Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16534
Title: Human-Friendly Ai on the Shop Floor: Leveraging Affective Computing and Machine Learning
Authors: Mathew, Sajan
Iyyappan, M
Modhe, Tejus
Keywords: Artificial General Intelligence
Artificial Intelligence
Automation System
Cluster Density
K-Means Clustering
Machine Learning
Issue Date: 2023
Publisher: 2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023
Institute of Electrical and Electronics Engineers Inc.
Citation: pp. 1-6
Abstract: In a proactive prognostication into exploring future scenarios of human artificial intelligence interaction among that paramount is very important to rethink and rework on our developments around narrow artificial intelligence. In the build of artificial systems that pivot safety and embed principles of collaborative intelligence. These technologies are potential to cultivated the process of transformation, optimization and predictive analytics using metrics like a cycle time, throughput time, forecasting errors, overall equipment effectiveness etc. These technologies are majorly focus in to the shop floor safety, workers wellbeing and collaborative human machine interaction. The merger of affective computing and machine learning as a whole to be focused upon is what is emphasized in this research work © 2023 IEEE.
URI: https://doi.org/10.1109/ICCAMS60113.2023.10525949
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16534
ISBN: 9798350317060
Appears in Collections:Conference Papers

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