This proposed presents an IoT-based single-phase transmission line fault detection system that enables real- time monitoring and automated fault diagnosis.The proposed system consists of an ESP32 microcontroller, current and voltage sensors, and a cloud-based platform for remote data access. The sensors continuously measure electrical parameters, and the ESP32 processes this data to identify abnormalities. When a fault is detected, the system sends real-time alerts to a Firebase database or an IoT dashboard, allowing utility operators to take immediate corrective action. Additionally, a web or mobile application provides remote access to fault data, improving response efficiency. This IoT-driven approach enhances the reliability of power distribution networks by enabling early fault detection, remote monitoring, and reduced downtime. The system is scalable, cost-effective, and energy-efficient, making it a viable solution for modernizing fault detection in single-phase power systems.
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He is currently working as Assistant Professor in the Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore. His area of specialization is Energy Management System, Intelligent Controllers in Renewable Energy Systems and Smart Grid.
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Paperback. Zustand: new. Paperback. This proposed presents an IoT-based single-phase transmission line fault detection system that enables real- time monitoring and automated fault diagnosis.The proposed system consists of an ESP32 microcontroller, current and voltage sensors, and a cloud-based platform for remote data access. The sensors continuously measure electrical parameters, and the ESP32 processes this data to identify abnormalities. When a fault is detected, the system sends real-time alerts to a Firebase database or an IoT dashboard, allowing utility operators to take immediate corrective action. Additionally, a web or mobile application provides remote access to fault data, improving response efficiency. This IoT-driven approach enhances the reliability of power distribution networks by enabling early fault detection, remote monitoring, and reduced downtime. The system is scalable, cost-effective, and energy-efficient, making it a viable solution for modernizing fault detection in single-phase power systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786209384400
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This proposed presents an IoT-based single-phase transmission line fault detection system that enables real- time monitoring and automated fault diagnosis.The proposed system consists of an ESP32 microcontroller, current and voltage sensors, and a cloud-based platform for remote data access. The sensors continuously measure electrical parameters, and the ESP32 processes this data to identify abnormalities. When a fault is detected, the system sends real-time alerts to a Firebase database or an IoT dashboard, allowing utility operators to take immediate corrective action. Additionally, a web or mobile application provides remote access to fault data, improving response efficiency. This IoT-driven approach enhances the reliability of power distribution networks by enabling early fault detection, remote monitoring, and reduced downtime. The system is scalable, cost-effective, and energy-efficient, making it a viable solution for modernizing fault detection in single-phase power systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. Bestandsnummer des Verkäufers 9786209384400
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Taschenbuch. Zustand: Neu. Transmission Line Fault Detection Using Iot | Loganathan N (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209384400 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 134442911
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