{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T02:48:38Z","timestamp":1742957318848,"version":"3.40.3"},"publisher-location":"Cham","reference-count":9,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031538292"},{"type":"electronic","value":"9783031538308"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-53830-8_28","type":"book-chapter","created":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T10:02:25Z","timestamp":1709114545000},"page":"273-278","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Containerized Wearable Edge AI Inference Framework in\u00a0Mobile Health Systems"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6714-4402","authenticated-orcid":false,"given":"Lionel","family":"Nkenyereye","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5743-1010","authenticated-orcid":false,"given":"Boon Giin","family":"Lee","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0121-855X","authenticated-orcid":false,"given":"Wan-Young","family":"Chung","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,29]]},"reference":[{"issue":"6","key":"28_CR1","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1109\/MNET.001.1900059","volume":"33","author":"J Yang","year":"2019","unstructured":"Yang, J., Zhou, J., Tao, G., Alrashoud, M., Mutib, K.N.A., Al-Hammadi, M.: Wearable 3.0: from smart clothing to wearable affective robot. IEEE Netw. 33(6), 8\u201314 (2019). https:\/\/doi.org\/10.1109\/MNET.001.1900059","journal-title":"IEEE Netw."},{"key":"28_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1007\/978-3-319-13105-4_14","volume-title":"Ambient Assisted Living and Daily Activities","author":"O Banos","year":"2014","unstructured":"Banos, O., et al.: mHealthDroid: a novel framework for agile development of mobile health applications. In: Pecchia, L., Chen, L.L., Nugent, C., Bravo, J. (eds.) IWAAL 2014. LNCS, vol. 8868, pp. 91\u201398. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-13105-4_14"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Niranjan, D.R., Mohana: Jenkins pipelines: a novel approach to machine learning operations (MLOps). In: 2022 International Conference on Edge Computing and Applications (ICECAA), Tamilnadu, India, pp. 1292\u20131297 (2022)","DOI":"10.1109\/ICECAA55415.2022.9936252"},{"key":"28_CR4","unstructured":"bhimmetoglu. A tutorial for datascience for classifying human activity from body motion and vital signs recordings. https:\/\/github.com\/bhimmetoglu\/datasciencecom-mhealth. Accessed 25 Sept 2022"},{"issue":"9","key":"28_CR5","doi-asserted-by":"publisher","first-page":"8760","DOI":"10.1109\/JIOT.2020.2996578","volume":"7","author":"O Barut","year":"2020","unstructured":"Barut, O., Zhou, L., Luo, Y.: Multitask LSTM model for human activity recognition and intensity estimation using wearable sensor data. IEEE Internet Things J. 7(9), 8760\u20138768 (2020)","journal-title":"IEEE Internet Things J."},{"key":"28_CR6","unstructured":"DockerHub. Docker image for mobile Health pre-trained models and inference server. https:\/\/hub.docker.com\/repositories\/nkenye1982. Accessed 25 Apr 2023"},{"key":"28_CR7","doi-asserted-by":"publisher","unstructured":"Va\u00f1o, R., Lacalle, I., Sowi\u0144ski, P., S-Juli\u00e1n, R., Palau, C.E.: Cloud-native workload orchestration at the edge: a deployment review and future directions. Sensors 23, 2215 (2023). https:\/\/doi.org\/10.3390\/s23042215","DOI":"10.3390\/s23042215"},{"key":"28_CR8","unstructured":"Locust. An open source load testing tool. https:\/\/locust.io\/. Accessed 25 July 2023"},{"key":"28_CR9","unstructured":"Cloud Native Computing Foundation. An Industry-standard container runtime with an emphasis on simplicity, robusteness and portability. https:\/\/containerd.io\/. Accessed 25 July 2023"}],"container-title":["Lecture Notes in Computer Science","Intelligent Human Computer Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-53830-8_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T10:05:43Z","timestamp":1709114743000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-53830-8_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031538292","9783031538308"],"references-count":9,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-53830-8_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"29 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IHCI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Human Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Daegu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ihci2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.ihcisociety.org\/ihci-2023","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"139","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"55","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"16","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"User Friendly, Easy to manage","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}