### State of the Art  
Recent years have seen extensive research into real-time Supervisory Control and Data Acquisition (SCADA) solutions for pilot plants in general [13], and SWTs under 100 kW in particular, especially when integrated into hybrid microgrids. Many groups have demonstrated low-cost, open-hardware platforms for remote monitoring and control of SWTs. For example, [PERSON] et al. [14] developed a multi-channel data acquisition system using Arduino(r) microcontrollers to capture the turbine's performance with high speed and fidelity. Open-source controllers--such as Arduino(r) (Arduino SA, Lugano, Switzerland), Raspberry Pi(r) (Raspberry Pi Foundation, Cambridge, UK), and ESP8266-based nodes (Espressif Systems, Shanghai, China)--are widely used in small wind installations to interface with sensors (e.g., wind speed, voltage, current, vibration) and actuators (e.g., pitch control, braking systems). [PERSON] [15] retrofitted a wind-solar-diesel-battery microgrid with a Raspberry Pi(r)-based Internet of Thing (IoT) gateway that continuously logs wind turbine data and publishes it to a cloud dashboard. Similarly, [PERSON] et al. [16] developed a vertical-axis wind turbine monitoring system using an Arduino(r) with a web-based digital dashboard, enabling real-time monitoring of power output and generator conditions over the internet. These open platforms [17] offer significantly lower implementation costs while providing the flexibility to integrate custom control algorithms and communication protocols. To enable remote, real-time operation, researchers have adopted lightweight IoT communication protocols [18]. MQTT (Message Queuing Telemetry Transport) has been used to collect and transmit sensor data from SWTs to remote servers with minimal bandwidth usage. [PERSON] et al. [19] implemented an MQTT-based fault monitoring system on an Arduino(r) Uno for a small turbine, achieving prompt cloud-based detection of anomalies. Recent contributions have also explored advanced time-frequency learning architectures for condition monitoring under time-varying speeds, such as Time-Frequency Self-Similarity Enhancement Network (TFSSEN) [20] and CTNet [21], reinforcing the role of data-driven Condition Monitoring Systems in SWT fault diagnosis. Other works employ modern web standards. [PERSON] et al. [22] present an open-source digital twin platform for wind turbines that uses an HTTP/WebSocket API to enable full-duplex, millisecond-level data exchange and control--illustrating the potential of WebSocket technology for interactive turbine management. These internet-enabled systems allow operators to supervise turbine status and send control commands (e.g., start/stop or set-points) remotely in real time. Notably, [PERSON] et al. [23] report an IoT-based supervisory system for a doubly-fed induction generator (DFIG) wind turbine, in which real-time measurements are sent to an online controller that dynamically adjusts settings to ride through grid voltage dips. This underscores that, beyond monitoring, remote IoT frameworks are now closing the loop by actively controlling SWT operations to enhance stability and performance. Another research area is the integration of SWTs into hybrid microgrids alongside solar PV, battery banks, and even hydrogen storage [24; 25]. These microgrids require coordinated control of multiple sources, often achieved through distributed controllers networked via IoT [26]. Open-source hardware has also demonstrated its capabilities in this context: [PERSON] et al. [27] combined an industrial power analyzer with Arduino(r)-based sensor nodes to monitor a laboratory microgrid (including a 3-kW wind turbine) in real time. In [PERSON] et al. 's [28] experimental microgrid, a SWT and PV array are co-managed by an IoT monitoring program, which balances power flows to a battery and a hydrogen electrolyte. Advanced energy management strategies are implemented on these platforms to maximize renewable utilization--[PERSON] et al.