A Smart Cloud-Integrated Power Quality and Environmental Monitoring System with Real-Time Fault Detection and GSM Alerts
LALAM ANURADHA*1, GOPU LIKHITHA2, KALAGANTI VEERANJANEYULU3, GANTLA SANDEEP NAIDU4, MUPOORI NAGENDRA5, DASARI NAGALAKSHMI6
1Student, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
2Student, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
3Student, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
4Student, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
5Assistant Professor, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
6Assistant Professor, Department of EEE, Bapatla Engineering College, Bapatla 522101, AP, India
Abstract — In the modern industrial setup, achieving optimal power quality becomes essential for effective operation, prolonging the life span of equipment, and ensuring the safety of workers. The traditional monitoring system is mostly reactive and lacks cloud integration and environmental hazard detection capabilities. In this study, an intelligent cloud-based power quality and environmental monitoring system is proposed. The system uses a PZEM-004T sensor for measuring the AC voltage, current, active power, energy, frequency, and power factor. Moreover, a DS18B20 digital thermometer is used to measure the temperature while an MQ-2 semiconductor sensor is utilized for detecting gases and smoke. All of the sensing operations are carried out by an Arduino UNO controller which then relays the data to the NodeMCU module for uploading on ThingSpeak IoT platform. The SIM800L GSM module gives instant alert messages for any faults, whereas the relay module automatically disconnects loads when thresholds are exceeded within 200 milliseconds. The I2C 16×2 LCD enables parameter readings locally. Experiments conducted during normal working conditions revealed that the input voltage is 236 V, load current is 0.42 A, effective power is 100 W, power factor is one, ambient temperature lies between 27 °C and 30 °C, and the gas index is 12.0 ppm equivalent. All the simulated fault conditions have been sensed and mitigated.
Key Words— Power Quality Monitoring, Internet of Things (IoT), Cloud Computing, PZEM-004T, NodeMCU ESP8266, GSM Communication, ThingSpeak, Fault Detection, Relay Protection, Predictive Maintenance, Industrial Automation
