Real-time energy-efficient framework for multi-source harvesting and adaptive communication IIoT networks

• Published in: Sustainable computing informatics and systems Vol. 47; p. 101150
• Main Authors: Sinha, Kumari Priyanka, Riyadh, Hosam Alden, Roopa, Y.Mohana, waris, Saiyed Faiayaz, Hamatta, Hatem S.A., Bhagyalakshmi, L., Alam, Shadab, Algahtani, Ali
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.09.2025
• Subjects: CoAP Optimization; Energy Harvesting; Energy-Aware Communication; Industrial IoT (IIoT); Lightweight Protocols; Multi-Source Energy Models; Protocol-Oriented Energy Scheduling; Resource-Constrained Networks; Smart Manufacturing; Sustainable Operations; Industrial IoT (IIoT); Smart Manufacturing; Energy-Aware Communication; Resource-Constrained Networks; Sustainable Operations; Protocol-Oriented Energy Scheduling; Lightweight Protocols; Energy Harvesting; Multi-Source Energy Models; CoAP Optimization
• ISSN: 2210-5379
• DOI: 10.1016/j.suscom.2025.101150

Over the past few years, Industrial Internet of Things (IIoT) devices have proliferated across modern manufacturing ecosystems, facilitatingreal-time monitoring, predictive analytics, and autonomous control. Nevertheless, maintaining these devices in low-resource contexts, especiallyin situations where the use of wired power is impossible and battery management is not feasible, is a significant challenge. Here, we introduce a new hybrid system that combines multi-source ambient energy harvesting (vibration, heat, and RF) with a lightweight adaptive communication protocol specifically designed for energy-limited industrial settings. Harnessing real-time energy buffer levels and environmental feedback, the architecture utilizes a central middleware engine to adapt transmission behaviors, routing decisions, and nodeactivity states. We design and test detailed models to measure the performance of the framework on major metrics such as energy usage, communication delay, packet delivery ratio, and network sustainability. We utilize a synthetic industrial case scenario with 45 IoT nodes out-deployed across three zones we show the framework's strong benefits over baseline and partial methods, reaching as high as 40 % improvement in node life, 28 % improvement in sustained throughput, and substantial improvements in node availability and energy fairness. This study provides a basisfor the installation of self-sustained, resilient IoT systems in realistic industrial environments, connecting the state of the art for energy autonomy design with the state of the art in the field of communication intelligence. •The integrated hybrid framework is proposed, capturing multi-environment energy harvesting and adaptive communication protocols in energy-constrained industrial IoT environments.•The real-time feedback based on energy buffer levels and environmental factors allows adaptation of transmission behaviors and node states dynamically.•Experimental results show a 40 % improvement in node lifespan and an increase of 28 % in sustained throughput.•Compared to baseline methods, the framework has shown better performance in terms of node availability, throughput, and energy fairness, proving its robustness in an industrial environment.