Literature DB >> 35637687

Indoor positioning systems to prevent the COVID19 transmission in manufacturing environments.

F Pilati1, A Sbaragli1, M Nardello1, L Santoro1, D Fontanelli1, D Brunelli1.   

Abstract

Since the 11th of March 2020 when the World Health Organization declared the novel COVID-19 outbreak a global pandemic, it registered officially over 5 million deaths worldwide. According to the course of the pandemic, governments encouraged best practices and then ruled out temporary restrictions on daily lives. In this scenario, non-essential labor-intensive sectors were forced to put on hold operations producing massive temporary layoffs. In gradually restoring the economic activities, governments passed several laws to passively mitigate the pathogen transmission in indoor working environments. However, several COVID19-related injuries were filled by manufacturing companies. According to the outlined conditions, this paper proposes an original and advanced hardware and software architecture to prevent the COVID19 transmission in indoor production environments. The aim is to increase the safety of whichever indoor productive workplace through a contact tracing approach. Indoor positioning systems due to their ability to accurately track the movement of tagged entities compose the hardware part. For this purpose, human operatives are equipped with adequate wearable sensors. Raw data acquired are properly mined through advanced algorithms to quantitatively assess the degree of safety of any working setting. Indeed, having as a reference the epidemiological evidence the software part defines an innovative risk index along two correlated dimensions. While the first defines the risk of any worker getting infected during the shift, the other one expresses the degree of COVID19-safety of the shop floor defined by the displacements of the anchors. Benefitting from these targeted and quantitative hints, plant supervisors may redesign the production settings to lower the chances of COVID19 infection. This innovative digital framework is validated in a real case study in the North of Italy which performs manual mechanical processing for the automotive industry.
© 2022 The Author(s). Published by Elsevier B.V.

Entities:  

Keywords:  contact tracing; covid19 transmission prevention; indoor positioning systems; manufacturing relayout; safe workplace

Year:  2022        PMID: 35637687      PMCID: PMC9134934          DOI: 10.1016/j.procir.2022.05.195

Source DB:  PubMed          Journal:  Procedia CIRP        ISSN: 2212-8271


  5 in total

1.  COVID-19 Contact Tracing: Challenges and Future Directions.

Authors:  Mohammad Jabed Morshed Chowdhury; Md Sadek Ferdous; Kamanashis Biswas; Niaz Chowdhury; Vallipuram Muthukkumarasamy
Journal:  IEEE Access       Date:  2020-11-09       Impact factor: 3.367

2.  A COVID-19 infection risk model for frontline health care workers.

Authors:  Louie Florendo Dy; Jomar Fajardo Rabajante
Journal:  Netw Model Anal Health Inform Bioinform       Date:  2020-08-08

3.  Occupant-density-detection based energy efficient ventilation system: Prevention of infection transmission.

Authors:  Junqi Wang; Jingjing Huang; Zhuangbo Feng; Shi-Jie Cao; Fariborz Haghighat
Journal:  Energy Build       Date:  2021-03-09       Impact factor: 5.879

4.  Laboratory Modeling of SARS-CoV-2 Exposure Reduction Through Physically Distanced Seating in Aircraft Cabins Using Bacteriophage Aerosol - November 2020.

Authors:  Watts L Dietrich; James S Bennett; Byron W Jones; Mohammad H Hosni
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2021-04-23       Impact factor: 17.586

Review 5.  Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.

Authors:  Abdulrahman Alarifi; AbdulMalik Al-Salman; Mansour Alsaleh; Ahmad Alnafessah; Suheer Al-Hadhrami; Mai A Al-Ammar; Hend S Al-Khalifa
Journal:  Sensors (Basel)       Date:  2016-05-16       Impact factor: 3.576

  5 in total
  1 in total

1.  Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation.

Authors:  Yi Li
Journal:  Comput Intell Neurosci       Date:  2022-09-13
  1 in total

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