{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:41:50Z","timestamp":1747190510053,"version":"3.40.5"},"reference-count":40,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,4,20]],"date-time":"2021-04-20T00:00:00Z","timestamp":1618876800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Major Special Science and Technology Project of Hainan Province","award":["ZDKJ2017012","2020YFB2104004","2021-GX-112"],"award-info":[{"award-number":["ZDKJ2017012","2020YFB2104004","2021-GX-112"]}]},{"name":"National Key R&D Program of China","award":["ZDKJ2017012","2020YFB2104004","2021-GX-112"],"award-info":[{"award-number":["ZDKJ2017012","2020YFB2104004","2021-GX-112"]}]},{"name":"Qinghai Key R&D and Transformation Project","award":["ZDKJ2017012","2020YFB2104004","2021-GX-112"],"award-info":[{"award-number":["ZDKJ2017012","2020YFB2104004","2021-GX-112"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mobile Information Systems"],"published-print":{"date-parts":[[2021,4,20]]},"abstract":"<jats:p>The field of activity recognition has evolved relatively early and has attracted countless researchers. With the continuous development of science and technology, people\u2019s research on human activity recognition is also deepening and becoming richer. Nowadays, whether it is medicine, education, sports, or smart home, various fields have developed a strong interest in activity recognition, and a series of research results have also been put into people\u2019s real production and life. Nowadays, smart phones have become quite popular, and the technology is becoming more and more mature, and various sensors have emerged at the historic moment, so the related research on activity recognition based on mobile phone sensors has its necessity and possibility. This article will use an Android smartphone to collect the data of six basic behaviors of human, which are walking, running, standing, sitting, going upstairs, and going downstairs, through its acceleration sensor, and use the classic model of deep learning CNN (convolutional neural network) to fuse those multidimensional mobile data, using TensorFlow for model training and test evaluation. The generated model is finally transplanted to an Android phone to complete the mobile-end activity recognition system.<\/jats:p>","DOI":"10.1155\/2021\/6615695","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T02:50:24Z","timestamp":1618973424000},"page":"1-11","source":"Crossref","is-referenced-by-count":1,"title":["Towards Activity Recognition through Multidimensional Mobile Data Fusion with a Smartphone and Deep Learning"],"prefix":"10.1155","volume":"2021","author":[{"given":"Junkuo","family":"Cao","sequence":"first","affiliation":[{"name":"Network and Data Center, Hainan Normal University, Haikou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingcai","family":"Lin","sequence":"additional","affiliation":[{"name":"Haikou National Science Park, Hainan Normal University, Haikou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi\u2019an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiacheng","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi\u2019an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7210-0543","authenticated-orcid":true,"given":"Yueshen","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi\u2019an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"issue":"3","key":"1","doi-asserted-by":"crossref","first-page":"752","DOI":"10.1109\/TETC.2018.2790080","article-title":"SEARE: a system for exercise activity recognition and quality evaluation based on green sensing","volume":"8","author":"F. 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