Download or read book Harnessing High Performance Computing and AI for Environmental Sustainability written by Naim, Arshi and published by IGI Global. This book was released on 2024-05-15 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is addressing the insistent challenge of climate change, and the need for innovative solutions has become paramount. In this period of technical developments, artificial intelligence (AI) has emerged as a powerful instrument with enormous prospects to combat climate change and other environmental subjects. AI's ability to process vast amounts of data, identify patterns, and make intelligent predictions offers unprecedented opportunities to tackle this global crisis. High-Performance Computing (HPC) or super-computing environments address these large and complex challenges with individual nodes (computers) working together in a cluster (connected group) to perform massive amounts of computing in a short period. Creating and removing these clusters is often automated in the cloud to reduce costs. Computer networks, communication systems, and other IT infrastructures have a growing environmental footprint due to significant energy consumption and greenhouse gas emissions. To address this seemingly self-defeating conundrum, and create a truly sustainable environment, new energy models, algorithms, methodologies, platforms, tools, and systems are required to support next-generation computing and communication infrastructures. Harnessing High-Performance Computing and AI for Environmental Sustainability navigates through AI-driven solutions from sustainable agriculture and land management to energy optimization and smart grids. It unveils how AI algorithms can analyze colossal datasets, offering unprecedented insights into climate modeling, weather prediction, and long-term climate trends. Integrating AI-powered optimization algorithms revolutionizes energy systems, propelling the transition towards a low-carbon future by reducing greenhouse gas emissions and enhancing efficiency. This book is ideal for educators, environmentalists, industry professionals, and researchers alike, and it explores the ethical dimensions and policies surrounding AI's contribution to environmental development.

Download or read book Green AI Powered Intelligent Systems for Disease Prognosis written by Khanna, Ashish and published by IGI Global. This book was released on 2024-08-23 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experts in Medicine are under new pressures of advancing their studies while also reducing the impact they leave on the environment. Researchers within the fields of bio-neuro informatics, healthcare, engineering, and medical sciences require a dynamic platform that bridges the realms of academia, science, industry, and innovation. Green AI-Powered Intelligent Systems for Disease Prognosis facilitates a crossroads for a diverse audience interested in these two seldom coalesced concepts. Academicians, scientists, researchers, professionals, decision-makers, and even aspiring scholars all find a space to contribute, collaborate, and learn within the platform that this book provides. The book's thematic coverage is unequivocally compelling; by exploring the intersections of bio-neuro informatics, healthcare, engineering, and medical sciences, it captures the spirit of interdisciplinary research. It delves into well-established domains while also casting a spotlight on emerging trends that have the potential to reshape our understanding of these fields. Two prominent tracks form the backbone of the book's content. The first covers the Bioinformatics and Data Mining of Biological Data (BiDMBD), and unravels the intricacies of biomedical computation, signal analysis, clinical decision support, and health data mining. This approach holds a treasure trove of insights into the mechanisms of health data acquisition, clinical informatics, and the representation of healthcare knowledge. The second covers Biomedical Informatics and is a symposium of computational modeling, genomics, and proteomics. Here, the fusion of data science with medical sciences takes center stage.

Download or read book Green AI Insights Into Deep Learning s Looming Energy Efficiency Crisis written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: As demands grow to integrate artificial intelligence into every aspect of industry, commerce, and life, deep learning's exploding energy cost has become a looming crisis, making AI systems a salient energy-efficiency challenge. One might expect that doubling a neural network's size would halve its error rate, or at least allow it to achieve greater performance given the same amount of time and energy. I will present clear and substantial scientific evidence which indicates that not only is this intuition wildly wrong, but that neural networks scale so poorly that to increase deep learning performance by only a small fraction can easily require an order of magnitude or more increase in computational resources and energy. Further, the marginal trade-off price of to increase model performance rapidly explodes as performance targets are increased. To address this challenge, I will provide a toolkit of techniques that can be applied today to mitigate the inefficiency of modern deep learning. And, I will conclude by illuminating a practical path forward towards efficient, Green AI.

Download or read book Towards Green AI written by Sangeeta Srivastava (Researcher in deep learning) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep neural networks have not only evolved to produce state-of-the-art artificial intelligence (AI) models, but also generalize well, especially when the network has a large capacity and access to a comparable massive training dataset. These models are computationally and environmentally inefficient. Such research works are known as Red AI. However, it is challenging to develop algorithms that generate cost-effective models for Green AI without sacrificing predictive strength or generality. This dissertation shows how we can effectively integrate domain knowledge, either implicitly or explicitly, into an end-to-end learning pipeline to reduce the training and testing overhead of a neural network. In particular, we exploit the target data and task information to make two types of modifications in the learning pipeline, each of which helps to lower the neural network's run-time costs in unique ways. We re-define the learning task as one or more "simpler" subtask(s) so that the subtask(s) requires fewer parameters and training data. Explicit inclusion of a regularization term in the objective function allows us to limit the exploration space to those that are both relevant and plausible for a given application. We demonstrate the benefits of the above methodologies with the help of three applications with disparate challenges: 1) acoustic event detection, 2) radar classification, and 3) scientific problems based on eigenvalue solvers. Acoustic and radar applications require on-device intelligence and rely on Cortex-M7/M3 microcontroller-based edge devices with limited hardware resources and a low power budget. On the other hand, eigenvalue problems yield memory- and compute-intensive models primarily due to the size of the output layer that grows exponentially with the number of particles in the system. For the acoustic event detector, we exploit unlabeled data from the target domain to constrain knowledge transfer from a large "teacher" model to a smaller "student" model such that the knowledge is relevant to the target problem. This results in a student with orders of magnitude lower static and dynamic memory requirements. For the N + 1 radar classification problem, where the +1-class corresponds to environmental noise, we use an application-specific ontology to decompose the end-to-end learning into two hierarchical subproblems. A more complex model trained to classify the N source classes is invoked occasionally, i.e., only when there is no environmental noise. This conditional invocation makes the resulting model 3.5x more run-time efficient than feature-engineered shallow solutions and gives the best trade-off between accuracy and efficiency. As for the eigenvalue solvers, we decompose the complex regression task of prediction of high-dimensional eigenvector into multiple simpler and parallel subtasks such that the inputs in each subtask have similar physical properties. We learn a parameter-efficient "expert" network for each subtask. Our proposed physics-guided architecture is 150x smaller than the network trained to learn the complex task while being competitive in generalization. Our results also show that domain knowledge helps reduce the amount of supervised data needed for model training.

Download or read book Artificial Intelligence for Environmental Sustainability and Green Initiatives written by Aboul Ella Hassanien and published by Springer Nature. This book was released on with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Atlas of AI written by Kate Crawford and published by Yale University Press. This book was released on 2021-04-06 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The hidden costs of artificial intelligence, from natural resources and labor to privacy and freedom What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? In this book Kate Crawford reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequality. Drawing on more than a decade of research, award-winning science, and technology, Crawford reveals how AI is a technology of extraction: from the energy and minerals needed to build and sustain its infrastructure, to the exploited workers behind "automated" services, to the data AI collects from us. Rather than taking a narrow focus on code and algorithms, Crawford offers us a political and a material perspective on what it takes to make artificial intelligence and where it goes wrong. While technical systems present a veneer of objectivity, they are always systems of power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.

Download or read book Perspectives on the Transition Toward Green and Climate Neutral Economies in Asia written by Ordóñez de Pablos, Patricia and published by IGI Global. This book was released on 2023-07-24 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge management and advanced information technologies such as AI, IoT, machine learning, and more can create digital tools and solutions to build more resilient, climate neutral, and green economies and societies. These digital tools and solutions and knowledge management can have a heavy impact on the achievement of sustainable development goals (SDGs) in Asia. Perspectives on the Transition Toward Green and Climate Neutral Economies in Asia offers innovative conceptual frameworks and theories, case studies, and empirical studies to understand how knowledge management and digital innovation can foster the transition towards more circular and climate neutral economies as well as greener economies in Asia. This book discusses how key and enabling digital tools and solutions and knowledge management can support the achievement of SDGs by 2030. Covering topics such as climate neutral economies, image recognition, and usability evaluation, this premier reference source is an excellent resource for deans, heads of departments, directors, politicians, policymakers, corporate heads, senior general managers, managing directors, librarians, students and educators of higher education, academicians, and researchers.

Download or read book Artificial Intelligence and Sustainability written by Mohamed Ahmed Alloghani and published by Springer Nature. This book was released on 2023-11-25 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives readers the tools to craft AI systems that don't just thrive today, but endure sustainably into the future. Whether a trailblazer or an aspiring innovator, this book enables readers to resonate with the ambitions of software developers, data scientists, and AI practitioners. The author covers the latest techniques and best practices for energy efficiency, reducing carbon footprints, and ensuring fair and ethical AI. The book also addresses important issues such as AI governance, managing risks, and ensuring transparency. Topics covered include understanding the relationship between AI and sustainable development, strategies for building efficient AI systems, and ethical considerations in AI development, among others. The author includes case studies of companies and organizations that have successfully implemented sustainable AI software development practices. Therefore, this book will be of interest to AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.

Download or read book Towards Net Zero Targets written by Neha Sharma and published by Springer Nature. This book was released on 2022-09-16 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the use of technology, data science and open data to achieve the net-zero carbon emissions target set up by the Paris Agreement on climate change. There have been many discussions around sustainability and climate change solutions to mitigate the negative impact. However, using technology levers to tackle climate challenges is rarely seen as the most significant catalyst. The available research in this field is generally qualitative in nature, where technology and data have not yet been leveraged. By using AI/ML, the book predicts the climate change consequences arising due to investment in fossil fuel sectors, estimates CO2 emissions from the transport sector, forecasts average land temperature due to non-renewable sources of energy, and segments Indian states on the basis of household carbon emissions. The researchers, policymakers, students, teachers, educational institutions, governments, regulators, companies, international organizations, etc., will benefit immensely by referring to this book. Moreover, the endeavour of this book is to provide a decarbonized environment and a better tomorrow to the next generation.

Download or read book Reviews and Perspectives on Smart and Sustainable Metropolitan and Regional Cities written by Tan Yigitcanlar and published by Mdpi AG. This book was released on 2021-12-24 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: The notion of smart and sustainable cities offers an integrated and holistic approach to urbanism by aiming to achieve the long-term goals of urban sustainability and resilience. In essence, a smart and sustainable city is an urban locality that functions as a robust system of systems with sustainable practices to generate desired outcomes and futures for all humans and non-humans. This book contributes to improving research and practice in smart and sustainable metropolitan as well as regional cities and urbanism by bringing together literature reviews and scholarly perspective pieces, forming an open access knowledge warehouse. It contains contributions that offer insights into research and practice in smart and sustainable metropolitan and regional cities by producing in-depth conceptual debates and perspectives, insights from the literature and best practice, and thoroughly identified research themes and development trends. This book serves as a repository of relevant information, material, and knowledge to support research, policymaking, practice, and the transferability of experiences to address challenges in establishing smart and sustainable metropolitan as well as regional cities and urbanism in the era of climate change, biodiversity collapse, natural disasters, pandemics, and socioeconomic inequalities.

Download or read book Green Internet of Things and Machine Learning written by Roshani Raut and published by John Wiley & Sons. This book was released on 2022-01-10 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Health Economics and Financing Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment. The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare. Audience The book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.

Download or read book Towards the Sustainability of AI written by Aimee Wynsberghe and published by Mdpi AG. This book was released on 2023-03-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our era is characterized by two major phenomena. On the one hand, we are confronted by climate and environmental crises constituted by, among others, changing weather patterns, loss of biodiversity and natural wildlife, and ecosystem degradation. On the other hand, we are experiencing an ongoing technological evolution culminating in the rise of artificial intelligence (AI). The popular notion of "AI for Sustainability" constitutes an attempt to connect these two phenomena in a beneficial way by using AI to alleviate climate and environmental worries. AI is increasingly being used in the analysis, mitigation, and prevention of the climate and environmental crises and their effects. Much less attention has been paid to the idea of the "Sustainability of AI", which focusses on the materiality of AI technologies themselves. Indeed, what are the hidden costs of AI? Although we use AI in combatting the climate and environmental crises, does it not have its own contributions to these crises? And, if so, how do we account for these contributions? The Special Issue "Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI" is the first attempt to address the topic of "Sustainable AI" from a multi-disciplinary perspective. The authors that contributed to this issue come from diverse fields such as philosophy, ethics, sociology, law, and engineering. The included papers represent the first steps in understanding what it means to tackle the climate and environmental crises with AI while refraining from aggravating these crises.

Download or read book Internet of Things written by Aurora González-Vidal and published by Springer Nature. This book was released on 2023-01-01 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised selected papers from the refereed proceedings of the 5th The Global IoT Summit, GIoTS 2022, which took place in Dublin, Ireland, in June 20–23, 2022. The 33 full papers included in this book were carefully reviewed andselected from 75 submissions. They were organized in topical sections as follows: ioT enabling technologies; ioT applications, services and real implementations; ioT security, privacy and data protection; and ioT pilots, testbeds and experimentation results.

Download or read book AI for the Sustainable Development Goals written by Henrik Skaug Sætra and published by CRC Press. This book was released on 2022-02-23 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is artificial intelligence? What are the Sustainable Development Goals (SDGs)? How does AI affect the SDGs? Artificial Intelligence has a real impact on our lives and on our environment, and the Sustainable Development Goals enable us to evaluate these impacts in a systematic manner. This book shows that doing so requires us to understand the context of AI – the infrastructure it is built on, who develops it, who owns it, who has access to it, who uses it, and what it is used for – rather than relying on an isolationist theory of technology. By doing so, we can analyze not only the direct effects of AI on sustainability, but also the indirect – or second-order – effects. AI for the Sustainable Development Goals shows how AI potentially affects all SDGs – both positively and negatively.

Download or read book Green Sustainability Towards Innovative Digital Transformation written by Dalia Magdi and published by Springer Nature. This book was released on 2023-11-15 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of best selected research papers presented at the Third World Conference on Internet of Things: Applications & Future (ITAF 2023) organized by Global Knowledge Research Foundation in Cairo during February 4–5, 2023. It includes innovative works from researchers, leading innovators, business executives, and industry professionals to examine the latest advances and applications for commercial and industrial end users across sectors within the emerging Internet of things ecosphere. It shares state-of-the-art as well as emerging topics related to Internet of things such as big data research, emerging services and analytics, Internet of things (IoT) fundamentals, electronic computation and analysis, big data for multi-discipline services, security, privacy and trust, IoT technologies, and open and cloud technologies.

Download or read book Towards Sustainable Artificial Intelligence written by Ghislain Landry Tsafack Chetsa and published by Apress. This book was released on 2021-08-14 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: So far, little effort has been devoted to developing practical approaches on how to develop and deploy AI systems that meet certain standards and principles. This is despite the importance of principles such as privacy, fairness, and social equality taking centre stage in discussions around AI. However, for an organization, failing to meet those standards can give rise to significant lost opportunities. It may further lead to an organization’s demise, as the example of Cambridge Analytica demonstrates. It is, however, possible to pursue a practical approach for the design, development, and deployment of sustainable AI systems that incorporates both business and human values and principles. This book discusses the concept of sustainability in the context of artificial intelligence. In order to help businesses achieve this objective, the author introduces the sustainable artificial intelligence framework (SAIF), designed as a reference guide in the development and deployment of AI systems. The SAIF developed in the book is designed to help decision makers such as policy makers, boards, C-suites, managers, and data scientists create AI systems that meet ethical principles. By focusing on four pillars related to the socio-economic and political impact of AI, the SAIF creates an environment through which an organization learns to understand its risk and exposure to any undesired consequences of AI, and the impact of AI on its ability to create value in the short, medium, and long term. What You Will Learn See the relevance of ethics to the practice of data science and AI Examine the elements that enable AI within an organization Discover the challenges of developing AI systems that meet certain human or specific standards Explore the challenges of AI governance Absorb the key factors to consider when evaluating AI systems Who This Book Is For Decision makers such as government officials, members of the C-suite and other business managers, and data scientists as well as any technology expert aspiring to a data-related leadership role.

Download or read book Artificial Intelligence AI and Customer Social Responsibility CSR written by Reem Khamis Hamdan and published by Springer Nature. This book was released on with total page 1093 pages. Available in PDF, EPUB and Kindle. Book excerpt: