Pathways to a Data-driven Green Future for Building Integrated, Intelligent Digital Sustainability
TL;DR
How the fundamental digital technologies, Internet of Things, Artificial Intelligence, machine learning, digital twins, edge computing, and blockchain facilitate environmental objectives in the energy sector by enhancing efficiency, integrating variable renewables, lowering emissions, and enhancing system resilience is discussed.
Abstract
The global energy sector is in the process of making a dual transition towards decarbonization and digitalization. This paper discusses how the fundamental digital technologies, Internet of Things (IoT), Artificial Intelligence (AI), machine learning, digital twins, edge computing, and blockchain facilitate environmental objectives in the energy sector by enhancing efficiency, integrating variable renewables, lowering emissions, and enhancing system resilience. Studies are reviewed to evaluate five pillars of applications, (i) integration of renewable energy through high‑fidelity forecasting, smart inverters, and AI‑aided dispatch, (ii) smart grids that employ ubiquitous sensing, automation, and edge intelligence for real‑time stability, demand response, and losses reduction, (iii) end‑use energy efficiency in buildings and industry through data‑driven controls and digital twin-based optimization, (iv) predictive maintenance of generation and network assets via condition monitoring and fault‑prediction models to reduce downtime and resource waste, and (v) emissions tracking and carbon management through IoT‑enabled monitoring, AI analytics, and blockchain‑backed certificates and markets. Observed benefits encompass double digit gains in energy efficiency, increased renewable penetration without reliability loss, quantifiable decreases in curtailment and peaking demand, and enhanced transparency in carbon accounting. Constrains such as cybersecurity, data privacy, interoperability, worker skills, and the energy profile of digital infrastructure are assessed with mitigation techniques such as privacy-preserving analytics, standard adoption, edge processing, and low-energy consensus mechanisms. Looking ahead, development in AI, IoT, digital-twin grids, 5G/6G‑facilitated edge coordination, sector coupling, and trusted decentralized markets will bring increasingly autonomous, adaptive, and verifiably low-carbon energy systems. Digitalization thereby presents itself as a catalyst and control layer for realizing scalable, equitable, and resilient decarbonization.