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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM40710

Online Inspection of Packed Cases

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM40710

Volume:

9 |

1 |

Jan 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM40710

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

DSER

D Sai Eswara Reddy

KD

K Dinesh

DNR

D Niranjan Reddy

NPK

N Pavan Kumar

BHR

B Harinath Reddy

SGMA

Sukruth Gowda M A

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Abstract

This paper presents a novel approach to automate the inspection process of packed agricultural cases using Artificial Intelligence (AI) and image processing techniques. The current manual inspection system, which assesses only 10% of packed cases based on subjective expert judgment, faces limitations such as inefficiency, subjectivity, and an inability to scale. The proposed solution leverages AI models and advanced image processing algorithms to perform real-time, automated inspections of packed cases. The system assesses quality based on predefined parameters like color, ripeness, and uniformity, as per customer specifications. This approach offers numerous benefits, including increased accuracy, scalability, cost reduction, and enhanced customer satisfaction.

KEYWORDS

Artificial Intelligence (AI) Image Processing Online Inspection Quality Control Automation Agricultural Products Real-Time Feedback Machine Learning Objectivity in Inspection Automated Quality Assessment Case Inspection.

Cite This Article

D Sai Eswara Reddy, K Dinesh, D Niranjan Reddy, N Pavan Kumar, B Harinath Reddy, Sukruth Gowda M A, "Online Inspection of Packed Cases," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 1, Jan 2025. https://doi.org/10.55041/IJSREM40710

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Publication Date

11/30/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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