Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/566991
Title: Iot based continuous glucose monitoring and intrusion detection system for diabetes mellitus using machine learning techniques
Researcher: Sathish N
Guide(s): Valarmathi K
Keywords: Computer Science
Computer Science Information Systems
Engineering and Technology
University: Anna University
Completed Date: 2024
Abstract: newlineHealth care industry and Internet of Things (IoT) are collaborative terms which share a common interest--- interest in helping the society in a better possible way. The oxford dictionary defines IoT as and#8213;the interconnection via the internet of computing devices embedded in everyday objects, enabling them to send and receive dataand#8214;. newlineThe term quotInternet of Thingsquot (IoT) describes the next generation of the Internet aimed at making it easier for products to communicate with each other. IoT serves as a medical assistant and is essential to many applications that keep an eye on healthcare facilities. Health technologists and specialists have created a great system that uses widely used technologies such as wireless channels, wearable technology, and other remote equipment to provide those who have an array of illness with cheaper medical oversight. Large volumes of data are gathered by network-connected sensors mounted in living spaces or worn on the body to evaluate the physical and mental health of the patient. The type of disease can be anticipated by examining the pattern of parameters that are observed. Multiple health checking tools are used sparingly by patients such as heart rate monitoring, hand hygiene monitoring, robotic surgery, are some of the examples for the application of Internet of Things. (https://ordr.net/article/iot-healthcare-examples/) newlineA study shows that in India more than 100 million people are living with diabetes. (https://www.bbc.com/news/world-asia-india-65852551) Many IoT based tools and devices support patients to monitor their blood glucose level. Still advancements in technological tools and methods are inevitable in the modern digital world. newlineiv newlineThis research work proposes the use of a Deep Siamese Domain Adaptation Convolutional Neural Network for Internet of Things-based Persistent Glucose Tracking for Diabetes Mellitus. Numerous researches have been done in this field of IoT based glucose level reading for Diabetes Mellitus. The investigation that has been discussed aims to
Pagination: xiii,135p.
URI: http://hdl.handle.net/10603/566991
Appears in Departments:Faculty of Information and Communication Engineering

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02_prelim pages.pdf2.6 MBAdobe PDFView/Open
03_content.pdf17.98 kBAdobe PDFView/Open
04_abstract.pdf135.28 kBAdobe PDFView/Open
05_chapter1.pdf214.89 kBAdobe PDFView/Open
06_chapter2.pdf331.55 kBAdobe PDFView/Open
07_chapter3.pdf1.44 MBAdobe PDFView/Open
08_chapter4.pdf362.15 kBAdobe PDFView/Open
09chapter5.pdf474.5 kBAdobe PDFView/Open
10_annexures.pdf108.22 kBAdobe PDFView/Open
80_recommendation.pdf57.92 kBAdobe PDFView/Open
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