Convergence Strategies For Green Computing And Sustainable Development

Convergence Strategies for Green Computing and Sustainable Development presents a comprehensive exploration of the potential of emerging technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), fog computing, and cloud computing, to aid in fostering a sustainable future. It examines how these technologies can reduce the impact of unsustainability in societies, the environment, and natural resources, offering invaluable insights into harnessing their power for positive change. Convergence Strategies for Green Computing and Sustainable Development serves as a comprehensive strategy that holistically understands, transforms, and develops technological systems in society. This book caters to a diverse range of readers, including graduate students, researchers, working professionals seeking knowledge, and industry experts seeking information about new trends. With its recommended topics and comprehensive table of contents, readers can gain in-depth knowledge about sustainable cloud computing, artificial intelligence and machine learning for sustainable development, sustainable wireless systems and networks, and the crucial role of green IoT and Edge-AI in driving a sustainable digital transition.

"This book focuses on information technology using sustainable green computing to reduce energy and resources used"--Provided by publisher.

In the age of corporate responsibility, green technology and sustainability continue to grip the consciousness of businesses. However, the development of appropriate business-driven green computing applications requires an awareness of the best practices of the green agenda. Green Computing Strategies for Competitive Advantage and Business Sustainability provides emerging research on maintaining an eco-friendly environment regarding cloud computing and promoting reusability. While highlighting competitive advantages, power consumption, and project evaluation, readers will learn about various techniques for reducing energy consumption in cloud performance and information technology systems. This book is a vital resource for academics, researchers, students, professionals, and managers interested in novel trends in green computing applications and technology.

As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems.

In an era overshadowed by pressing global challenges such as climate change, burgeoning populations, and the depletion of natural resources, the agricultural landscape is at a critical juncture. The need for sustainable practices has never been more urgent, with conventional methods struggling to meet the demands of a growing population while grappling with environmental degradation. Harnessing NanoOmics and Nanozymes for Sustainable Agriculture delves into the heart of the problem, navigating the intricate web of challenges facing agriculture today. From dwindling crop yields to the environmental repercussions of conventional farming practices, the urgency to find innovative, sustainable solutions is paramount. Harnessing NanoOmics and Nanozymes for Sustainable Agriculture offers a comprehensive exploration of nanotechnology's potential to revolutionize agriculture, presenting a promising pathway toward enhanced productivity, minimizing environmental impact, and optimal resource utilization.

As the global population continues to grow, the depletion of Earth's resources poses a significant challenge in ensuring food security for current and future generations. This book addresses this pressing issue by presenting innovative strategies and methods to reduce food loss, enhance production, identify alternative ingredients, and digitize the food system. It explores topics like the circular economy, cellular agriculture, artificial intelligence in food production, and novel sources of ingredients like microalgae and insects. Engineers play a pivotal role in translating ideas into tangible products and services that enhance human lives. Innovations in Engineering and Food Science is a comprehensive guide that explores the latest advancements, technologies, challenges, and solutions in the domains of engineering and food science. This book delves into the integration of cutting-edge technologies such as Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), Quantum Computing, and Virtual and Augmented Reality, showcasing their potential to revolutionize the engineering landscape. With a focus on emerging technologies and practical solutions, this book serves as a valuable resource for researchers, students, academicians, and professionals in these fields.

In recent years, the advent of biosensors and bioelectronics has facilitated the swift and precise detection of numerous biomolecules or pathogens in animal samples, aquatic habitats, and plants. These technologies have emerged as potent assets for the agriculture and aquaculture industries. Many experts have raised the question; how might the integration of biosensors into portable devices or automated monitoring systems enable on-site and real-time detection of diverse biomolecules or pathogens? Agriculture and Aquaculture Applications of Biosensors and Bioelectronics presents the recent developments in biological recognition elements, transducer materials, and signal processing techniques for biosensors and bioelectronics used in agriculture and aquaculture applications. Sophisticated biosensors and bioelectronics operate through the immobilization of biological recognition components—such as enzymes or antibodies—on a transducer surface. This immobilization process allows for the targeted recognition and binding of biomolecules or pathogens. The resulting electrical, optical, or chemical changes triggered by the recognition event are quantifiable through various methods and are often enhanced by applications utilizing artificial intelligence (AI). The necessity for high sensitivity and selectivity, the optimization of biocompatibility and stability, and the integration of biosensors with AI-aided solutions are just some of the challenges and opportunities in developing biosensors for high-tech agriculture and aquaculture. This book targets a mixed audience of biotechnology engineers, biosensors scientists, bioelectronics researchers, high-tech agriculture analysts, Ph.D. scholars, researchers, academics, professionals, engineers, and students.