On the Design of a Hybrid Framework for Resilient Indoor IoT Connectivity via Distributed 3-D Voronoi Deployment, Mobile Agents, and RIS-Assisted Communication

In indoor smart spaces, ensuring reliable IoT connectivity is a significant challenge. Walls, furniture, and other obstacles often create coverage gaps that disrupt wireless links. This work presents a system-level integration and validation study of a hybrid networking framework that combines static, mobility-enabled, and reconfigurable components to sustain connectivity in complex indoor environments. First, a 3-D Voronoi-based deployment of static IoT nodes provides an optimized baseline coverage map. Next, a set of mobility-enabled platforms, ceiling-rail robots and floor Automated Guided Vehicles (AGVs), form an adaptive layer that can reposition as needed to restore links or extend coverage around obstacles. In parallel, Reconfigurable Intelligent Surfaces (RIS) are strategically placed on walls or ceilings to dynamically redirect wireless signals, creating virtual line-of-sight paths and mitigating shadowing. A multi-objective Genetic Algorithm (GA) coordinates these elements, optimizing coverage, connectivity, and latency simultaneously. Across hospital, office, and warehouse layouts, the integrated system achieves on average 95.6% volumetric coverage and 100% connectivity. Latency and energy-efficiency results are reported together with 95% confidence intervals to highlight statistical robustness. The study quantifies the gains of a unified controller versus sequential or disjoint orchestration and provides sensitivity analyses under RIS quantization and shadowing effects. The contribution is therefore positioned as a practical, unified framework that couples planning, mobility, and RIS operation under non-ideal hardware and channel conditions.