire comprises of an independent variable (perceived social support) and a dependent variable (patient empowerment). Validated scales have been used. For analysis, a factor analysis was undertaken to reconfirm the validity of the scales. Thereafter, regression equation has been developed to measure the impact. Results show that the model obtained passes the fitness and the independent variable has a significant positive association with patient empowerment. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
The transformative potential of artificial intelligence in building sustainable agricultural systems: Innovations, challenges, and future directions
Artificial Intelligence is revolutionizing agricultural practices by enhancing efficiency, productivity, and sustainability. Through precision agriculture, AI enables data-driven decision-making, optimizing resource use, crop management, and yield prediction. Innovations such as machine learning algorithms and IoT integration facilitate real-time monitoring of soil, weather patterns, and pest control. These technologies address critical challenges like food security and environmental conservation. However, the adoption of AI in agriculture faces obstacles, including high implementation costs, data privacy, and limited access to technology. Future directions involve advancing AI capabilities to support climate-resilient farming, promoting digital inclusion, and developing policy frameworks to address socioeconomic concerns. By leveraging AI, agriculture can transition toward sustainable practices, ensuring food security while minimizing environmental impact. In light of the above perspective, this chapter highlights AI's potential to transform agriculture amidst ongoing challenges. 2025, IGI Global Scientific Publishing. All rights reserved. -
Bridging SDG4 With Innovation for Quality Education: A Way Foreward
Sustainable Development Goal 4 (SDG4) aims to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all. However, achieving this ambitious goal requires more than traditional approaches. Innovation plays a crucial role in bridging the gap between the current state of education and the ambitious targets set by SDG4. It can transform teaching and learning practices, improve access to education, and enhance the relevance and quality of educational outcomes. While innovation holds immense promise for achieving SDG4, there are also challenges that need to be addressed. By embracing technology, fostering pedagogical innovation, and creating supportive policies, one can transform education systems and ensure that all learners have access to quality education and lifelong learning opportunities. This chapter delves into the intersection of SDG4 and innovation, examining how technology and policy can be leveraged to enhance the quality of education and promote digital learning. 2026, IGI Global Scientific Publishing. All rights reserved. -
Transformative Artificial Intelligence for Sustainable Supply Chains: Optimizing Green Logistics and Circular Economy
Artificial intelligence (AI) is revolutionizing supply chain management by providing ways to improve operational effectiveness and sustainability. In supply chain operations, businesses can decrease waste, and lower carbon footprints by utilizing machine learning, predictive analytics, and decision- making. As environmental concerns grow, industries are using AI technologies more and more to improve supply chains' sustainability, efficiency, and transparency. AI greatly enhances distribution and transportation networks by assisting with fuel efficiency, route planning, and emission monitoring via green logistics. Furthermore, by making it easier to reuse, recycle, and remanufacture things, AI advances circular economy models. It helps companies make the shift from linear to circular production systems by forecasting product lifecycle stages and controlling material flows. Keeping in view the above, this chapter analyzes the critical role of AI in shaping future supply chains, where economic performance aligns with environmental stewardship, fostering a more sustainable global economy. 2026, IGI Global Scientific Publishing. -
Navigating the Ethico-Legal Landscape of Blockchain in Healthcare: A Critical Analysis
Blockchain technology offers improved data security, interoperability, and patient empowerment, which could revolutionize the healthcare industry. Its incorporation, however, calls for thorough evaluation of the complicated legal and ethical issues. The global pandemic has exposed the current healthcare system's lack of interoperability and the requirement for reliable clinical data that can be efficiently and securely disseminated to healthcare providers on a large scale. This analysis explores important issues such as algorithmic bias, informed consent, data privacy and ownership, and legal barriers. It looks at current regulatory frameworks and new best practices for using blockchain responsibly in the healthcare industry, highlighting the necessity of stakeholder collaboration to guarantee safe, reliable, and equitable healthcare systems. In light of the above perspective, this chapter explores the ethical and legal implications of blockchain in the healthcare sector. It critically overviews the current laws and regulations in force to implement blockchain in healthcare. 2026, IGI Global Scientific Publishing. All rights reserved. -
Integrating Sustainability with Financial Markets: Risk, Return, and Responsibility
This chapter explores the burgeoning field of green finance and its crucial role in aligning financial markets with sustainable development objectives. It examines how incorporating environmental, social, and governance (ESG) factors influences traditional risk and return profiles, presenting both opportunities and challenges for investors and financial institutions. We delve into innovative financial instruments and strategies designed to mobilize capital towards environmentally sound and socially responsible projects. Furthermore, the chapter critically analyzes the evolving concept of fiduciary responsibility in the context of sustainability, arguing forabroaderinterpretationthatencompasseslong-termvaluecreationandplanetary well-being.Bybridgingthegapbetweenfinancialimperativesandsustainabilitygoals, this chapter underscores the transformative potential of integrating responsibility into the core of financial decision-making for a more resilient and equitable future. Copyright 2026, IGI Global Scientific Publishing. -
Agroecological transformation through farmers' empowerment and IP reform: A human rights-based approach
The transition to agroecology is essential for achieving sustainable food systems, biodiversity conservation, and climate resilience. However, dominant intellectual property (IP) regimes often marginalize small-scale farmers by restricting seed sovereignty and traditional knowledge systems. By recognizing farmers' rights to seeds, knowledge, and fair market access, IP policies can shift from corporate-driven monopolization to collective stewardship models. The chapter advocates for a multi-stakeholder approach that integrates legal, economic, and ecological dimensions, ensuring that farmers' empowerment is at the core of agroecological transitions. By embedding human rights in IP governance, policymakers can foster more just, resilient, and biodiversity-rich food systems, ultimately advancing the global movement for agroecological transformation. This chapter argues that a human rights-based approach to IP reform can empower farmers as key agents of agroecological transformation. 2025, IGI Global Scientific Publishing. All rights reserved. -
Blockchain in industrial supply chains: Tracing the transparency
Over the past several years, blockchain technology has become more and more significant and widely accepted. Independent businesses that are actively involved in the upstream and downstream flows of goods, services, money and information from a source to a customer make a supply chain. Members of the supply chain must collaborate and exchange information in order to be managed effectively. Blockchain technology offers a platform for direct communication between supply chain participants to exchange reliable and unchangeable data, which has the potential to significantly enhance supply chain management and accomplish supply chain performance goals. Notwithstanding its potential, there are obstacles to the broad use of blockchain. Legal and regulatory issues are also very important for supply chain management in the future. Keeping in view the above, the chapter analyzes the role of blockchain in the industrial supply chain and explores the facet of transparency in supply chain management. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Aligning Green Finance With Climate Governance: Strategies for Mitigating Global Warming
Green finance plays a pivotal role in aligning financial systems with climate policy objectives to mitigate global warming. This chapter examines strategies that integrate green finance with regulatory frameworks, ensuring that capital flows support climate resilience and sustainability. It explores mechanisms such as green bonds, sustainability-linked loans, carbon pricing, and public-private partnerships to mobilize investments toward low-carbon technologies. Additionally, the chapter highlights the role of financial institutions in promoting climate disclosure and risk assessment while addressing challenges like greenwashing and policy misalignment. Case studies illustrate successful implementations of green finance policies in different jurisdictions, offering insights into best practices and regulatory advancements. By fostering collaboration between governments, financial markets, and international organizations, green finance can accelerate the transition toward a net-zero economy. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Harnessing Artificial Intelligence for Sustainable Innovation and Policy: The Eco-Intelligence
Artificial Intelligence (AI) is revolutionizing sustainable innovation and policymaking by optimizing resource management, enhancing environmental monitoring, and fostering circular economies. This chapter explores Eco-Intelligence-the integration of AI-driven analytics, predictive modeling, and automation in addressing environmental challenges. By leveraging machine learning, and digital twins, AI enables real-time decision-making for climate adaptation, carbon footprint reduction, and green supply chains. Also, AI-driven regulatory frameworks enhance compliance with sustainability standards, bridging the gap between technological advancement and environmental governance. However, ethical concerns, algorithmic biases, and data privacy issues pose challenges to AI's effective deployment in sustainability policy. This chapter critically examines the intersection of AI, environmental stewardship, and regulatory landscapes, proposing a balanced approach to harness AI's potential for long-term ecological and economic resilience. 2026, IGI Global Scientific Publishing. All rights reserved. -
Farmers' Rights at the Intersection of Intellectual Property and Human Rights: Balancing Innovation and Economic Sustainability
Farmers' rights are at the intersection of intellectual property (IP) law, human rights, and sustainable agricultural practices. As global food systems evolve, the increasing commercialization of seeds, genetic resources, and agricultural knowledge has raised concerns over farmers' autonomy, economic sustainability, and cultural heritage. This chapter explores the intersection of farmers' rights, IP law, and human rights, analyzing how legal frameworks impact their access to seeds, traditional knowledge, and economic sustainability. It highlights the tension between seed sovereignty and corporate patenting, where restrictive IP protections often limit farmers' ability to save, exchange, and breed seeds-practices that have been fundamental to sustainable agriculture for generations. Finally, it advocates for harmonized approach that upholds farmers' rights while fostering sustainable agricultural practices. By bridging legal protections and cultural heritage, the chapter underscores the importance of inclusive policies that ensure both economic viability and environmental resilience. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Supply Chain 4.0: The Digital Twin Revolution
The chapter explores the transformative role of digital twin technology in the evolution of modern supply chains. As businesses confront increasing complexity, volatility, and sustainability demands, digital twins offer realtime, data-driven solutions to simulate, monitor, and optimize supply chain processes. This chapter examines the integration of digital twins across logistics, inventory, demand forecasting, and sustainability tracking, highlighting their ability to enhance agility, resilience, and efficiency. It also addresses critical enablers such as IoT, AI, cloud computing, and discusses ethical, legal, and regulatory considerations in implementation. Through a strategic lens, it offers guidelines for adoption, policy recommendations, and identifies research gaps for future exploration. Positioned at the intersection of Industry 4.0 and sustainability, the digital twin revolution is redefining the future of supply chain management. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Harnessing AI for Environmental Hazard Mitigation and Resilience: Pathways to a Safer Future
This chapter explores the transformative potential of artificial intelligence (AI) in mitigating environmental hazards and enhancing resilience to climate- related challenges. AI technologies are revolutionizing environmental monitoring, risk assessment, and disaster response through advanced data analytics, machine learning, and predictive modeling. By leveraging AI, stakeholders can predict and mitigate the impacts of natural disasters, improve resource management, and foster resilient infrastructures. The chapter examines the various applications of AI in hazard prediction, such as flood forecasting, wildfire management, and storm tracking, alongside its role in real- time monitoring and adaptive response systems. Furthermore, it highlights the ethical considerations, challenges, and limitations of deploying AI in environmental management. Through case studies and emerging practices, this chapter outlines pathways for harnessing AI to safeguard communities and ecosystems, ensuring a more resilient and sustainable future. 2025 by IGI Global Scientific Publishing. All rights reserved. -
AI-Powered Military Logistics and Strategy: A Paradigm Shift in Modern Warfare
The function of logistics and strategic planning has expanded beyond traditional supply lines as contemporary warfare becomes more complicated. AI is changing military operations by facilitating autonomous logistics systems, real-time data processing, and quicker decision-making. This change is altering how military strategy is developed and implemented, going beyond efficiency improvements. AI provides a level of adaptability never before achievable, from autonomous transport systems and coordinated battlefield support to predictive maintenance of combat vehicles. An intelligent and robust logistics ecosystem is being fostered by the integration of technologies such as swarm robotics, satellite-based monitoring, and quantum-enhanced optimization. But this change also presents operational, ethical, and policy issues. This chapter addresses the hazards of reliance and misalignment while examining the complex effects of AI on military logistics and strategy. Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development. -
AI-Driven Image Forensics for Cybercrime Detection: Chain of Custody and Legal Admissibility
Advanced techniques for analyzing and verifying digital images make AI-driven image forensics a crucial tool in detecting cybercrime. With the rise of cybercrime involving altered and forged images, AI-driven techniques like deepfake detection and metadata analysis present hopeful means for uncovering evidence. The incorporation of AI into forensic investigations, however, presents considerable challenges concerning the chain of custody and the legal admissibility of digital evidence. To ensure that digital evidence stays intact and unmodified during the investigation, it is crucial to uphold an uninterrupted chain of custody. To set forth unambiguous criteria regarding the admissibility of AI-processed evidence in court, legal systems must also grapple with the progressing character of AI. This chapter investigates how AI-driven forensics, maintaining the integrity of digital evidence, and the legal structures necessary to guarantee justice in the era of artificial intelligence intersect. 2026 by IGI Global Scientific Publishing. -
The Dual Challenge of Genetically Modified Crops for the Environment and Farmers Rights
The potential environmental benefits of genetically modified (GM) crops are accompanied by worries about ecological dangers and the degradation of farmers' rights. The relationship between genetically modified crop technology, environmental sustainability, and seed sovereignty laws is critically examined in this chapter. Certain genetically modified features may result in biodiversity loss, soil degradation, and genetic contamination, even though they can help minimize pesticide use and increase climate resistance. Furthermore, traditional farming methods are frequently undermined by the spread of intellectual property regimes, which restrict farmers' capacity to share and conserve seeds. Diverse socio-legal results are illustrated by case studies from Africa, the USA, and India, exposing a gap in global governance. To guarantee that GM technologies are in line with ecological integrity and farmers' autonomy, the chapter advocates for a multifaceted policy framework that balances innovation and justice, encourages participatory regulation, and funds interdisciplinary research. 2026 by IGI Global Scientific Publishing. All rights reserved. -
The Role of Local and Regional Governments in Fostering Cross-Border Climate Cooperation
With climate change increasingly crossing political boundaries, the importance of local and regional governments (LRGs) in promoting cross-border climate cooperation has grown significantly. LRGs are often better positioned than national governments to tackle localized climate challenges through context-specific collaboration. This chapter examines the growing importance of LRGs in transboundary climate governance, emphasizing their ability to innovate, involve communities, and carry out adaptive solutions. It investigates mechanisms like cross-border networks, inter-municipal forums, joint environmental initiatives, and digital platforms that facilitate collaboration among subnational actors across borders. Through the examination of global case studies and policy scrutiny, this chapter pinpoints essential obstacles-like financial shortfalls and legal constraints-and proposes tactical policy suggestions, such as bolstering legal acknowledgment, establishing regional climate funds, and fostering knowledge sharing. 2026, IGI Global Scientific Publishing. All rights reserved. -
Addressing the Problems of Forest and Biodiversity in Developing Nations: A Conservation Conundrum
Forests and biodiversity are essential for ecological stability and human well-being, but they confront unprecedented threats in developing countries. This chapter investigates the multifaceted interactions among environmental decline, socio-economic stresses, inadequate governance, and global market forces that drive biodiversity loss and deforestation. It underscores the difficulties of reconciling development with conservation in areas characterized by poverty, land tenure disputes, and weak institutions. The chapter emphasizes the necessity for methods that are integrated, participatory, andequitable throughan examination oflocaland global frameworks, such as community-based conservation, indigenous knowledge, and international agreements. Case studies demonstrate conservation initiatives that succeeded and others that did not, providing vital perspectives on the future of biodiversity governance. In conclusion, the chapter calls for global cooperation, inclusive policy frameworks, and context-specific strategies to ensure sustainable management of forests and biodiversity. Copyright 2026 by IGI Global Scientific Publishing.