Jun 2026· International Journal for Research in Applied Science and Engineering Technology· Vol 14, pp. 3412-3419· 0 citations
TL;DR
The suggested innovation refers to a smart embedded system to monitor the operational state of an induction motor and analyze fault levels in real time and provides local monitoring along with IoT-based remote transmission.
Abstract
The significance of induction motors lies in their robustness, simplicity of design, durability, and minimum
maintenance, which makes them essential components in industry. Nevertheless, constant exposure to electrical, thermal, and
mechanical stresses results in problems like overheating, winding deterioration, bearing damage, rotor imbalance, and
vibrations. Without timely identification of these issues, they lead to breakdowns, delays, and additional expenses. The suggested
innovation refers to a smart embedded system to monitor the operational state of an induction motor and analyze fault levels in
real time. It measures the parameters of temperature, currents, and vibrations that reflect motor conditions. These measurements
are carried out with sensors and analyzed by means of a microcontroller through comparison with predefined thresholds,
resulting in fault recognition and classification. Existing systems lack remote monitoring and instant alerts. To address these
gaps, the proposed system provides local monitoring along with IoT-based remote transmission. A buzzer/LED alert mechanism
ensures immediate notification during critical conditions.
Three-phase induction motors are extensively utilized in industrial and commercial applications due to their robustness, efficiency, and capability to handle high-power loads. However, these motors are vulnerable to damage from phase failure conditions, including single-phasing, voltage imbalance, and phase loss, which can lead to overheating, reduced efficiency, and permanent equipment failure. This paper presents the design and development of a low-cost, intelligent three-phase monitoring and protection system integrated with Internet of Things (IoT) communication for real-time fault notification. The proposed system employs an Arduino Uno microcontroller as the central processing unit, continuously monitoring the availability of R, Y, and B phases through voltage sensor modules. Upon detection of any phase failure, the system automatically disconnects relay-controlled loads to prevent single-phasing damage. Local status indication is provided through an I2C LCD display and audible buzzer alerts, while remote monitoring is achieved via an ESP32 DevKit module that transmits fault notifications to a Telegram application through Wi-Fi connectivity. The system architecture combines embedded control, automated protection, and wireless communication into a single scalable platform. Experimental validation demonstrates reliable phase detection, rapid relay response, and effective remote alerting, confirming the system's suitability for industrial automation, motor protection, and smart energy management applications.
J. Babu, More Divya, Varu Chirag et al.· International Journal for Sc...· 0 citations
This research presents an internet of things (IoT-based) system for real-time monitoring and control of a three-phase induction motor that enables continuous monitoring, early fault detection, and predictive maintenance, thereby improving overall operational efficiency and reducing downtime.
Y. S. Pawar, Sandip Rahane, A. Thakare et al.· Bulletin of Electrical Engin...· 0 citations
The study investigates real-time problem diagnosis of induction motors (IMs) with digital signal processing (DSP) to improve monitoring. IMs are essential to industrial applications but can fail owing to mechanical, electrical, and thermal stressors. These defects must be detected quickly to prevent motor failure and production downtime. DSP is used to create a sophisticated real-time online condition monitoring system to diagnose three-phase IM issues. The suggested system was validated using MATLAB calculations and experimental investigations on a 415 V, 1 HP, 50 Hz, 1440 rpm, 4-pole IM. Disruptions in the stator windings, such as inter-turn short circuits or inter-phase faults, as well as problems with the rotor, such as broken bars or end rings, are identified in this investigation. Keeping an eye on negative sequence currents and analyzing fault frequencies with a fast Fourier transform (FFT). According to the results of the testing, current approaches are not very good at detecting stator inter-turn difficulties under light-load and no-load conditions. Under varying loads, the proposed DSP-based system identified stator inter-turn, inter-phase, and broken rotor bar problems. Results showed that the DSP-based online condition monitoring system was more accurate and better at detecting faults than earlier methods, making it a good fit for usage in industrial applications.
Mohan P. Thakre, Badal Kumar, Supriya Nilesh Thakur et al.· Bulletin of Electrical Engin...· 0 citations
The reliability of electrical systems plays a crucial role in ensuring the continuous operation of equipment and preventing potential damage and fires caused by electrical faults. This study aims to design and implement a web-based electrical fault monitoring and warning system using the Internet of Things (IoT) concept. The system was developed using an ESP32 microcontroller integrated with a PZEM-004T sensor, a DHT22 sensor, and an MQ-2 sensor. The measurement data is processed in real time, stored on an SD card and in a local database, and then displayed via a web interface in numerical and graphical formats. Test results showed an average error of 0.52% for voltage and 0.92% for current in the PZEM-004T sensor; calibration of the DHT22 yielded a correction of 0.074°C; and the MQ-2 sensor set the smoke detection threshold at 40 PPM. The system successfully detected abnormal voltage conditions, overcurrent or undercurrent, high temperatures, and the presence of smoke, and automatically activated the relay to cut off the power supply. The designed system successfully improved installation safety and reduced the risk of equipment damage and fire. .
Unknown authors· Internet of Things and Artif...· 0 citations
Haiwell Cloud SCADA-based monitoring system to analyze the behavior of induction motors in real-time voltage, current, speed, frequency, and temperature, and a tension control method using a magnetic powder brake to simulate changes in the load dynamically is offered.
The Sudden equipment failures are common in industrial systems, which means more downtime and higher maintenance costs. A Smart AI-Integrated Predictive Maintenance and Condition Monitoring System is proposed to solve this problem. It will allow for real-time monitoring and early fault detection in industrial machines. The system uses an Arduino Uno (ATmega328P) microcontroller that is connected to several sensors, such as voltage, current, temperature (LM35), vibration, proximity, and MPU6050 sensors, to collect important operational data. The ESP8266 NodeMCU Wi-Fi module sends the processed data to an IoT cloud platform so that it can be monitored and analyzed from afar. There is also an I2C display developed in for real-time viewing on position. The proposed system uses AI-based analysis to find problems and assume when equipment might break down, which enables maintenance be performed on time. By using a hardware prototype to evaluate shows that the system reliably monitor in real time and make accurate predictions, which cuts down on downtime and makes the system work better. The Integration of AI and IoT technologies makes predictive maintenance in modern industrial settings cheaper, more flexible, and smarter.
V. R. Kumar, P. Poornima, M. Abinesh et al.· International Conference on...· 0 citations