Jul 2026· 2026 International Conference on Intelligent and Sustainable AI Systems (ICOSAAS)· pp. 227-232· 0 citations· 22 references
Abstract
Conventional energy meters measure only total consumption and give no information about harmonic distortion or load faults. This paper presents an edge intelligence power auditor on an STM32F411 ARM Cortex-M4 that performs real-time harmonic analysis and three-state fault classification with no cloud dependency. Voltage and current are acquired using a ZMPT101B sensor and SCT-013 clamp with LM358 conditioning, sampled at 5000 Hz through the 12-bit ADC. A 1024-point CMSIS-DSP FFT extracts harmonics up to the seventh order and computes THD, RMS voltage, RMS current, and power factor. A rule-based classifier using THD, power factor, and H3/H1 ratio identifies load conditions as Healthy, Degraded, or Faulty, with the 10% THD boundary aligned with IEEE 519. Hardware testing confirmed correct classification across all three states, with THD of 1.97% healthy and 39.84% faulty. Results are shown on an SSD1306 OLED, and a relay disconnects the load on fault detection. All processing runs on-chip with no external data transmission, making the system suitable for rural, off-grid, and small-industry use.
This research develops a single-phase AC electrical parameter monitoring system based on the Wemos D1 microcontroller, PZEM-004T sensor, and ThingSpeak Internet of Things platform. The system monitors voltage, current, active power, electrical energy, frequency, and power factor, and transmits measurement data through...
The transition to smart grids integrated with information and communication technology (ICTs) for the Special Protection Group (SPG) not only increases operational efficiency but also creates opportunities for advanced Cyber-Physical Attacks (CPAs). These threats are often stealthy, hard to detect with current securit...
A. Adejimi, Mesioye Ayobami Emmanuel, D. D. Wisdom et al.· UMYU Scientifica· 0 citations
Motors are crucial elements in the industry, where unexpected failures can interrupt production cycles, reduce profits, and raise safety concerns; and therefore an early anomaly detection in motor behavior is highly appreciated. As an extension of the known internet of things (IoT), industrial IoT or IIoT allows connec...
M. Zeidan, S. Aldalahmeh, Z. Haymoor et al.· IEEE Jordan Conference on Ap...· 0 citations
This paper presents a low-cost embedded monitoring system for real-time RMS voltage and RMS current acquisition in three-phase electrical networks. The proposed architecture is based on distributed Arduino Nano acquisition nodes equipped with ACS712 Hall-effect current sensors and isolated voltage transformers, while a...
George-Andrei Marin, M. Gaiceanu, A. Burlibasa et al.· Electricity· 0 citations
The work demonstrates the feasibility of an IoT-assisted APFC teaching prototype while also identifying the need for calibrated voltage sensing, zero-crossing/phase-angle measurement, and controlled meter-based experiments before industrial deployment.
Anurag Singh, Yatresh Mishra· World Journal of Advanced Re...· 0 citations
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