The development of intelligent transportation infrastructure is increasingly supported by the Internet of Things (IoT), offering opportunities to improve data-driven mobility management through real-time sensing and automation. This study aims to examine the conceptual foundations and practical implementations of IoT-based systems in the modernization of transport infrastructure, emphasizing architectural design, communication protocols, and deployment challenges. The methodology combines a literature-based synthesis with a simulation experiment using Node MCU ESP8266 microcontrollers, MQTT (Message Queuing Telemetry Transport) communication, Node-RED gateway integration, and cloud dashboard visualization. A total of 22 relevant scientific studies were reviewed, and six real-world case studies were evaluated to extract recurring design patterns and bottlenecks. Simulation results demonstrate that the proposed System maintains a low average transmission delay (128 ms) and minimal packet loss (0.83%) over 720 data cycles, indicating technical feasibility for small-to-medium scale deployments. The evaluation further identifies three critical factors affecting IoT transport systems: network reliability, cloud integration, and scalability. While MQTT over TLS and modular software frameworks enhance real-time performance and system resilience, network instability, particularly in rural or outdoor settings, remains a significant constraint. The study concludes that a scalable and sustainable IoT-based transportation infrastructure requires a context-aware, modular, and multi-layered architecture that is adapted to local operational conditions. The proposed framework provides practical guidance for developers, urban planners, and policymakers seeking to transition from conceptual models to real-world, innovative mobility applications.
Jaya Zairipan Jaya (Tue,) studied this question.
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