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  • An IoT and Machine Learning-Based Predictive Maintenance System for . . .
    This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring The system integrates Industrial IoT, MQTT messaging and machine learning algorithms
  • IoT in Predictive Maintenance: A Complete Overview
    What is IoT predictive maintenance? IoT predictive maintenance leverages the power of connected sensors and advanced analytics to revolutionize equipment upkeep By continuously monitoring machine health through vibration, temperature, pressure, and other sensors, IoT systems collect vast amounts of real-time data
  • Divyanshu-53 rtos-motor-health-monitoring-esp32-predictive-maintenance
    Real-Time IoT Motor Health Monitoring with FreeRTOS, MQTT, and Blynk Dashboard Production-ready predictive maintenance system for electric motors using ESP32 with concurrent real-time sensing, MQTT integration, and cloud alerts
  • Predictive Maintenance for Industrial Equipment (Motor) Using IoT
    This paper generally bring in a smart system that predicts when industrial motors need maintenance using machine learning Traditional maintenance methods, like waiting for something to disrupt or following a set schedule, can lead to unexpected downtime and higher repair costs This research explores a predictive approach that influences real-time data from vibration, current, and temperature
  • An IoT and Machine Learning-Based Predictive Maintenance System for . . .
    An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors Noor A Mohammed1 , Osamah F Abdulateef2 , Ali H Hamad2*
  • IoT-Enabled Real-Time Monitoring for Predictive Maintenance in DC Motors
    This project presents an IoT-based predictive maintenance system based on machine learning algorithms—Random Forest, Logistic Regression, SVM, and LSTM—to identify motor faults precisely Real-time data such as sound, vibration, and RPM are recorded through hardware prototyping, while Simulink simulates speed and torque Data is transmitted to Firebase for real-time monitoring, prompting
  • An Edge-AI and IoT Based Predictive Maintenance Device for Electric . . .
    Electric motors are indispensable in industrial operations, yet their reliability is often threatened by unplanned failures that lead to costly downtime Traditional maintenance strategies, such as reactive and preventive approaches, are either disruptive or resource-inefficient This paper introduces an AIdriven IoT device that leverages multi-modal sensor fusion and edge computing for
  • Remote motor condition monitoring using IoT and Machine Learning: A . . .
    A data-driven approach for predictive motor maintenance supports industrial automation The approach leverages the integration of Internet of Things and machine learning to create a scalable solution The system employs an array of sensors, including current, voltage, temperature, and humidity, connected to an ESP8266 microcontroller These sensors collect operational data, which is streamed
  • IoT-Driven Intelligent Motor Health Assessment and Predictive . . .
    The motivation behind this work is to design a low-cost, intelligent, and IoT-integrated predictive maintenance system that can continuously monitor motor health, detect abnormalities in real time, and predict failures before they occur using machine learning techniques
  • A COMPREHENSIVE FRAMEWORK FOR IOT-DRIVEN PREDICTIVE MAINTENANCE . . .
    The convergence of the Internet of Things (IoT), Artificial Intelligence (AI), and Edge Computing has advanced predictive maintenance (PdM) The main two benefits of this integration are to enable real-time monitoring and proactive equipment management across industries This paper presents a comprehensive framework for IoT-driven PdM, using AI-powered analytics and Edge Computing to enhance





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