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This research emphasized the application of Internet of Things (IoT) in enhancing the customer data warehousing, data mining, and analysis of energy consumption behavior data of the UAE construction industry. In this study, convenience sampling was used, and 209 participants were selected for the study. Utilizing SmartPLS 4.0 software, the study precisely assessed the reliability and validity of data to come up with solid results. Based on this, a structured equation model (SEM) was used to further hypothesis testing, and it provided rather conclusive findings. Some main findings reveal IoT integration improves data warehousing processes, providing better results of the consumption behavior categorization among the construction firms in the UAE. However, the study points out the significant importance of IoT in enhancing the efficiency of data mining with regard to understanding customers’ behaviors in terms of energy utilization patterns. Based on the results obtained, it is possible to assert that improvements in strategic decision-making due to IoT-driven optimizations in data analysis are beneficial for the construction industry in terms of encouraging sustainable practices and resource management. Consequently, the present research adds substantial knowledge in the realm of IoT for improving the operational processes and measures for sustainability in the construction industry of the UAE context.

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Investigating the Influence of IoT on Optimizing Customer Data Warehousing, Data Mining, and Data Analysis on Categorizing Energy Consumption Behavior Data

  • 会议论文

  • 发表日期：

    2025年

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  • Muhammad Turki Alshurideh,
  • Mounir El Khatib,
  • Khalid Al-Sulaiti,
  • Lilana Sukkari,
  • Barween Al Kurdi,
  • Aram Khalaf Nawaiseh,
  • Wasfi A. Alrawabdeh,
  • Azad Alshurideh,
  • Fanar Shwedeh,
  • Haitham M. Alzoubi

摘要

This research emphasized the application of Internet of Things (IoT) in enhancing the customer data warehousing, data mining, and analysis of energy consumption behavior data of the UAE construction industry. In this study, convenience sampling was used, and 209 participants were selected for the study. Utilizing SmartPLS 4.0 software, the study precisely assessed the reliability and validity of data to come up with solid results. Based on this, a structured equation model (SEM) was used to further hypothesis testing, and it provided rather conclusive findings. Some main findings reveal IoT integration improves data warehousing processes, providing better results of the consumption behavior categorization among the construction firms in the UAE. However, the study points out the significant importance of IoT in enhancing the efficiency of data mining with regard to understanding customers’ behaviors in terms of energy utilization patterns. Based on the results obtained, it is possible to assert that improvements in strategic decision-making due to IoT-driven optimizations in data analysis are beneficial for the construction industry in terms of encouraging sustainable practices and resource management. Consequently, the present research adds substantial knowledge in the realm of IoT for improving the operational processes and measures for sustainability in the construction industry of the UAE context.