AN EXHAUSTIVE SURVEY ON COMPUTATIONAL INTELLIGENCE APPROACHES FOR MAINTENANCE OF HOUSING PROPERTIES

This in-depth study investigates the use of computational intelligence techniques in housing property upkeep· Traditional maintenance techniques are growing less effective in addressing the issues of sustainability, cost-effectiveness, and efficiency as modern housing systems get more complicated [34]· The present review delves into the diverse computational intelligence methodologies that are transforming property maintenance methods, such as artificial intelligence, machine learning, and Internet of Things (IoT) applications [30] , [33]· We examine how they are used in resource allocation, energy optimization, defect detection, and predictive maintenance· The paper highlights the advantages and difficulties of these cutting-edge techniques through a wide range of real-world applications and case studies· According to our research, computational intelligence has a great deal of promise for raising the general sustainability of housing properties, cutting expenses, and increasing maintenance efficiency [32] [31]· But before it is widely used, issues including scalability, integration with current systems, and data quality must be resolved [7]· Researchers, property managers, and policymakers looking to use computational intelligence to improve housing maintenance tactics can learn a lot from this poll·

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-09
DOI
https://doi.org/10.5281/zenodo.13735666
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
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article

AN EXHAUSTIVE SURVEY ON COMPUTATIONAL INTELLIGENCE APPROACHES FOR MAINTENANCE OF HOUSING PROPERTIES

Zenodo (CERN European Organization for Nuclear Research)
Genomics and Phylogenetic Studies
article

AN EXHAUSTIVE SURVEY ON COMPUTATIONAL INTELLIGENCE APPROACHES FOR MAINTENANCE OF HOUSING PROPERTIES

article en

Abstract

This in-depth study investigates the use of computational intelligence techniques in housing property upkeep· Traditional maintenance techniques are growing less effective in addressing the issues of sustainability, cost-effectiveness, and efficiency as modern housing systems get more complicated [34]· The present review delves into the diverse computational intelligence methodologies that are transforming property maintenance methods, such as artificial intelligence, machine learning, and Internet of Things (IoT) applications [30] , [33]· We examine how they are used in resource allocation, energy optimization, defect detection, and predictive maintenance· The paper highlights the advantages and difficulties of these cutting-edge techniques through a wide range of real-world applications and case studies· According to our research, computational intelligence has a great deal of promise for raising the general sustainability of housing properties, cutting expenses, and increasing maintenance efficiency [32] [31]· But before it is widely used, issues including scalability, integration with current systems, and data quality must be resolved [7]· Researchers, property managers, and policymakers looking to use computational intelligence to improve housing maintenance tactics can learn a lot from this poll·

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 58%
Genomics and Phylogenetic Studies
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