Please use this identifier to cite or link to this item: http://ir.lib.seu.ac.lk/handle/123456789/6352
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dc.contributor.authorJayasekara, J. T. N. N.-
dc.contributor.authorGunasekera, R. H.-
dc.contributor.authorRavindu Hasanka, V. G.-
dc.contributor.authorHasintha Kashmika, H. B. G.-
dc.contributor.authorSuriyaa Kumari, P. K.-
dc.contributor.authorRavi Supunya Swarnakanthac, N. H. P.-
dc.date.accessioned2022-12-06T10:58:43Z-
dc.date.available2022-12-06T10:58:43Z-
dc.date.issued2022-11-15-
dc.identifier.citation11th Annual Science Research Sessions 2022 (ASRS-2022) Proceedings on "“Scientific Engagement for Sustainable Futuristic Innovations”. 15th November 2022. Faculty of Applied Sciences, South Eastern University of Sri Lanka, Sammanthurai, Sri Lanka. pp. 21.en_US
dc.identifier.isbn978-624-5736-60-7-
dc.identifier.urihttp://ir.lib.seu.ac.lk/handle/123456789/6352-
dc.description.abstractEspecially today's society tends to use new technological devices instead of relying on on document materials in daily life. While there are diabetes-related apps that more accurately predict users' prediabetes or diabetes type 2 using machine learning approaches, predicting health risks by analyzing glucose monitoring data, recommend meal and exercise plans, and use a non-invasive approach to measure and monitor blood glucose level, heart rate, and blood oxygen level, and over Wi-Fi using NodeMCU makes the proposed DiaBeta application unique among diabetes applications. Other secondary functions such as digital logbook, reminders, lifestyle-based meal recommendations, medical guidelines, and efforts such as glucose monitoring data can be easily performed with a smartphone. DiaBeta is a life-saving app that can be used by anyone around the world to get a more accurate and personalized meal plan. DiaBeta offers a precise, clinical, validated, and standardized solution for diabetes patients.en_US
dc.language.isoen_USen_US
dc.publisherFaculty of Applied Sciences, South Eastern University of Sri Lanka, Sammanthurai.en_US
dc.subjectNon-Invasiveen_US
dc.subjectDiabetes Predictionen_US
dc.subjectMachine Learningen_US
dc.subjectNodeMCUen_US
dc.subjectLoTen_US
dc.titleIntelligent, secured smart app for complete diabetes lifestyle management –“Diabeta”en_US
dc.typeArticleen_US
Appears in Collections:11th Annual Science Research Session - FAS

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