Industrial IoT and sustainable development

Official URL: https://dx.doi.org/10.1002/9781394337262.ch07

The Industrial Internet of Things (IIoT) represents a pivotal force in the ongoing digital transformation of industrial ecosystems. As industries face rising sustainability demands and regulatory expectations, IIoT offers powerful tools for enhancing energy efficiency, minimizing waste, and fostering transparency through real-time data analytics. This chapter presents an integrated overview of how IIoT intersects with the principles of sustainable development. We explore smart manufacturing applications such as artificial intelligence (AI)-powered predictive maintenance, material efficiency improvements, and circular economy-aligned factory designs. The role of big data and machine learning in enabling real-time environmental monitoring and sector-specific optimizations is critically examined. Further, we address cybersecurity, ethical AI, and policy frameworks that ensure trust, compliance, and interoperability in IIoT systems. Finally, we highlight emerging technologies, digital twins, edge AI, and federated learning, that hold promise for building scalable, secure, and privacy-preserving IIoT architectures. Through a synthesis of empirical studies, use cases, and future directions, this chapter offers a roadmap for implementing IIoT as a catalyst for achieving global sustainability targets.