Conference2025IEEE

AoI-Driven IoT Fault Detection for Smart Grids

Sajjad Baghaee, Muhammed Burak Aydar, Görkem Yıldırım, Keyvan Firuzi, Alper Acartürk, Elif Uysal, Ayça Hande Erkün Osunluk, Mustafa Çelikpençe, Faik Delibalta, Fatih Kaymak

2025 33rd Signal Processing and Communications Applications Conference (SIU)

Official publicationDOI

Abstract

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 microcontrollers 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.

Selected figures

Figure 1 from “AoI-Driven IoT Fault Detection for Smart Grids”: AoI-driven IoT fault detection device on a transformer
Fig. 1 · AoI-driven IoT fault detection device on a transformer.
Reproduced from: S. Baghaee et al., “AoI-Driven IoT Fault Detection for Smart Grids,” 2025 33rd Signal Processing and Communications Applications Conference (SIU), 2025. View the original publication.
Figure 3 from “AoI-Driven IoT Fault Detection for Smart Grids”: Distribution system simulation
Fig. 3 · Distribution system simulation.
Reproduced from: S. Baghaee et al., “AoI-Driven IoT Fault Detection for Smart Grids,” 2025 33rd Signal Processing and Communications Applications Conference (SIU), 2025. View the original publication.
Figure 6 from “AoI-Driven IoT Fault Detection for Smart Grids”: Three-phase current measurements over 2,000 samples with overall mean values
Fig. 6 · Three-phase current measurements over 2,000 samples with overall mean values.
Reproduced from: S. Baghaee et al., “AoI-Driven IoT Fault Detection for Smart Grids,” 2025 33rd Signal Processing and Communications Applications Conference (SIU), 2025. View the original publication.

Cite this work

Plain text

S. Baghaee, M. B. Aydar, G. Yıldırım, K. Firuzi, A. Acartürk, E. Uysal, A. H. E. Osunluk, M. Çelikpençe, F. Delibalta and F. Kaymak, "AoI-Driven IoT Fault Detection for Smart Grids," in 2025 33rd Signal Processing and Communications Applications Conference (SIU), pp. 1-4, 2025. doi: 10.1109/SIU66497.2025.11112068.

BibTeX 
@inproceedings{baghaee2025aoidriven,
  author    = {Baghaee, Sajjad and Aydar, Muhammed Burak and Yıldırım, Görkem and Firuzi, Keyvan and Acartürk, Alper and Uysal, Elif and Osunluk, Ayça Hande Erkün and Çelikpençe, Mustafa and Delibalta, Faik and Kaymak, Fatih},
  title     = {AoI-Driven IoT Fault Detection for Smart Grids},
  booktitle = {2025 33rd Signal Processing and Communications Applications Conference (SIU)},
  pages     = {1-4},
  publisher = {IEEE},
  year      = {2025},
  doi       = {10.1109/SIU66497.2025.11112068},
  url       = {https://ieeexplore.ieee.org/abstract/document/11112068}
}

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