Название: Building Next-Gen ESG Platforms with IoT and AI for Sustainable Development Goals
Автор: Chandrasekar Vuppalapati
Издательство: CRC Press
Год: 2026
Страниц: 321
Язык: английский
Формат: pdf (true)
Размер: 41.9 MB

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. Combining practical implementation - codes, training pipelines, and deployment guides - with strategic Environmental, Social, and Governance (ESG) insights, the book provides a cross-disciplinary framework to building transparent, scalable, and data-driven ESG platforms aligned with the UN Sustainable Development Goals.

Machine Learning (ML) is the subset of AI that uses statistical techniques to enable machines to improve with experience. Machine learning algorithms detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. The algorithms also adapt in response to new data and experiences to improve efficiency and efficacy over time. ML, importantly, enables to calibrate auto calibrate, correct or re-build itself if it sees the data that are being drifted, of course, from original trained model. The availability of such features dawns a new era of commuting that adapts itself to course correctly or to hyper-scale efficiently as it sees new. There are three types of learning that AI uses supervised learning, unsupervised learning, and semi-supervised learning. For more on these topics, please refer to my book.