A review of object detection technology in industrial sector: Methods and applications

Object detection technology contributes to increasing operational efficiency, including in the industrial sector. Several object detection methods have been developed by researchers, such as classification/regression-based or region-based models. This study has reviewed the object detection technology related to the methods and applications implemented in the industrial sector. The analysis method and review carried out refer to the systematic literature review (SLR) through several stages: (1) article searching strategy using the three keywords; (2) article selection results; (3) article analysis and review; and (4) documentation and conclusion. Data sources were taken from two major repositories, including Scopus and IEEExplore for the years 2023 to 2025. In the aspect of method, the YOLO model is a common method that is used in industrial sectors regarding its fast detection and efficiency, while in the aspect of object detection application is commonly implemented in robotic arms to control objects or things’ position and monitor the conveyor motor. Object detection methods continue to experience development and adaptation in various sectors, making it an interesting topic to be discussed in the paper review.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-20
DOI
https://doi.org/10.1051/e3sconf/202566401001/pdf
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
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article

A review of object detection technology in industrial sector: Methods and applications

Springer Link (Chiba Institute of Technology)
Advanced Neural Network Applications
article

A review of object detection technology in industrial sector: Methods and applications

article en

Abstract

Object detection technology contributes to increasing operational efficiency, including in the industrial sector. Several object detection methods have been developed by researchers, such as classification/regression-based or region-based models. This study has reviewed the object detection technology related to the methods and applications implemented in the industrial sector. The analysis method and review carried out refer to the systematic literature review (SLR) through several stages: (1) article searching strategy using the three keywords; (2) article selection results; (3) article analysis and review; and (4) documentation and conclusion. Data sources were taken from two major repositories, including Scopus and IEEExplore for the years 2023 to 2025. In the aspect of method, the YOLO model is a common method that is used in industrial sectors regarding its fast detection and efficiency, while in the aspect of object detection application is commonly implemented in robotic arms to control objects or things’ position and monitor the conveyor motor. Object detection methods continue to experience development and adaptation in various sectors, making it an interesting topic to be discussed in the paper review.

Springer Link (Chiba Institute of Technology)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Advanced Neural Network Applications
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