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

¹ Graduate Institute, Prospective Technology of Electrical Engineering and Computer Science, National Chin-Yi University of Technology, 411030 Taichung, Taiwan
² Graduate Institute of Precision Manufacturing, National Chin-Yi University of Technology, 411030 Taichung, Taiwan

^* Corresponding author: indraisa89@gm.student.ncut.edu.tw

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.