{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T16:11:08Z","timestamp":1775923868389,"version":"3.50.1"},"reference-count":26,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T00:00:00Z","timestamp":1745539200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"The Key scientific research Projects of Higher Education Institutions in Henan Province","award":["No. 24A630029"],"award-info":[{"award-number":["No. 24A630029"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Computational Methods in Sciences and Engineering"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>\n                    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 CO\n                    <jats:sub>2<\/jats:sub>\n                    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\u2019s 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\u2019s 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.\n                  <\/jats:p>","DOI":"10.1177\/14727978251337923","type":"journal-article","created":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T20:41:57Z","timestamp":1745613717000},"page":"4180-4195","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"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"],"prefix":"10.1177","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0196-9258","authenticated-orcid":false,"given":"Lixiang","family":"Guo","sequence":"first","affiliation":[{"name":"Office of Educational Administration, Zhengzhou Vocational College of Finance and Taxation, Zhengzhou, China"}]}],"member":"179","published-online":{"date-parts":[[2025,4,25]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3331078"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.107938"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3204042"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.3390\/smartcities6050106"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.3390\/su12041500"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/su14159640"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2022.109095"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.3390\/s22062345"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2020.102231"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3250235"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2024.101099"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.technovation.2021.102427"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1080\/13562517.2020.1734922"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.buildenv.2021.108529"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10766-018-0570-1"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.indic.2020.100092"},{"key":"e_1_3_4_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2021.100387"},{"key":"e_1_3_4_19_2","article-title":"LoRaWAN-enabled smart campus: the dataset and a people counter use case","author":"Eldeeb E","year":"2023","unstructured":"Eldeeb E, Alves H. LoRaWAN-enabled smart campus: the dataset and a people counter use case. IEEE Internet Things J 2023.","journal-title":"IEEE Internet Things J"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3260979"},{"key":"e_1_3_4_21_2","first-page":"1","article-title":"Self-building artificial intelligence and machine learning to empower big data analytics in smart cities","volume":"1","author":"Alahakoon D","year":"2023","unstructured":"Alahakoon D, Nawaratne R, Xu Y, et al. Self-building artificial intelligence and machine learning to empower big data analytics in smart cities. 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