Smart automation through computer vision and image processing: a systematic literature review
Keywords:
Computer vision, Image processing, Smart automation, Deep learning, Artificial intelligenceAbstract
This systematic literature review focused on the role of computer vision (CV) and image processing (IP) in smart automation, including their applications in manufacturing processes, healthcare, agricultural production, infrastructure, and edge computing, as well as their implications for these areas. The OpenAlex database was used to identify relevant studies published between 2013 and 2025. Eight empirical studies were included in this review, each reporting quantitative results. The reviewed articles evaluated the accuracy of classification, average precision, throughput, and various rates of defects detected for specific purposes, such as inspection, pest detection, parking, edge vision, and simulated instrument use. Due to the differences in their findings and contexts, it was not possible to combine the results reported by the selected studies into a single summary estimate. The reviewed articles indicate that computer vision techniques can be utilized to facilitate certain forms of automated decision-making but require additional research into external validity and actual performance after implementation. This article summarizes the eight studies included in the completed OpenAlex search.
References
[1] M. A. Rahman, M. F. Shahrior, K. Iqbal & A. A. Abushaiba, ``Enabling intelligent industrial automation: a review of machine learning applications with digital twin and edge AI integration'', Automation 6 (2025) 37. https://doi.org/10.3390/automation6030037.
[2] R. Szeliski, Computer Vision: Algorithms and Applications, 2nd ed., Springer, Cham, Switzerland, 2022. https://doi.org/10.1007/978-3-030-34372-9.
[3] K. He, X. Zhang, S. Ren & J. Sun, ``Deep residual learning for image recognition'', 2016 IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, 2016, pp. 770. https://doi.org/10.1109/CVPR.2016.90.
[4] Y.-P. Cheng, C.-W. Li & Y.-C. Chen, ``Apply computer vision in GUI automation for industrial applications'', Mathematical Biosciences and Engineering 16 (2019) 7526. https://doi.org/10.3934/mbe.2019378.
[5] Q. Cheng, ``Application of computer vision technology in industrial automation'', Journal of Physics: Conference Series 2037 (2021) 012015. https://doi.org/10.1088/1742-6596/2037/1/012015.
[6] C. Cui & Y. Li, ``Application of computer visual recognition in industrial automation assembly production line'', Journal of Physics: Conference Series 1992 (2021) 032067. https://doi.org/10.1088/1742-6596/1992/3/032067.
[7] M. Park & J. Jeong, ``Design and implementation of machine vision-based quality inspection system in mask manufacturing process'', Sustainability 14 (2022) 6009. https://doi.org/10.3390/su14106009.
[8] C. A. de Souza Silva & E. P. Paladini, ``Smart machine vision system to improve decision-making on the assembly line'', Machines 13 (2025) 98. https://doi.org/10.3390/machines13020098.
[9] S. J. More & A. J. More, ``Computer vision & IoT based smart conveyor belt sorting system'', International Journal of Engineering Research & Technology 13 (2024) IJERTV13IS060066. Available online: https://www.ijert.org/computer-vision-iot-based-smart-conveyor-belt-sorting-system.
[10] I. Yousif, L. Burns, F. El Kalach & R. Harik, ``Leveraging computer vision towards high-efficiency autonomous industrial facilities'', Journal of Intelligent Manufacturing 36 (2025) 2983. https://doi.org/10.1007/s10845-024-02396-1.
[11] J.-S. Chou & C.-H. Liu, ``Automated sensing system for real-time recognition of trucks in river dredging areas using computer vision and convolutional deep learning'', Sensors 21 (2021) 555. https://doi.org/10.3390/s21020555.
[12] S. R. Addula & A. K. Tyagi, ``Future of computer vision and industrial robotics in smart manufacturing'', in Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing, A. K. Tyagi, S. Tiwari, S. K. Arumugam & A. K. Sharma (Eds.), Wiley, Hoboken, NJ, USA, 2024, pp. 505--539. https://doi.org/10.1002/9781394303601.ch22.
[13] R. Bhana, H. Mahmoud & M. Idrissi, ``Smart industrial safety using computer vision'', 2023 28th International Conference on Automation and Computing, Birmingham, UK, 2023, pp. 1--6. https://doi.org/10.1109/ICAC57885.2023.10275164.
[14] J. L. Mira, J. Barba, F. P. Romero, M. S. Escolar, J. Caba & J. C. López, ``Benchmarking of computer vision methods for energy-efficient high-accuracy olive fly detection on edge devices'', Multimedia Tools and Applications 83 (2024) 81785. https://doi.org/10.1007/s11042-024-18589-y.
[15] G. Li, Z. Liu, Z. Feng, J. Lyu, B. Li, G. Chen & Q. Yao, ``Research on a machine vision-based electro-killing pheromone-baited intelligent agricultural pest monitoring method'', Frontiers in Plant Science 16 (2025) 1521594. https://doi.org/10.3389/fpls.2025.1521594.
[16] H. A. Zhou, D. Wolfschläger, C. Florides, J. Werheid, H. Behnen, J.-H. Woltersmann, T. C. Pinto, M. Kemmerling, A. Abdelrazeq & R. H. Schmitt, ``Generative AI in industrial machine vision: a review'', Journal of Intelligent Manufacturing 37 (2026) 1447. https://doi.org/10.1007/s10845-025-02604-6.
[17] M. J. Page, J. E. McKenzie, P. M. Bossuyt, I. Boutron, T. C. Hoffmann, C. D. Mulrow, L. Shamseer, J. M. Tetzlaff, E. A. Akl, S. E. Brennan, R. Chou, J. Glanville, J. M. Grimshaw, A. Hróbjartsson, M. M. Lalu, T. Li, E. W. Loder, E. Mayo-Wilson, S. McDonald, L. A. McGuinness, L. A. Stewart, J. Thomas, A. C. Tricco, V. A. Welch, P. Whiting & D. Moher, ``The PRISMA 2020 statement: an updated guideline for reporting systematic reviews'', BMJ 372 (2021) n71. https://doi.org/10.1136/bmj.
[18] A. Shaushenova, O. Kuznetsov, A. Nurpeisova & M. Ongarbayeva, ``Implementation of Kolmogorov--Arnold networks for efficient image processing in resource-constrained Internet of Things devices'', Technologies 13 (2025) 155. https://doi.org/10.3390/technologies13040155.
[19] R. Rani, S. Kumar, S. K. Pippal, M. Gund, U. Chaudhari, R. Agrawal, M. Dalsaniya & L. Verma, ``IPS: intelligent parking system using YOLO and image processing'', International Journal of Transport Development and Integration 8 (2024) 447. https://doi.org/10.18280/ijtdi.080308.
[20] J. Shreyas, A. P. Jyothi & H. M. Mallaradhya, ``Smart robotic surgical assistant using voice command and image processing'', International Journal of Multidisciplinary Research and Analysis 7 (2024) 5457. https://doi.org/10.47191/ijmra/v7-i12-12.
[21] S. Khan, M. Naseer, M. Hayat, S. W. Zamir, F. S. Khan & M. Shah, ``Transformers in vision: a survey'', ACM Computing Surveys 54 (2022) 200. https://doi.org/10.1145/3505244.
[22] S. Pak, S. G. Park, J. Park, H. R. Choi, J. H. Lee, W. Lee, S. T. Cho, Y. G. Lee & H. Ahn, ``Application of deep learning for semantic segmentation in robotic prostatectomy: comparison of convolutional neural networks and visual transformers'', Investigative and Clinical Urology 65 (2024) 551. https://doi.org/10.4111/icu.20240159.
[23] A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark, G. Krueger & I. Sutskever, ``Learning transferable visual models from natural language supervision'', Proceedings of Machine Learning Research 139 (2021) 8748. Available online: https://proceedings.mlr.press/v139/radford21a.html.
[24] A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, P. Dollár & R. Girshick, ``Segment Anything'', 2023 IEEE/CVF International Conference on Computer Vision, Paris, France, 2023, pp. 4015--4026. Available online: https://openaccess.thecvf.com/content/ICCV2023/html/Kirillov_Segment_Anything_ICCV_2023_paper.html.
[25] M. Caron, H. Touvron, I. Misra, H. Jégou, J. Mairal, P. Bojanowski & A. Joulin, ``Emerging properties in self-supervised vision transformers'', 2021 IEEE/CVF International Conference on Computer Vision, Montreal, Canada, 2021, pp. 9650--9660. Available online: https://openaccess.thecvf.com/content/ICCV2021/html/Caron_Emerging_Properties_in_Self-Supervised_Vision_Transformers_ICCV_2021_paper.html.
Published
How to Cite
Issue
Section
Copyright (c) 2026 Osita Miracle Nwakeze, Nwabudike Uju Cynthia, Omorogie Michael, Chukwura Anthony Afamefuna, Udensi Nkechi Grace Cecilia, Ezekiel-Odimgbe Chinenye Love
This work is licensed under a Creative Commons Attribution 4.0 International License.
