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Autonomous Mobile Robots Inclusive Building Design for Facilities Management: Comprehensive PRISMA Review

Author(s): ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 11, v. 14
Page(s): 3615
DOI: 10.3390/buildings14113615
Abstract:

The increasing adoption of advanced technologies and the growing demand for automation have driven the development of innovative solutions for smart Facilities Management (FM). The COVID-19 pandemic accelerated this trend, highlighting the need for greater automation in FM, including the use of Autonomous Mobile Robots (AMRs). Despite this momentum, AMR adoption remains in its early stages, with limited knowledge and research available on their practical applications in FM. This study seeks to explore the challenges that hinder the successful integration of AMRs in the FM industry. To achieve this, a systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, encompassing three phases: identification, screening, and inclusion. The review covered 80 full-text articles published from 1994 to 2024, reflecting the growing interest in technological advancements for FM and the increased focus on AMR research. The study identified five key barriers specific to FM that affect AMR adoption: diverse operational contexts, poorly designed indoor environments, varying building occupants, multi-faceted FM functionalities, and differences in building exteriors. These findings provide a comprehensive understanding of the unique challenges faced by FM professionals, offering valuable insights for organizations and AMR developers to consider during the adoption process. The research contributes to the field by providing a foundation for FM practitioners, policymakers, and researchers to develop strategies for overcoming these barriers and advancing the adoption of AMR technologies in FM.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10810203
  • Published on:
    17/01/2025
  • Last updated on:
    17/01/2025
 
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