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- Integrating Industrial Systems with Cloud-Based Platforms for Enhanced Connectivity and EfficiencyPublication . Imbó, Judá; Coelho, Paulo Jorge Simões; Ribeiro, Eliseu Manuel ArtilheiroThis dissertation investigates the integration of industrial automation systems with cloud based platforms by designing, implementing, and evaluating a practical Industrial Internet of Things (IIoT) architecture. The work addresses the limited availability of implementation oriented comparative studies of PLC-Edge-Cloud solutions by combining a PRISMA-based systematic review with a practical case study using Siemens S7-1500 PLCs, a Siemens SIMATIC IOT2050 gateway, Node-RED, and three cloud platforms: Siemens Insights Hub, AWS IoT SiteWise, and Microsoft Azure Digital Twins. The proposed architecture acquires industrial data via OPC UA, processes it at the edge, and transmits telemetry to cloud services via MQTT. The implementation demonstrates a reproducible gateway-centred approach for connecting industrial assets to cloud environments for monitoring, data modelling, and telemetry processing. The systematic review identifies the most common cloud platforms, protocols, architectures, benefits, and limitations reported in recent IIoT literature. The practical evaluation compares the selected platforms based on ease of use and implementation complexity, using observable criteria such as configuration steps, number of services, integration type, coding effort, dependencies, and conceptual difficulty. End-to-end latency was also analysed for the cloud based MQTT communication paths implemented with AWS IoT Core and Azure IoT Hub. The results show that Siemens Insights Hub offers the lowest implementation effort and the best ease of use, mainly due to its native integration mechanisms and reduced architectural complexity. AWS IoT SiteWise provides a balanced solution with moderate implementation effort. At the same time, Azure Digital Twins offers advanced modelling capabilities at the cost of higher configuration complexity, service dependency, and coding effort. In the latency comparison, AWS IoT Core achieved lower and more stable end-to-end latency than Azure IoT Hub under the tested conditions. Overall, this dissertation provides a replicable IIoT integration architecture and practical guidance for selecting cloud-based platforms in Industry 4.0 scenarios.