Energy-Aware IoT and Edge Computing for Decentralized Smart Infrastructure in Underserved U.S. Communities

This work presents a novel energy-aware Internet of Things (IoT) and edge computing framework specifically designed to support decentralized infrastructure management in underserved U.S. communities. The proposed system integrates virtual MIMO-based wireless sensor networks, federated edge AI inference models, and nanomaterial-enhanced solar energy harvesting to autonomously monitor and control public utility operations—including waste, water, and energy. The architecture enables real-time decision-making at the edge, minimizing reliance on cloud connectivity and improving system resilience and sustainability. Through prototype deployment and experimental validation, the system demonstrates a 28% reduction in energy usage and sub-second response latency, with 97.5% uptime in off-grid operation. This research directly supports national goals under the NSF Smart and Connected Communities initiative and the U.S. Department of Energy’s energy equity frameworks. It contributes to the advancement of intelligent infrastructure in rural America and offers a scalable, low-cost solution for municipalities seeking to modernize essential services through secure, efficient, and autonomous technologies. The publication includes system architecture diagrams, performance benchmarking data, and insights into real-world deployment challenges in low-resource settings.