A Mobile-Integrated IoT Framework for Intelligent Warehousing: Design, Optimization, and Performance Analysis of Automated Logistics Control Systems

Abstract

The rapid evolution of Internet of Things (IoT) technologies has significantly transformed warehouse management systems, enabling intelligent, automated, and data-driven logistics operations. This research proposes a mobile-integrated IoT framework designed to enhance real-time monitoring, control, and optimization of warehouse logistics processes. The study integrates sensor-based data acquisition, mobile control interfaces, and intelligent decision-making mechanisms to improve inventory accuracy, operational efficiency, and environmental regulation within warehouse systems. Drawing upon established inventory management theories and modern IoT-based automation concepts, the framework emphasizes scalability, interoperability, and responsiveness.
A structured methodological design is developed for system architecture, communication protocols, and performance evaluation metrics. The proposed system is analyzed in terms of latency reduction, inventory tracking accuracy, energy efficiency, and operational reliability. Literature integration highlights the convergence of IoT-enabled microclimate control systems and mobile automation technologies in logistics environments. The findings suggest that mobile-integrated IoT systems significantly improve warehouse responsiveness and reduce human intervention in critical control operations. The study also identifies challenges related to network dependency, sensor reliability, and system scalability in large-scale deployments.
The research contributes a comprehensive architectural model and performance evaluation strategy for intelligent warehousing systems, offering practical implications for industrial automation and smart logistics ecosystems.