AN EXHAUSTIVE SURVEY ON COMPUTATIONAL INTELLIGENCE APPROACHES FOR MAINTENANCE OF HOUSING PROPERTIES
Keywords:
Artificial Intelligence, Machine Learning, Predictive Maintenance, Computational Intelligence, Energy Efficiency, Defect DetectionAbstract
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.
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Copyright (c) 2024 Ashok Kandipati (Author)
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