Abstract: Power Quality Analyzers (PQA) are essential for monitoring and maintaining electrical networks. These assist in identifying changes in electrical measurements due to load fluctuations and other power quality factors. Traditional monitoring systems are mostly real-time, however they do not have automated alerts which would help in fault detection and corrective actions. The system is built on top of a Raspberry Pi Pico W microcontroller to which the voltage and current sensing modules, OLED display, and communication interfaces are connected. Wi-Fi gateway is used for passing the data obtained by different sensors. The transmitted and stored Data can be processed in further with an opensource cloud platform such as ThingSpeak to help monitor different aspects like IR status, temperature etc. SIM900A GSM module is used to alert the users in real-time as soon as any abnormal power event or voltage fluctuation occurred over the system in order to ensure higher reliability of the system. This ensures timely action and aids in avoiding the destruction of electrical devices.
Experimental Results: The proposed system performance is compared with conventional measuring apparatuses like FPGA-based Power Quality Analyzers and state-of-the-the art Fluke meters under different load conditions. The results collected indicate that the developed system enables correct measurements and monitoring.
The low-cost IoT design-based alternative proposed represents a simple method for managing the analysis and enhancement of power quality in home, business, and industrial electrical applications.
Keywords: Internet of Things (IoT), Raspberry Pi Pico W, Voltage and Current Sensors, GSM Alert System, Remote Data Monitoring, Cloud Platform (ThingSpeak)
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DOI:
10.17148/IARJSET.2026.133110
[1] M. Priyanka, M. Anusha, P. Poojitha, "Experimental Analysis Using IOT-Based Smart Power Quality Analyzer System With Remote Data Access And GSM Alerting Mechanism," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2026.133110