Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/17231
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dc.contributor.authorChaiyarab L.
dc.contributor.authorMopung C.
dc.contributor.authorCharoenpong T.
dc.date.accessioned2022-03-10T13:16:39Z-
dc.date.available2022-03-10T13:16:39Z-
dc.date.issued2021
dc.identifier.other2-s2.0-85118982597
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/17231-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85118982597&doi=10.1109%2fICKII51822.2021.9574661&partnerID=40&md5=10105498df3dae5240836ca052ecc635
dc.description.abstractAn infectious and contagious disease affects human life significantly. Unexpectedly, monthly check-up of patients is inconvenient to receive a medical supply. Conveniently receiving medical supplies is a solution to hospital patients, eliminating crowded environments, and reducing contamination of the surface area. Therefore, this paper proposed a medical dispenser machine composed of two parts which are Web-based and face recognition in real-time. The medical profession can adjust the quantity of medicine. After the pharmacist arranged medicine, the email is distributed to the patients with the date and time for receiving packages. An automated system with a machine-learning algorithm assists them in receiving medical supply by using face recognition with Histogram Orientated Gradients (HOG) embedded in Raspberry Pi 4B. Face recognition is the ultimate technology to improve and make an impact in people's lives by diminishing contamination by viruses by not touching any surface area. The result of 50 image inputs showed an impressive recognition of authorized individuals with an accuracy of 80.0 %. This work combines hardware set up with PHP Web-based to distribute the medical supply efficiently. Subsequently, the implementation performed a satisfying performance that was suitable for the hospital. © 2021 IEEE.
dc.languageen
dc.subjectAutomation
dc.subjectDispensers
dc.subjectHospitals
dc.subjectLearning algorithms
dc.subjectMachine learning
dc.subjectViruses
dc.subjectWebsites
dc.subjectAuthentication systems
dc.subjectAutomatic medicine dispensing
dc.subjectDispenser machine
dc.subjectFaces detection
dc.subjectFirebase console
dc.subjectHaar cascade
dc.subjectHistogram orientated gradient
dc.subjectRaspberry pi
dc.subjectSurface area
dc.subjectWeb based
dc.subjectFace recognition
dc.titleAuthentication System by using HOG Face Recognition Technique and Web-Based for Medical Dispenser Machine
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitation4th IEEE International Conference on Knowledge Innovation and Invention 2021, ICKII 2021. Vol , No. (2021), p.97-100
dc.identifier.doi10.1109/ICKII51822.2021.9574661
Appears in Collections:Scopus 1983-2021

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