Ai And Data Analytics In Precision Agriculture For Sustainable Development
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AI and Data Analytics in Precision Agriculture for Sustainable Development
This book offers a comprehensive analysis of artificial intelligence (AI) and data analytics in precision agriculture. The integration of technology in agriculture is revolutionizing traditional farming practices, paving the way for sustainability. Precision farming, powered by AI, IoT, and big data, optimizes resource use by enabling real-time monitoring of soil health, weather conditions, and crop growth. Automated irrigation systems and drones reduce water wastage and enhance productivity. Biotechnology advances, such as genetically modified crops and CRISPR gene editing, improve yield, pest resistance, and climate adaptability. Vertical farming and hydroponics offer space-efficient solutions, minimizing land degradation and water consumption. Robotics and autonomous machinery streamline labor-intensive tasks, reducing reliance on chemical inputs. Blockchain ensures transparency in the food supply chain, promoting fair trade and reducing food fraud. Renewable energy sources, like solar-powered farms, further lower agriculture’s carbon footprint. By adopting these innovations, farmers can produce more with fewer resources, ensuring food security while preserving the environment. Embracing technology-driven agriculture is crucial for meeting global food demands sustainably, combating climate change, and fostering economic resilience in farming communities. The future of agriculture lies in intelligent, data-driven, and eco-friendly solutions that balance productivity with environmental stewardship.
Artificial Intelligence and Data Science for Sustainability: Applications and Methods
The integration of artificial intelligence (AI) and data science (DS) into sustainability efforts is increasingly crucial as the world faces environmental and resource challenges. By leveraging advanced AI and DS techniques, we can create innovative solutions for sectors like energy, agriculture, and waste management, promoting long-term sustainability. These technologies have the potential to optimize processes, reduce environmental footprints, and support smarter decision-making across industries. Ultimately, AI and DS are key to advancing both the efficiency and impact of sustainability efforts, contributing to a more sustainable future for society at large. Artificial Intelligence and Data Science for Sustainability: Applications and Methods explores the application of AI and DS techniques and methodologies in addressing various sustainability challenges. It brings together cutting-edge research, case studies, and practical applications that demonstrate how AI can be leveraged to promote sustainable development across diverse domains. Covering topics such as structural optimization, drone imagery, and development financing, this book is an excellent resource for computer scientists, computer engineers, urban planners, sustainability professionals, government officials, policymakers, researchers, professionals, scholars, academicians, and more.
Sustainable Development through Machine Learning, AI and IoT
This book constitutes the revised selected papers of the First International Conference, ICSD 2023, virtually held in Delhi, India, during July 15–16, 2023. The book comprises 31 full papers that were selected from a total of 129 submissions. It provides insights into the latest research and advancements in sustainable development through the integration of machine learning, artificial intelligence, and IoT technologies. It serves as a valuable resource for researchers, practitioners, and policymakers working in the field of sustainable development.