### Industry 4.0 IIoT, Cloud, and Edge Computing for Next-Generation Offshore Wind Farms  
IIoT devices, mounted on wind turbines within the wind farm, communicate with each other to exchange environmental data and coordinate actions in the wind farm to prevent damage or accidents. The interaction between wind turbines and remote control centers is crucial for efficient operation and management. Key activities in this interaction are (i) the transmission and reception of alarms, (ii) the initiation of service requests, (iii) the adjustment of control parameters, and (iv) the collection of turbine status and performance data [31]. The implementation of these IIoT devices for monitoring and maintenance significantly enhances these processes and leads to several benefits for wind farm operators, including the prevention of extended downtime, the reduction in operation and maintenance (O&M) costs through the early identification of faults, and the enhancement of real-time decision-making capabilities [32]. These improvements not only provide direct financial benefits but also contribute to indirect economic advantages. To quantify these benefits, [PERSON] et al. [33] developed a maintenance cost model that showedup to 75% reduction in annual maintenance costs and downtime ratio in wind power equipment's IIoT-enabled offshore wind farms. An IIoT system comprises IIoT devices, a communication network, and cloud storage servers (with advanced computation capabilities). Figure 2 illustrates the seven-layer IoT World Forum Reference Model adapted from [34], which illustrates all the layers of an IIoT system. The reference model layers are grouped into the Data-in-Motion (DIM) module, which comprises Layer 1 to Layer 3, and the Data-at-Rest (DAR) module, which comprises Layer 5 to Layer 7. For an offshore wind farm application scenario, the DIM module comprises real-time, operational technology (OT), and event-based functions of the offshore wind farm. Here, the functions and flow of data are based on the events of the application domain. The DAR module consists of non-real-time business applications implemented as software. Further, the module's end users or applications run queries on the data to capture only data relevant to their particular interests (predictive analytics, forecasting, trends, and visualization). The IoT World Forum reference model layers are described as two modules DIM and DAR:  
**Data-in-Motion (DIM) Module:** The Data-in-Motion module comprises layer 1 to layer 3. Layer 1 (Physical Devices and Controllers): Vibration, environmental, and operational IIoT devices are mounted to monitor critical components in an offshore wind farm [35]. Considering their application environment, these IIoT devices are ruggedized to withstand harsh environmental conditions such as extreme temperatures, humidity, vibrations, and exposure to dust and chemicals. They are periodically recalibrated to provide precise and reliable data consistently over time. Layer 2 (Connectivity): The IIoT devices send the digitized measurements through communication and processing units to the edge computing platform [36]. Several wired and wireless technologies are deployed in this layer to facilitate latency-sensitive data transfer within short and long ranges. The communication technologies adopted at this layer are either wired (such as fiber optic cable, ethernet copper cable, and coaxial cable) or wireless (such as NB-IoT, Wi-Fi, LoRA, LTE, WiMax, Bluetooth, SigFox, NFC) solutions [37]. Layer 3 (Edge Computing): The measurements are received at the edge computing layer, which provides advanced computing and memory resources similar to those offered by a cloud but closer to the physical devices and controllers in layer 1 [38]. **Layer 4 (Data Accumulation):** The layer stores and manages the big data obtained from the physical devices and controllers in Layer 1.