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Cloud-based platform for intelligent healthcare monitoring and risk prevention in hazardous manufacturing contexts

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conference contribution
posted on 2021-05-06, 10:45 authored by Alessandro Simeone, Alessandra Caggiano, Lev Boun, Rebecca GrantRebecca Grant
This paper presents an intelligent cloud-based platform for workers healthcare monitoring and risk prevention in potentially hazardous manufacturing contexts. The platform is structured according to sequential modules dedicated to data acquisition, processing and decision-making support. Several sensors and data sources, including smart wearables, machine tool embedded sensors and environmental sensors, are employed for data collection, comprising information on offline clinical background, operational and environmental data. The cloud data processing module is responsible for extracting relevant features from the acquired data in order to feed a machine learning-based decision-making support system. The latter provides a classification of workers’ health status so that a prompt intervention can be performed in particularly challenging scenarios.

Funding

Research Start-up Fund Subsidized Project of Shantou University, China, (No. NFT17004)

CLOUD MODE “CLOUD Manufacturing for On-Demand manufacturing sErvices” of the University of Naples Federico II, Italy (000011-ALTRI_ DR_3450_2016_RICERCA_ATENEO-CAGGIANO)

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Procedia CIRP

Volume

99

Pages

50 - 56

Source

14th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 15-17 July 2020

Publisher

Elsevier

Version

  • VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2021-05-03

Copyright date

2021

ISSN

2212-8271

Language

  • en

Location

Online

Event dates

15th July 2020 - 17th July 2020

Depositor

Dr Rebecca Grant. Deposit date: 4 May 2021

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