International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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IOT Based Smart Machine Monitoring System

Author(s) Sarang Dattaji Devkule, Swaraj Krishna Khutale, Sainath Balaso Kumbhar, Satej Sadashiv Desai, Prof. S. V. Sagavkar, Dr. D. J. Pawar
Country India
Abstract Industrial machinery constitutes the operational backbone of modern manufacturing and production facilities. Ensuring its uninterrupted performance is paramount, yet traditional inspection-based monitoring is inadequate for the speed and complexity of contemporary industrial environments. This paper presents an Internet of Things (IoT)-enabled Smart Machine Monitoring System that leverages a Raspberry Pi 4 as the central processing unit, integrated with an ACS712 current sensor, an LM35 temperature sensor, and an SW-420 vibration sensor to enable continuous, real-time acquisition of critical machine health parameters. Sensor data is processed on-device, compared against configurable safety thresholds, and relayed automatically to the ThingSpeak cloud platform for remote visualization and historical analysis. When any monitored parameter exceeds a prescribed limit, the system activates a relay module to isolate the machine from its power supply, simultaneously dispatching operator alerts through GSM-based SMS messaging and IoT dashboards. Experimental validation demonstrates stable current monitoring within a 0.2 A–1.3 A range, temperature tracking from 28°C to 43°C, and effective detection of vibration anomalies up to six units above baseline. The proposed architecture delivers a cost-effective, scalable, and Industry 4.0-compliant solution capable of substantially reducing unplanned downtime and supporting predictive maintenance strategies in small-to-large industrial deployments.
Keywords Internet of Things (IoT); machine monitoring; Raspberry Pi; ACS712; LM35; SW-420; ThingSpeak; predictive maintenance; Industry 4.0; fault detection.
Field Engineering
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-06-08
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E-ISSN 2582-2160
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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