Аңдатпа
The digitization of brownfield manufacturing environments, particularly within Small and Medium-sized Enterprises (SMEs), is fundamentally constrained by the lack of robust, scalable, and cost-effective communication infrastructure capable of retrofitting legacy equipment. While Industry 4.0 applications demand reliable, low-latency data acquisition, existing solutions often fail to balance cost-effectiveness with the performance demands of industrial settings. This paper introduces the design, optimization, and empirical evaluation of a highly cost-effective Industrial Internet of Things (IIoT) communication framework tailored for challenging industrial environments. Utilizing a conventional hierarchical edge-to-cloud architecture, this study leverages existing Wi-Fi infrastructure and the MQTT protocol to enable decentralized, parallel data acquisition while optimizing localized sensor density through aggregator nodes. The hardware design utilizes custom ESP32-based nodes, achieving a unit cost of approximately $74.00. Rather than proposing a fundamentally novel topology, the core scientific contribution of this work is the provision of an applied deployment blueprint and the extraction of transferable analytical insights for accessible MQTT/Wi-Fi deployment. Performance was quantified through a facility-level pilot deployment of 19 nodes in an operational industrial bakery characterized by significant electromagnetic interference and physical obstructions. The results demonstrate stable operation, achieving a system uptime of 99.92% over a 30-day period. Network performance metrics confirm the framework’s suitability for high-fidelity monitoring, recording an average end-to-end latency of 185 ms and a low jitter of 86 ms. Furthermore, the scalability of the proposed architecture was explored through Discrete-Event Simulation (DES), suggesting acceptable monitoring performance for approximately 200 concurrent nodes under stated assumptions. Security trade-offs were theoretically analyzed, justifying a defense-in-depth strategy that prioritizes system availability and latency budgets over device-level encryption in resource-constrained environments. This study provides an applied deployment blueprint for establishing the foundational communication layer required for localized Industry 4.0 applications in brownfield settings.