A comprehensive study on enhancing the smart campus evaluation index system through IoT technologies: A case study of a vocational college in Henan Province.
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| Title: | A comprehensive study on enhancing the smart campus evaluation index system through IoT technologies: A case study of a vocational college in Henan Province. |
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| Authors: | Guo, Lixiang1 (AUTHOR) 18703697991@163.com |
| Source: | Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). Sep2025, Vol. 25 Issue 5, p4180-4195. 16p. |
| Subjects: | Video blogs, Energy consumption, Internet of things, Light intensity, Key performance indicators (Management) |
| Abstract: | Campus evaluation approaches can potentially be significantly improved by the rapid deployment of Internet of Things (IoT) technology in learning settings. With an emphasis on important factors, including infrastructure quality, user engagement, safety, operational efficiency, and sustainability, this study offers a thorough evaluation index system for smart campuses. Leveraging IoT devices, different data types, including sensor data (temperature, humidity, light intensity, and CO2 levels), user interaction metrics (device usage duration and access frequency), operational metrics (energy and water usage), and security data (CCTV video and access logs), are collected. To determine the efficacy of smart campus initiatives, Binary Harris Hawk Optimizer Tuned Elastic Net Regression (BHHO-ENR) is used to evaluate the data and create key performance indicators (KPIs). The suggested index system's applicability is demonstrated by a case study done at a vocational college, which also provides information about the strengths and weaknesses of the learning environment. The results show that the evaluation index system offers an organized approach to monitor and enhance the educational experience on campus by using data to inform decisions. Given that it's useful, more investigation is recommended to improve the choice of indicators and take into account new IoT capabilities, which will ultimately help create a more robust and efficient educational ecosystem. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Abstract: | Campus evaluation approaches can potentially be significantly improved by the rapid deployment of Internet of Things (IoT) technology in learning settings. With an emphasis on important factors, including infrastructure quality, user engagement, safety, operational efficiency, and sustainability, this study offers a thorough evaluation index system for smart campuses. Leveraging IoT devices, different data types, including sensor data (temperature, humidity, light intensity, and CO2 levels), user interaction metrics (device usage duration and access frequency), operational metrics (energy and water usage), and security data (CCTV video and access logs), are collected. To determine the efficacy of smart campus initiatives, Binary Harris Hawk Optimizer Tuned Elastic Net Regression (BHHO-ENR) is used to evaluate the data and create key performance indicators (KPIs). The suggested index system's applicability is demonstrated by a case study done at a vocational college, which also provides information about the strengths and weaknesses of the learning environment. The results show that the evaluation index system offers an organized approach to monitor and enhance the educational experience on campus by using data to inform decisions. Given that it's useful, more investigation is recommended to improve the choice of indicators and take into account new IoT capabilities, which will ultimately help create a more robust and efficient educational ecosystem. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 14727978 |
| DOI: | 10.1177/14727978251337923 |
