Machine-Learning-Based Classification of Electronic Devices Using an IoT Smart Meter
This study investigates the implementation of artificial intelligence (AI) algorithms on resource-constrained edge devices, such as ESP32 and Raspberry Pi, within the context of smart grid (SG) applications. Specifically, it proposes a smart-meter-based system capable of classifying and detecting th...
Saved in:
| Main Authors: | Paulo Eugênio da Costa Filho, Leonardo Augusto de Aquino Marques, Israel da S. Felix de Lima, Ewerton Leandro de Sousa, Márcio Eduardo Kreutz, Augusto V. Neto, Eduardo Nogueira Cunha, Dario Vieira |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Informatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9709/12/2/48 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Set of Tools and Data Management Framework for the IoT–Edge–Cloud Continuum
by: Janis Judvaitis, et al.
Published: (2024-12-01) -
New developing narrow band IoT technology NB-IoT
by: Zhi-bin ZHENG, et al.
Published: (2017-12-01) -
FedSensor: Federated Learning Framework for Secure Sensor-Based IoT at the Extreme Edge
by: Norisvaldo Ferraz Junior, et al.
Published: (2025-01-01) -
Enhancing DevOps Practices in the IoT–Edge–Cloud Continuum: Architecture, Integration, and Software Orchestration Demonstrated in the COGNIFOG Framework
by: Kostas Petrakis, et al.
Published: (2025-04-01) -
An Intelligent IoT and ML-Based Water Leakage Detection System
by: Mohammed Rezwanul Islam, et al.
Published: (2023-01-01)