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Leveraging advanced artificial intelligence (AI) models such as ChatGPT holds promise in reshaping the conceptualization, development, and commercialization of IoT devices. Through real\u2010world data utilization, AI enhances the effectiveness, adaptability, and intelligence of IoT devices and wearables, expediting their production process from ideation to deployment and customer assistance. However, integrating ChatGPT into IoT\u2013based devices and wearables poses ethical concerns including data ownership, security, privacy, accessibility, bias, accountability, cost, design, quality, storage, model training, explainability, consistency, fairness, safety, transparency, trust, and generalizability. Addressing these ethical principles necessitates a comprehensive review of the literature to identify and classify relevant principles. The author identified 14 ethical principles from the literature using a systematic literature review (SLR) with a criteria of frequency\u2009\u2265\u200950% based on similarities. Four categories emerge based on the identified ethical principles, culminating in the application of Fuzzy\u2010TOPSIS for analyzing, categorizing, ranking, and prioritizing these ethical principles. From the Fuzzy\u2010TOPSIS technique results, the principle of data security and privacy is the highly ranked ethical principle for IoT\u2013based software wearable devices with the ranking value of \u201c0.925\u201d as a consistency coefficient index. This method, well\u2010established in computer science, effectively navigates fuzzy and uncertain decision\u2010making scenarios. The pioneer outcomes of this study provide a taxonomy\u2010based valuable insight for software manufacturers, facilitating the analysis, ranking, categorization, and prioritization of ethical principles amid the integration of ChatGPT in IoT\u2013based devices and wearables\u2019 research and development.<\/jats:p>","DOI":"10.1155\/int\/6660868","type":"journal-article","created":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T01:17:59Z","timestamp":1745371079000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Ethical Principles of Integrating ChatGPT Into IoT\u2013Based Software Wearables: A Fuzzy\u2010TOPSIS Ranking and Analysis Approach"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4311-6068","authenticated-orcid":false,"given":"Maseeh Ullah","family":"Khan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4810-7883","authenticated-orcid":false,"given":"Muhammad Farhat","family":"Ullah","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2461-5417","authenticated-orcid":false,"given":"Sabeeh Ullah","family":"Khan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4338-5927","authenticated-orcid":false,"given":"Weiqiang","family":"Kong","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2025,4,22]]},"reference":[{"key":"e_1_2_11_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2024.104034"},{"key":"e_1_2_11_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-23983-1_10"},{"key":"e_1_2_11_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/math11051263"},{"key":"e_1_2_11_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2018.08.009"},{"key":"e_1_2_11_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2024.101405"},{"key":"e_1_2_11_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2021.103244"},{"key":"e_1_2_11_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3605943"},{"key":"e_1_2_11_8_2","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2024.052618"},{"key":"e_1_2_11_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-024-02310-4"},{"key":"e_1_2_11_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125095"},{"key":"e_1_2_11_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.giq.2023.101881"},{"key":"e_1_2_11_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.05.103"},{"key":"e_1_2_11_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iswa.2023.200308"},{"key":"e_1_2_11_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103476"},{"key":"e_1_2_11_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2025.104318"},{"key":"e_1_2_11_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125861"},{"key":"e_1_2_11_17_2","doi-asserted-by":"publisher","DOI":"10.1002\/itl2.411"},{"key":"e_1_2_11_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-023-10641-x"},{"key":"e_1_2_11_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/ojcs.2023.3300321"},{"key":"e_1_2_11_20_2","doi-asserted-by":"publisher","DOI":"10.3390\/asi7050078"},{"key":"e_1_2_11_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2022.106894"},{"key":"e_1_2_11_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.108377"},{"key":"e_1_2_11_23_2","doi-asserted-by":"publisher","DOI":"10.1002\/smr.2387"},{"key":"e_1_2_11_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106541"},{"key":"e_1_2_11_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/comst.2017.2731979"},{"key":"e_1_2_11_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iotcps.2023.05.004"},{"key":"e_1_2_11_27_2","doi-asserted-by":"publisher","DOI":"10.1002\/asi.24750"},{"key":"e_1_2_11_28_2","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12071509"},{"key":"e_1_2_11_29_2","unstructured":"PasrichaS.andWolfM. 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