Wind turbines are the modern-day equivalent of windmills. Simply, it harnesses the wind's energy to create electricity. Although huge wind turbines are the most noticeable, smaller wind turbines for residential use are also available. For example, you may use it to power your caravan or boat. A large plot of land will be necessary. In addition, it endangers the habitat of wildlife, particularly bird species. It uses wind energy to produce energy, making it a renewable energy source. To overcome this issue a novel Integration of Monitoring and Security based Deep Learning Network for wind turbine system technique has been proposed. Denoising Wind Signal to Diagnose Faults in Turbines Using Deep Recurrent Neural Network, the fault can be analysed and classified by using the Optimised Classification Algorithm, Complete Condition Monitoring Elements Integration Model for Wind Turbine System, and Defence Methods for Securing Wind Turbine Records in Cloud-based Cryptography. In terms of accuracy, the proposed fault detection and fault isolation method (CSO-SVM) is 6.5% more accurate than SVM, particle swarm optimisation SVM (PSO-SVM), and K-Nearest Neighbours (KNN).