AoI-Driven IoT Fault Detection for Smart Grids

Date

2025-01-01

Author

Baghaee, Sajjad
Aydar, Muhammed Burak
Yildirim, Gorkem
Firuzi, Keyvan
Acarturk, Alper
Uysal, Elif
Erkun Osunluk, Ayca Hande
Celikpence, Mustafa
Delibalta, Faik
Kaymak, Fatih

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Ensuring the reliability and efficiency of electric distribution grids necessitates real-time fault detection systems that prioritize data freshness and transmission efficiency. This paper presents the first Age of Information (AoI)-driven IoT fault detection system, powered by an AoI-optimized algorithm that dynamically adjusts transmission intervals to ensure timely and critical updates. By integrating ESP32 and STM32 micro-controllers with an MQTT-based communication framework, the system adapts to network conditions, mitigating congestion while improving data precision. As a pilot project, the system was deployed across five transformer stations on a live power grid, where it successfully detected 27 fault types with high accuracy. Experimental results show timely fault detection with minimal data use - 17 KB/year in fault mode and 55 MB/year in continuous mode - enabling long-term, battery-powered operation.

Subject Keywords

Age of Information (AoI), IoT Fault Detection, Real-Time Monitoring, Semantic Communication, Smart Grids

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105015386210&origin=inward
https://hdl.handle.net/11511/115776

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Department of Electrical and Electronics Engineering, Conference / Seminar