Integration of Computer Vision Systems in Robotics and Industry 4.0
Computer vision is the field that focuses on automating and combining various processes and representations used for visual perception. The subject encompasses numerous approaches that provide individual use, such as image processing. Image processing is converting, transforming and transferring an image. This method is the statistical categorization of patterns based on applying statistical decision theory. Computer vision systems are deployed in various environments, from the shop floor and hospital suite to Mars and surgical suits. Incorporating computer vision in manufacturing is a groundbreaking step towards elevating Industry 4.0 by enhancing efficiency, accuracy and connectivity. This is driven by the compelling benefits realized when computer vision can be used in a factory to create a safe environment for all stakeholders and operators, affording machines with visual perception and enabling them to process and act on the high-richness of environmental data given input by a camera. Computer vision integrated into manufacturing is a drastic step towards more intelligent, efficient and connected production methods as part of Industry 4.0. This paper discusses different features of the Industrial Revolution, the role of computer vision in Industrial Revolution 4.0, and how computer vision affected the Industrial Revolution in future industry development. As computer vision debuts firsthand in commercial use in manufacturing, so is the industry about to explode with unprecedented creativity and productivity.
Authors
- Vikas Vikas (ORCID: https://orcid.org/0000-0002-3901-5205)
- Rajesh Prasad (ORCID: https://orcid.org/0000-0002-3456-6980)
- Amit Kumar (ORCID: https://orcid.org/0009-0002-5708-3225)
- Santosh Kumar Upadhaya
Institutions
- Institute of Management Technology (IN)
Publication Details
- Published
- 2024-11-23
- DOI
- https://doi.org/10.1109/icicat62666.2024.10923326
- Citations
- 1
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.35