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1714527 Vol 9 · Issue 8 Download Paper

Smart Automated Onion Skin Peeling Machine Using Parallel Roller Mechanism

J. Karthikeyan R. Kishore V. Ajay S. Pradeep Kumar

Subject area: Science,Engineering and Technology  ·  Area of research: Embedded Systems and Power Electronics

DOI: https://doi.org/10.64388/IREV9I8-1714527

Abstract

The Smart Automated Onion Skin Peeling Machine is designed to reduce manual labor and improve peeling efficiency using a parallel roller mechanism driven by 12V DC geared motors. Onion presence is detected using an IR Proximity Sensor, while operating conditions are monitored using a DHT11 Temperature and Humidity Sensor to ensure stable performance. An HX711 Load Cell measures onion weight for batch control and uniform processing. Peeling completion and motor load variations are monitored using a Limit Switch and ACS712 Current Sensor, which help prevent over-peeling and mechanical damage. The system is controlled by an Arduino Uno / ESP32 microcontroller, programmed through the Arduino IDE. Operational data such as weight, motor current, and environmental parameters are transmitted to the cloud using Thing Speak for real-time monitoring and analysis. Python is used for data processing, automation logic, and performance evaluation. This system enhances peeling uniformity, improves safety, optimizes energy consumption, and provides a cost-effective smart solution for small- and medium-scale onion processing industries.

References

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How to cite this paper

J. Karthikeyan, R. Kishore, V. Ajay, S. Pradeep Kumar "Smart Automated Onion Skin Peeling Machine Using Parallel Roller Mechanism" Iconic Research And Engineering Journals Volume 9 Issue 8 2026 Page 1726-1732 https://doi.org/10.64388/IREV9I8-1714527
J. Karthikeyan, R. Kishore, V. Ajay, S. Pradeep Kumar "Smart Automated Onion Skin Peeling Machine Using Parallel Roller Mechanism" Iconic Research And Engineering Journals, vol. 9, no. 8, Feb. 2026, doi: https://doi.org/10.64388/IREV9I8-1714527
J. Karthikeyan, R. Kishore, V. Ajay, S. Pradeep Kumar (2026). Smart Automated Onion Skin Peeling Machine Using Parallel Roller Mechanism. Iconic Research And Engineering Journals, 9(8). doi: https://doi.org/10.64388/IREV9I8-1714527
J. Karthikeyan, R. Kishore, V. Ajay, S. Pradeep Kumar "Smart Automated Onion Skin Peeling Machine Using Parallel Roller Mechanism" Iconic Research And Engineering Journals, vol. 9, no. 8, Feb. 2026. Crossref, https://doi.org/10.64388/IREV9I8-1714527
@article{1714527,
      author = {J. Karthikeyan, R. Kishore, V. Ajay, S. Pradeep Kumar},
      title = {Smart Automated Onion Skin Peeling Machine Using Parallel Roller Mechanism},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {8},
      pages = {1726-1732},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1714527.pdf},
      abstract = {The Smart Automated Onion Skin Peeling Machine is designed to reduce manual labor and improve peeling efficiency using a parallel roller mechanism driven by 12V DC geared motors. Onion presence is detected using an IR Proximity Sensor, while operating conditions are monitored using a DHT11 Temperature and Humidity Sensor to ensure stable performance. An HX711 Load Cell measures onion weight for batch control and uniform processing. Peeling completion and motor load variations are monitored using a Limit Switch and ACS712 Current Sensor, which help prevent over-peeling and mechanical damage. The system is controlled by an Arduino Uno / ESP32 microcontroller, programmed through the Arduino IDE. Operational data such as weight, motor current, and environmental parameters are transmitted to the cloud using Thing Speak for real-time monitoring and analysis. Python is used for data processing, automation logic, and performance evaluation. This system enhances peeling uniformity, improves safety, optimizes energy consumption, and provides a cost-effective smart solution for small- and medium-scale onion processing industries.},
      month = {February},
      doi = {https://doi.org/10.64388/IREV9I8-1714527}
  }