Early Detection of Onion Spoilage Utilizing IoT and AI during Storage and Transportation


Authors : Spurthi D.; Swathi P C.; S Chandan Yerra; Mutala Balaji; Deepika D Pai

Volume/Issue : Volume 9 - 2024, Issue 4 - April


Google Scholar : https://tinyurl.com/mu54x398

Scribd : https://tinyurl.com/9pw8rr82

DOI : https://doi.org/10.38124/ijisrt/IJISRT24APR2585

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : This paper introduces an innovative approach to reducing crop wastage by converting traditional onion warehouses into smart warehouses using IoT and AI technologies. We propose an IoT-based monitoring solution that continuously analyses and communicates the health status of onion stock in real time. Additionally, our methodology aims to support farmers by providing them with essential information about their onion stocks, enabling informed decision-making. Traditionally, farmers rely on sensory cues such as onion odor to detect decomposition. However, we propose a technological intervention utilizing image processing and AI-driven sensory mechanisms to enhance the onion detection process. Specifically, cameras are employed to identify sprouted onions, while AI algorithms analyze sensory data to detect rotten onions. Our prototype achieves an impressive 87% efficiency in identifying sprouted onions using camera-based systems. Furthermore, the response of the gas sensing system in detecting rotten onions under prescribed chamber dimensions yields encouraging results. Through the integration of IoT and AI, our methodology offers a promising solution to minimize crop wastage and promote sustainable agricultural practices.

Keywords : Internet of Things (IOT), Smart Warehouses, AI (Artificial Intelligence), Informed Decision-Making, Image Processing, Crop Wastage Reduction, Sprouted Onion Detection, Rotten Onion Detection, Gas Sensing System.

References :

  1. Syed Musthak Ahmed, Vinit Kumar Gunjan, Varsha Reddy, and Rahul Chandrahas. “Effective Monitoring of Onion Production Stored in Warehouse to Reduce the Commercial Commodity Wastage and Improve Reutilization” Springer Nature Switzerland, 15 July 2022, 343-352.
  2. Zahid Khan, Muhammad Zahid Khan, Sikandar Ali, Irshad Ahmed Abbasi, Haseeb Ur Rahman, Umar Zeb, Hizbullah Khattak, and Jiwei Huang, “Internet of Things-Based Smart Farming Monitoring System for Bolting Reduction in Onion Farms”, Volume 24 July 2021.
  3. Vinay S. Sidawadkar, Rohini Ahire, Shankaranand Lohare, Dipak Gavhale, Prachi P. Vast, “Internet of Things-Based Onion Preservation System”, All India Shivaji Memorial Society’s College of Engineering, Volume 12, Issue 2, 2020, ISSN:2454-5767.
  4. Farha. B. Shahanaz and AFM Jamal Uddin, “An overview of studies on summer onion production technology” ISSN:2309-7892 Volume 8 Issue 3, Page:25-27, July-December 2020.
  5. Malgorzata Labanska, Sarah van Amsterdam, Sascha Jenkins, John P. Clarkson and James A. Covington, “Preliminary Studies on Detection of Fusarium Basal Rot Infection in Onions and Shallots Using Electronic Nose”, 21 July 2022.
  6. Mokshi Vyas, Rutuja Gore, Manali Misal, Sneha Jagtap and Prof. S.V. Todkari. “Post Harvesting Onion Storage Methodology Using IOT”, International Journal of Advanced Research in Computer and Communication Engineering, Volume 8, Issue 5, May 2019.
  7. Popa A, Hnatiuc M, Paun M, Geman O, Hemanth D. J, Dorcea D, Son L.H, Ghita S “An Intelligent IOT-Based Food Quality Monitoring Approach Using Low-Cost Sensors” Symmetry 2019,11,374.
  8. Mr. S. A. Pawar, “Cost Effective Long-Time Preservation and Reporting of Onion Rotting and Onion Decay with Online Feedback”, International Journal of Advanced Research in Electrical and Electronics and Instrumentation Engineering Volume 6, Issue 1, January 2017.
  9. Selam Getachew Eriballo, Neela Satheesh, and Solomon Workneh Fanta, “Performance Evaluation of Low-cost Storage Structures for Onions” (Allium cepa L.) Storage in Bahir Dar, Amhara Region, Ethiopia.
  10. Siddayya, Narayanaswamy H, Suresh D Ekabote, Pradeep S, Nagarajapp Adivappar, “Survey for the post-harvest diseases of onion with special reference to black mold” in Chikkamagaluru, Chitradurga and Davanagere districts of Karnataka.
  11. Seid Hussen Muhie, “Preharvest production practices, and postharvest treatment and handling methods for best quality onion bulbs”.
  12. Mr. S. A. Pawar, “Cost Effective Long-Time Preservation and Reporting of Onion Rotting and Onion Decay with Online Feedback”. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 6, Issue 1, January 2017.

This paper introduces an innovative approach to reducing crop wastage by converting traditional onion warehouses into smart warehouses using IoT and AI technologies. We propose an IoT-based monitoring solution that continuously analyses and communicates the health status of onion stock in real time. Additionally, our methodology aims to support farmers by providing them with essential information about their onion stocks, enabling informed decision-making. Traditionally, farmers rely on sensory cues such as onion odor to detect decomposition. However, we propose a technological intervention utilizing image processing and AI-driven sensory mechanisms to enhance the onion detection process. Specifically, cameras are employed to identify sprouted onions, while AI algorithms analyze sensory data to detect rotten onions. Our prototype achieves an impressive 87% efficiency in identifying sprouted onions using camera-based systems. Furthermore, the response of the gas sensing system in detecting rotten onions under prescribed chamber dimensions yields encouraging results. Through the integration of IoT and AI, our methodology offers a promising solution to minimize crop wastage and promote sustainable agricultural practices.

Keywords : Internet of Things (IOT), Smart Warehouses, AI (Artificial Intelligence), Informed Decision-Making, Image Processing, Crop Wastage Reduction, Sprouted Onion Detection, Rotten Onion Detection, Gas Sensing System.

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