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Springer Sustainable IoT and Data Analytics Machine Learning - Springer

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Description

Explore the convergence of sustainable IoT, data analytics, and machine learning techniques in this comprehensive volume from Springer. This book examines innovative approaches to environmental sciences and cutting-edge business technology applications, bridging the gap between sustainability goals and intelligent systems. Discover practical methodologies for implementing machine learning solutions within IoT ecosystems, leveraging data analytics to drive environmental impact and business transformation. The volume provides researchers, practitioners, and technology leaders with essential frameworks for developing smart, data-driven applications that address real-world challenges in sustainability and digital innovation.

Key Features

Springer publishing brings authoritative research on sustainable IoT systems and their practical applications in environmental sciences.

Machine learning techniques are integrated with data analytics methods to solve contemporary sustainability and technology challenges.

The book covers contributions spanning environmental sciences and innovative business technology for comprehensive industry understanding.

Data-driven approaches demonstrate how IoT platforms can be optimised for both ecological impact and commercial success.

Advanced analytics methodologies enable extraction of actionable insights from complex IoT datasets for strategic decision-making.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
28 September 2024
Listed Since
14 June 2024

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