A Review of Real-Time Monitoring of Hybrid Energy Systems by Using Artificial Intelligence and IoT
Zuhaib Nishtar, Jamil Afzal
Abstract
This research focuses on the invention of real-time monitoring of hybrid energy systems using artificial intelligence (AI) and the Internet of Things (IoT). The study aims to develop a monitoring system that provides real-time insights, anomaly detection, fault diagnosis, and energy optimization. The research methodology involves the integration of AI algorithms and IoT devices to collect, analyze, and visualize system data. The results demonstrate the effectiveness of the developed monitoring system in improving system performance, sustainability, and cost savings. The practical implementation and scalability of the system are also addressed, along with future research opportunities. This research contributes to the advancement of monitoring systems for hybrid energy applications, promoting efficiency and sustainability in energy management. This research provides significant contributions to the field of real-time monitoring of hybrid energy systems. The article focuses on addressing key problems related to the real-time monitoring of hybrid energy systems using AI and IoT technologies. The lack of real-time insights provided by conventional methods also limits timely decision-making and responsiveness to dynamic changes in the system.