An Evaluation Approach Enhancing Apartment Building Comfort through Artificial Intelligence

Abstract

Background: In the last two decades, there has been a growing interest in intelligent management systems capable of strengthening numerous industries. This study looks at the use of fuzzy sets for analyzing and enhancing the comfort levels of apartment dwellers. Objective: The basic objective of this project is to create an intelligent system which focuses on both statistical and subjective elements of living comfort. This article aims to help readers understand the difficulties and possible conflicts caused by insufficient data and the various subjective preferences of apartment purchasers. Methods: A fuzzy Petri net is a fundamental solution to the conflict between fuzzy knowledge and logical reasoning. The model combines numerous indicators such as neighborhood, neighboring area, home, and unit reviews, as well as price formulation and value fixation, to fully assess apartment building comfort. Results: The findings show that the suggested approach effectively handles the multidimensional character of comfort assessment. Using fuzzy systems and various indicators adds a nuanced viewpoint to the evaluation, accounting for physical and intangible variables that contribute to pleasant living in apartment complexes. Conclusion: The current study sheds light on the possibilities of artificial intelligence and fuzzy systems for improving apartment building comfort. It underlines the need for novel methodologies and intelligent management systems to tackle the complexity and subjectivities connected with assessing and enhancing apartment living comfort.

Keywords

• evaluation
• approach
• enhancing
• fuzzy petri net
• apartment building
• genetic algorithm
• comfort
• artificial intelligence
• fuzzy logic inference
• mamdani algorithm