Building Next-Gen ESG Platforms with IoT and AI for Sustainable Development Goals

1. Auflage 2026
ISBN: 978-1-032-85607-0
Verlag: Taylor & Francis Ltd

Buch, Englisch, 320 Seiten, Format (B × H): 156 mm x 234 mm

This book delivers a practical blueprint for applying AI, IoT, and advanced analytics to drive measurable ESG outcomes. It covers machine learning, deep learning, generative AI, and fast language models for edge use, with benchmarks like MMLU, GPQA, and MGSM. Step-by-step guides teach ESG IoT model building, neural network fine-tuning, and RAG implementations. Application chapters span IoT-enabled GHG monitoring, methane/rumination tracking with Class 10 sensors, and AI for remote farming. Real-world case studies and deployment pipelines provide innovators, policymakers, and leaders with a cross-disciplinary framework aligned to UN Sustainable Development Goals.

Zielgruppe

Academic, Postgraduate, and Professional Reference

Autoren/Hrsg.

Vuppalapati, Chandrasekar

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Geowissenschaften Umweltwissenschaften Lebensmittelsicherheit und -versorgung
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Lebensmitteltechnologie und Getränketechnologie
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Nachhaltige Landwirtschaft
• Geowissenschaften Umweltwissenschaften Nachhaltigkeit
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Wirtschaftswissenschaften Volkswirtschaftslehre Internationale Wirtschaft Entwicklungsökonomie & Emerging Markets
• Geowissenschaften Umweltwissenschaften Umweltwissenschaften

Inhaltsverzeichnis

Preface. 1. Artificial Intelligence. 2. IoT and AI Models. 3. Environmental, Social, and Governance (ESG). 4. IoT and Greenhouse Gas (GHG) Emissions Models for Creating Sustainable Communities. 5. AI, IoT, and Business Process Automation for Enhanced Productivity, Economic Sustainability, and Reduced Inequalities. 6. Next-Gen AI Climate Models Revolutionizing Agricultural Inputs and Boosting Biodiversity.

Über Autor(innen)

Chandrasekar Vuppalapati is a Software Principal Architect, CTO, Executive, Entrepreneur, Industrialist, and Educator with expertise in Enterprise Software Architectures, Cloud Computing, Artificial Intelligence, Machine Learning, Data Analytics, IoT, and Product Management. Since1994, he has built a distinguished career in technology leadership, consulting, and innovation. He holds a master’s in software engineering from San José State University and an MBA from Santa Clara University.

Chandra has held senior leadership roles at Microsoft, GE Healthcare, Cisco Systems, St. Jude Medical, and Lucent Bell Labs, while consulting for Deloitte, PwC, Johnson & Johnson, T-Mobile, State Street Bank, Humana, Kroger, Verizon, Shell, and BP. Since 2013, he has taught graduate courses in Software Engineering, Cloud Technologies, and Data Science at San José State University while advising Cisco, Lam Research, and others. As Principal Investigator for the Valley School of Nursing, he pioneered Virtual Reality-based healthcare education. Chandra leads global initiatives in Agriculture Analytics, Dairy Analytics, Specialty Crops Analytics, and Class-10 Wearable Veterinary Sensors, including the Sriya AgriVet Monitor, advancing IoT-driven ESG solutions for farmers worldwide. Under his leadership, Hanumayamma Corp (an initiative by Chandra) earned the Fast Company Innovation by Design Award (2023), presented its products at SPACE 2025 in Rennes, France, and secured USPTO trademarks. A decorated innovator, Chandra won the US National IEEE Voice Data Challenge (2018) and has published over 29 IEEE papers along with several books on AI, IoT, agriculture, and food security. He has also served as editor and chair for major IEEE conferences across the US and Europe.