# The Integration of Internet of Things and Machine Learning for Energy Prediction of Wind Turbines
## 2 IoT and Wind Energy
### Cyber-Physical Integration of a Wind Turbine  
Upon conducting a thorough analysis of the many components of WECS, it is evident that they can be classified as intricate technologies that incorporate embedded systems. The cooperation between WECS layers, as depicted in Figure 6 exhibits a significant degree of diversity and constitutes a characteristic cyber-physical system (CPS) [14]. Viewing WECS as CPS introduces additional levels of technology adaption and amplifies the capabilities of WECS to be seamlessly included in intelligent power grids and the IoE.  
The advancement of CPS necessitates the creation of novel models and design approaches. The primary objective of these new models and methodologies is to strike a harmonious equilibrium between intricacy and practicality. Integrating all diverse components of the cyber and physical levels to model wind turbine systems poses a significant challenge. Various elements of characteristics must be taken into account when creating CPS compositional models, including functional, non-functional, physical, component interfaces, and interface coordination. Thus, the intricate and diverse nature of components in contemporary wind turbines necessitates the application of similar concerns to be extended to WECS. It is necessary to use comprehensive analysis and verification methods to guarantee the precise operation of control systems for different electrical and mechanical components. Moreover, it is important to furnish comprehensive models of wind resources and electrical loads that influence the operational conditions. In the same context, it is imperative to establish a framework to guarantee the continuous viability, protection, defense, and adaptability of WECS [16].  
Verification techniques are necessary to assess the physical requirements, such as size, power, dynamics, and memory, of various computing and networking components used in wind turbines within the context of CPS. Additionally, there is a requirement for tools to verify the compatibility of various interfaces of SCADA, CMS, sensor nodes, and power electronics with control circuits [5]. Future WECS necessitate the implementation of unified techniques to enhance their extensibility, facilitate interaction with smart grids, and improve human-machine interfaces [12]. WECS models are expected to incorporate both continuous physical dynamics and discrete occurrences. There needs to be a consistent understanding of time across sensor nodes, networks, and computing platforms. In addi  
Figure 5: Communication architecture for a wind turbine equipped with multiple sensors.  
tion, contemporary wind turbine technology incorporates computing systems that operate at varying speeds [17]. SCADA systems in wind facilities function at a low frequency to record performance data, whereas CMS operates at a high frequency to monitor components effectively. Moreover, it is imperative to depict the tangible movements of mechanical structures, the study of airflow around objects, the behavior of electrical parts, and the control of electrical power using descriptive programming abstractions. Therefore, it is becoming more and more necessary to combine conceptual computational and information flow models from sensor networks with physical-mechanical and electrical models in wind turbines. Alternatively, black box approaches can be used, relying on system identification using real data obtained from wind facilities.