Robotic Label Applicator: Design, Development and Visual Servoing Based Control

Lin, Chyi‐Yeu; Wagshum, Asheber T.; Le, Trung-Son

doi:10.1051/matecconf/20165606001

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…Each label is imprinted with a date and batch number using a laser video jet imprinter for the date and batch number on each label. Systec Vision System, Allen Bradley PLC power, Colour Touch Screen Controller interface, and complete kit validation are all part of the capabilities 68 .…”

Section: Metal Detector Targetsmentioning

confidence: 99%

Untitled

2023

IJPSR

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The rapid development of artificial intelligence (AI) has far-reaching consequences for the global economy. Computers are helping with human input, decisionmaking, and data provision in medicine more than ever before. AI, algorithms, robotics, and big data are all used in today's healthcare sector and the medical profession to derive inferences for monitoring large-scale medical trends and detecting and measuring individual risks and chances based on data-driven estimations. Healthcare is a knowledge-intensive industry that relies heavily on data and analytics to advance treatments and procedures. There has been a significant expansion in the types of medical data gathered in recent years. This includes clinical, genetic, behavioural and environmental information. Large volumes of data from various sources are generated daily by healthcare providers, biomedical researchers, and patients. Technology advancements, such as AI, allow for the analysis of human thought processes. The pharmaceutical business saw significant transformation as a result of the application of machine learning, AI, and automation processes. Various types of analysis have contributed to a general decline in death rates. The use of AI techniques aids in diagnosing the most serious illnesses. To properly diagnose and treat a patient, it is essential to first identify any potential genetic disputes. Technological advancements have made it easier for pharmaceutical companies to detect dosage mistakes. Machine learning relies on monetary analysis, regular spectral analysis and the feature attraction process. The creation of an intelligent computer program is crucial for modelling mechanical systems. In this review, we have glanced at how technology plays a part in the pharmaceutical industry and at the potential outcomes that robotics and AI could have. INTRODUCTION:Robotic systems with artificial intelligence (AI) can learn, make decisions, and solve problems in a manner comparable to that of a person, but they are not yet QUICK RESPONSE CODE

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Section: Metal Detector Targetsmentioning

confidence: 99%