Suggestion new monitoring system by depending on the human activity recognition videos

Basit Öğe Kaydı
dc.contributor.authorIbrahim, Al-Siraj, M.N.
dc.contributor.authorCevik, M.
dc.contributor.authorIbrahim, S.M.
dc.date.accessioned2024-09-29T16:20:47Z
dc.date.available2024-09-29T16:20:47Z
dc.date.issued2022
dc.departmentKarabük Üniversitesien_US
dc.description6th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2022 -- 20 October 2022 through 22 October 2022 -- Ankara -- 184355en_US
dc.description.abstractModern home monitoring system techniques, such as motion detection technology and home camera system intrusion warning, are said to be insufficient, especially to meet the needs of whole automation with flaws such as needing human interaction. We suggest a substitute system, a human activity recognition (HAR) method based on the video, and a combination of long short-term memory (LSTM) and convolution neural networks (CNN) algorithm, to address the flaws that have been found. Our suggestion doesn't need to be changed. is simply deployed utilizing just low-cost modifications to the current home security protocols, and commercially available hardware The conventional security camera may be used with ease for computer vision applications. Utilizing information on actual activity gathered by video-based sensors, we assess our strategy. By drawing Loss and Accuracy curves, we demonstrate how successful it is. Show Results demonstrate that the video-approved human activity recognition method can deliver complete home automation. The monitoring system has higher accuracy as compared to traditional camera motion detectors. The precision of the system may be improved further, and we can attain for best results. (Long-term Recurrent Cnvlution Network) implementation yields result better. © 2022 IEEE.en_US
dc.identifier.doi10.1109/ISMSIT56059.2022.9932751
dc.identifier.endpage354en_US
dc.identifier.isbn978-166547013-1
dc.identifier.scopus2-s2.0-85142820515en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage351en_US
dc.identifier.urihttps://doi.org/10.1109/ISMSIT56059.2022.9932751
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9328
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofISMSIT 2022 - 6th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectand Human Action Recognitionen_US
dc.subjectComputer Visionen_US
dc.subjectDeep Learningen_US
dc.subjectTenser flowen_US
dc.titleSuggestion new monitoring system by depending on the human activity recognition videosen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu