{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,19]],"date-time":"2026-04-19T20:02:36Z","timestamp":1776628956498,"version":"3.51.2"},"reference-count":51,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T00:00:00Z","timestamp":1642982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Zhejiang Normal University Research Fund","award":["ZC304021938"],"award-info":[{"award-number":["ZC304021938"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To better regulate smoking in no-smoking areas, we present a novel AI-based surveillance system for smart cities. In this paper, we intend to solve the issue of no-smoking area surveillance by introducing a framework for an AI-based smoker detection system for no-smoking areas in a smart city. Moreover, this research will provide a dataset for smoker detection problems in indoor and outdoor environments to help future research on this AI-based smoker detection system. The newly curated smoker detection image dataset consists of two classes, Smoking and NotSmoking. Further, to classify the Smoking and NotSmoking images, we have proposed a transfer learning-based solution using the pre-trained InceptionResNetV2 model. The performance of the proposed approach for predicting smokers and not-smokers was evaluated and compared with other CNN methods on different performance metrics. The proposed approach achieved an accuracy of 96.87% with 97.32% precision and 96.46% recall in predicting the Smoking and NotSmoking images on a challenging and diverse newly-created dataset. Although, we trained the proposed method on the image dataset, we believe the performance of the system will not be affected in real-time.<\/jats:p>","DOI":"10.3390\/s22030892","type":"journal-article","created":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T21:07:11Z","timestamp":1643144831000},"page":"892","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["CNN-Based Smoker Classification and Detection in Smart City Application"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5364-645X","authenticated-orcid":false,"given":"Ali","family":"Khan","sequence":"first","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua 321004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3489-1094","authenticated-orcid":false,"given":"Somaiya","family":"Khan","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3672-8100","authenticated-orcid":false,"given":"Bilal","family":"Hassan","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhonglong","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua 321004, China"},{"name":"Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MC.2014.281","article-title":"E-Government Interoperability: Linking Open and Smart Government","volume":"47","author":"Jimenez","year":"2014","journal-title":"Computer"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MMUL.2018.2873564","article-title":"AI-Oriented Large-Scale Video Management for Smart City: Technologies, Standards, and Beyond","volume":"26","author":"Duan","year":"2018","journal-title":"IEEE MultiMedia"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1109\/TBDATA.2017.2715815","article-title":"Smart Monitoring Cameras Driven Intelligent Processing to Big Surveillance Video Data","volume":"4","author":"Shao","year":"2017","journal-title":"IEEE Trans. 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