Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386499533> ?p ?o ?g. }
- W4386499533 endingPage "126" @default.
- W4386499533 startingPage "90" @default.
- W4386499533 abstract "A computer's vision models the human's abilities to see and comprehend the environment. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects. Pattern recognition and Industry 4.0 have enhanced production automation, precision, efficiency, cost savings, and the ability to evaluate massive amounts of data to make better decisions. Also using IOT devices to monitor patient health remotely. Robotics automates dangerous and repetitive tasks, speeds up production, and improves product quality in Industry. The technologies, such as blockchain and digital twins, enhance security, transparency, and efficiency in industrial operations. The emergence of these technologies has spread its horizons from e-management to healthcare, and from agriculture to the digital economy. This chapter briefly explains the adoptions of the fourth industrial revolution, which uses technology such as AI, IoT, and cyber-physical systems to create smart factories that are highly automated, data-driven and connected." @default.
- W4386499533 created "2023-09-07" @default.
- W4386499533 creator A5020485282 @default.
- W4386499533 creator A5028190485 @default.
- W4386499533 date "2023-09-07" @default.
- W4386499533 modified "2023-10-16" @default.
- W4386499533 title "Industrial 4.0 Adaptation and Challenges in Pattern Recognition, Computer Vision, and IoT" @default.
- W4386499533 cites W2032233621 @default.
- W4386499533 cites W2125186487 @default.
- W4386499533 cites W2789444712 @default.
- W4386499533 cites W2994336423 @default.
- W4386499533 cites W3023264563 @default.
- W4386499533 cites W3089219526 @default.
- W4386499533 cites W3164246203 @default.
- W4386499533 cites W3174245551 @default.
- W4386499533 cites W3202581252 @default.
- W4386499533 cites W3206662769 @default.
- W4386499533 cites W3214945533 @default.
- W4386499533 cites W4200630024 @default.
- W4386499533 cites W4205837126 @default.
- W4386499533 cites W4205996330 @default.
- W4386499533 cites W4214616327 @default.
- W4386499533 cites W4220704354 @default.
- W4386499533 cites W4225619930 @default.
- W4386499533 cites W4225659306 @default.
- W4386499533 cites W4281983829 @default.
- W4386499533 cites W4282002152 @default.
- W4386499533 cites W4288801250 @default.
- W4386499533 cites W4288854983 @default.
- W4386499533 cites W4290375100 @default.
- W4386499533 cites W4304820640 @default.
- W4386499533 cites W4307764542 @default.
- W4386499533 cites W4312056556 @default.
- W4386499533 cites W4313378349 @default.
- W4386499533 cites W4313457971 @default.
- W4386499533 cites W4313887335 @default.
- W4386499533 cites W4315778741 @default.
- W4386499533 cites W4315782912 @default.
- W4386499533 cites W4315783030 @default.
- W4386499533 cites W4315783092 @default.
- W4386499533 cites W4315853528 @default.
- W4386499533 cites W4317435837 @default.
- W4386499533 cites W4317632579 @default.
- W4386499533 cites W4322628973 @default.
- W4386499533 cites W4323928462 @default.
- W4386499533 cites W4324134785 @default.
- W4386499533 cites W4366138895 @default.
- W4386499533 doi "https://doi.org/10.4018/978-1-6684-8602-3.ch007" @default.
- W4386499533 hasPublicationYear "2023" @default.
- W4386499533 type Work @default.
- W4386499533 citedByCount "0" @default.
- W4386499533 crossrefType "book-chapter" @default.
- W4386499533 hasAuthorship W4386499533A5020485282 @default.
- W4386499533 hasAuthorship W4386499533A5028190485 @default.
- W4386499533 hasConcept C111472728 @default.
- W4386499533 hasConcept C115901376 @default.
- W4386499533 hasConcept C120665830 @default.
- W4386499533 hasConcept C121332964 @default.
- W4386499533 hasConcept C126082660 @default.
- W4386499533 hasConcept C127413603 @default.
- W4386499533 hasConcept C136764020 @default.
- W4386499533 hasConcept C138885662 @default.
- W4386499533 hasConcept C139807058 @default.
- W4386499533 hasConcept C149635348 @default.
- W4386499533 hasConcept C154945302 @default.
- W4386499533 hasConcept C2522767166 @default.
- W4386499533 hasConcept C2524010 @default.
- W4386499533 hasConcept C2777986313 @default.
- W4386499533 hasConcept C2779530757 @default.
- W4386499533 hasConcept C2780233690 @default.
- W4386499533 hasConcept C33923547 @default.
- W4386499533 hasConcept C34413123 @default.
- W4386499533 hasConcept C38652104 @default.
- W4386499533 hasConcept C41008148 @default.
- W4386499533 hasConcept C78519656 @default.
- W4386499533 hasConcept C90509273 @default.
- W4386499533 hasConcept C90673727 @default.
- W4386499533 hasConceptScore W4386499533C111472728 @default.
- W4386499533 hasConceptScore W4386499533C115901376 @default.
- W4386499533 hasConceptScore W4386499533C120665830 @default.
- W4386499533 hasConceptScore W4386499533C121332964 @default.
- W4386499533 hasConceptScore W4386499533C126082660 @default.
- W4386499533 hasConceptScore W4386499533C127413603 @default.
- W4386499533 hasConceptScore W4386499533C136764020 @default.
- W4386499533 hasConceptScore W4386499533C138885662 @default.
- W4386499533 hasConceptScore W4386499533C139807058 @default.
- W4386499533 hasConceptScore W4386499533C149635348 @default.
- W4386499533 hasConceptScore W4386499533C154945302 @default.
- W4386499533 hasConceptScore W4386499533C2522767166 @default.
- W4386499533 hasConceptScore W4386499533C2524010 @default.
- W4386499533 hasConceptScore W4386499533C2777986313 @default.
- W4386499533 hasConceptScore W4386499533C2779530757 @default.
- W4386499533 hasConceptScore W4386499533C2780233690 @default.
- W4386499533 hasConceptScore W4386499533C33923547 @default.
- W4386499533 hasConceptScore W4386499533C34413123 @default.
- W4386499533 hasConceptScore W4386499533C38652104 @default.
- W4386499533 hasConceptScore W4386499533C41008148 @default.
- W4386499533 hasConceptScore W4386499533C78519656 @default.