Intelligent System-Oriented Methodologies for LoRa Gateway Coverage Analysis in Urban Environments: A Technical Survey

Urban LoRaWAN deployments are engineering systems whose connectivity, energy use, reliability, and operating cost depend on informed gateway-placement and configuration decisions. Although LoRa is widely adopted for smart-city and industrial Internet of Things (IoT) applications, the methods used to construct gateway coverage analyses remain fragmented across propagation modeling, field measurement, simulation, optimization, and emerging data-driven approaches. This technical survey critically synthesizes the representative literature on methodologies for LoRa gateway coverage analysis in urban environments. Its contributions are threefold: it organizes the evidence around performance evaluation, configuration and optimization, localization, applications, communication technologies, security, and comparison with alternative LPWANs; it maps those methods onto a system-level workflow linking inputs, inference, decisions, and validation; and it identifies reporting and validation conditions needed for transferable engineering evidence. The cited literature prominently represents empirical measurements and simulation models, whereas integrated intelligent-system workflows that combine urban-context data, real-time measurements, predictive models, and decision support remain underdeveloped. Inconsistent environmental assumptions, incomplete reporting of validation settings, and nonuniform performance metrics limit transferability between cities. This survey therefore formulates a system-level design framework and research agenda centered on digital representations of the radio environment, hybrid physics- and data-driven models, adaptive configuration, and measurable validation of reliability, energy efficiency, and cost. These findings will support researchers and engineering practitioners in designing trustworthy, scalable, and adaptive IoT connectivity systems for urban environments.