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

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dc.contributor.authorIbrahim Al-Siraj, Marwah Nabeel
dc.contributor.authorÇevik, Mesut
dc.contributor.authorIbrahim, Shakir Mahmood
dc.date.accessioned2022-12-25T13:36:09Z
dc.date.available2022-12-25T13:36:09Z
dc.date.issued2022en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_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.en_US
dc.identifier.citationAl-siraj, M. N. I., Çevik, M., Ibrahim, S. M. (2022). Suggestion new monitoring system by depending on the human activity recognition videos. In 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 351-354). IEEE.en_US
dc.identifier.endpage354en_US
dc.identifier.isbn9781665470131
dc.identifier.scopus2-s2.0-85142820515
dc.identifier.scopusqualityN/A
dc.identifier.startpage351en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3153
dc.indekslendigikaynakScopus
dc.institutionauthorÇevik, Mesut
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofISMSIT 2022 - 6th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings
dc.relation.isversionof10.1109/ISMSIT56059.2022.9932751en_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHuman 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 videos
dc.typeConference Object

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