A Hexagonal Spatial Index And React Agent Architecture For Real-Time Broadband Service Qualification In Next-Generation Networks

Abstract

The commercial densification of fifth-generation millimeter-wave networks has rendered legacy static polygon broadband qualification systems inadequate for building-level, line-of-sight-aware serviceability decisions. This article reviews an AI-driven geospatial intelligence platform with three integrated components: an H3 hexagonal spatial index processing 20 terabytes per hour with 87% query reduction; a ReAct autonomous qualification agent achieving 99.9% accuracy at sub-200ms latency across 50 million annual requests, eliminating 580,000 false positive truck rolls and USD 87–174 million in annual waste; and a Text-to-SQL interface achieving 89.1% accuracy, reducing time-to-insight from 6.2 hours to 18 minutes. The platform generates predictive demand heatmaps informing capital expenditure exceeding ten billion dollars annually, expands serviceable locations by 1.45 million per year, and reduces CO₂ emissions by 1,624–2,436 metric tonnes annually.