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

This paper proposes an energy-efficient Internet of Things (IoT) and edge computing framework tailored for decentralized infrastructure management in underserved U.S. municipalities. The system integrates virtual MIMO-based wireless sensor networks, edge AI inference modules, and nanomaterial-enhanced photovoltaic systems to autonomously monitor and control public utilities such as waste, water, and energy. By deploying a low-power, AI-integrated infrastructure compatible with municipal use cases, the framework reduces dependency on centralized grids, enables intelligent decision-making at the edge, and promotes inclusive innovation for rural communities. Experimental results from a prototype deployment show reduced energy consumption by 28% compared to conventional sensor networks, and increased system autonomy with sub-second decision latency. The proposed architecture supports U.S. policy priorities under the NSF Smart & Connected Communities initiative and the Department of Energy’s energy equity frameworks.