IOT-BASED MACHINE CONDITION MONITORING SIMULATION USING ESP32

Authors

  • Adam Satria Politeknik STMI Jakarta
  • Al Kautsar Permana
  • Hikari Qurrata’ain Nurhadi
  • Archie Farras Belmino Tyto Putra

DOI:

https://doi.org/10.36761/hexagon.v6i1.5034

Keywords:

ESP32, Condition Monitoring, IoT, Connectivity, Embedded System, Thingspeak

Abstract

This research develops an IoT-based machine condition monitoring system capable of real-time monitoring of machine power consumption to enhance operational efficiency and predictive maintenance in industrial settings. The system utilizes the ACS712 current sensor to detect electrical current consumed by the machine. Using the Thingspeak platform, data collected from the sensor is periodically sent to a cloud server and displayed in a dashboard format, enabling remote monitoring. The monitoring program is designed to reduce the data load on the server, with data being transmitted every 10 seconds to minimize irrelevant data redundancy. In testing, the system successfully transmitted data to the Thingspeak server stably, despite occasional connectivity disruptions between the microcontroller and server. Over a total testing duration of one hour, 100 data samples were successfully uploaded, showing an average current of 2.8 Amperes and power of 550 Watts, with an operational voltage range of 220-235 Volts. The uploaded data is not only used for monitoring machine conditions but can also be further integrated into analysis to support better data-driven decision-making in industrial environments.

References

Aragón González, G., Barragán Santiago, I., Bautista Godínez, I., Becerra Martínez, P., Delgado Román, O., León Galicia, A., & Manrique Garay, J. (2022). Remote control and monitoring of a hydraulic machine. In Journal of Physics: Conference Series (Vol. 2307). Institute of Physics. https://doi.org/10.1088/1742-6596/2307/1/012009.

Anandh, R., & Indirani, G. (2018). Real Time Health Monitoring System Using Arduino with Cloud Technology. Asian Journal of Computer Science and Technology, 7(S1), 29–32. https://doi.org/10.51983/ajcst-2018.7.s1.1810

Mabrouki, J., Azrour, M., Dhiba, D., Farhaoui, Y., & Hajjaji, S. E. (2021). IoT-based data logger for weather monitoring using arduino-based wireless sensor networks with remote graphical application and alerts. Big Data Mining and Analytics, 4(1), 25–32. https://doi.org/10.26599/BDMA.2020.9020018.

Al-Naggar, Y. M., Jamil, N., Hassan, M. F., & Yusoff, A. R. (2021). Condition monitoring based on IoT for predictive maintenance of CNC machines. In Procedia CIRP (Vol. 102, pp. 314–318). Elsevier B.V. https://doi.org/10.1016/j.procir.2021.09.054

Carvalho, C. P. de, Simões, B. dos R., Carvalho, É. A. de, & Diniz, R. R. (2020). SENSING: An Approach to Establish the First Step to Prepare a CNC Machine for IoT Implementation. International Journal of Advanced Engineering Research and Science, 7(11), 71–79. https://doi.org/10.22161/ijaers.711.10

Abu Sneineh, A., & Shabaneh, A. A. A. (2023). Design of a smart hydroponics monitoring system using an ESP32 microcontroller and the Internet of Things. MethodsX, 11. https://doi.org/10.1016/j.mex.2023.102401

Budijono, S., & Felita. (2021). Smart Temperature Monitoring System Using ESP32 and DS18B20. In IOP Conference Series: Earth and Environmental Science (Vol. 794). IOP Publishing Ltd. https://doi.org/10.1088/1755-1315/794/1/012125

Pravalika, V., & Rajendra Prasad, C. (2019). Internet of things-based home monitoring and device control using Esp32. International Journal of Recent Technology and Engineering, 8(1 Special Issue 4), 58–62.

Julián, R. C. L., Oscar, D. F. C., & Jaramillo-Matta, A. A. (2023). PULSE OXIMETER IMPLEMENTED WITH ESP32 AND MONITORED IN BLYNK AND THINKSPEAK. ARPN Journal of Engineering and Applied Sciences, 18(14), 1692–16999. https://doi.org/10.59018/0723210

Sarker, S., Rakib, M. A., Islam, S., & Shafin, S. S. (2021). An IoT-based Smart Grid Technology: Bidirectional Power Flow, Smart Energy Metering, and Home Automation. In 2021 International Conference on Maintenance and Intelligent Asset Management, ICMIAM 2021. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICMIAM54662.2021.9715188

Published

2025-01-23

Issue

Vol. 6 No. 1 (2025): Vol. 6 No. 1 (2025): HEXAGON - Edition 10

Section

Articles

Copyright (c) 2025 Hexagon

Creative Commons License

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