Design and Deployment of Smart Sensor Networks for Real-Time Industrial Automation

Abstract

The increasing need of the industry 4.0 to have intelligent and responsive control systems has led to the creation of Smart Sensor Networks (SSNs) that have the capacity of decentralized sensing, edge analytics and adaptive communication. In this paper the modular SSN framework, targeted to real-time industrial automation, is presented. The solution to overcome the heterogeneity of the time-sensitive sensors, edge nodes, and a cloud-based supervisory control layer is the architecture based on time-sensitive communication protocols, including Time-Sensitive Networking (TSN) and MQTT-SN. Fault tolerance and latency minimization hybrid networking approach to networking combining both wired (Modbus-TCP) and wireless (IEEE 802.15.4 and Wi-Fi 6) links can be achieved under dynamic industrial circumstances. Some design decisions covered are time determinism, energy efficiency, scalability, and protocol interoperability. The framework uses edge-fog computing paradigms, real-time scheduling algorithms, and multi-tier fault diagnostic mechanism to ensure responsiveness and reliability of the systems. Results of an experimental assessment made on a simulated smart manufacturing floor, which included robotic arms and conveyor systems, showed 38 percent reduction in average system response latency and 25 percent increase in isolation accuracy of faults compared with traditional SCADA systems. These findings highlight the potential of the framework in the domain of optimizing predictive maintenance in smart industrial environments, improving robotic coordination, and providing assistance in terms of process optimization. This effort opens a plausible roadmap to eventual fully decentralized, resilient, and scalable automation infrastructures to support next-generation industrial systems.