Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/410151
Title: | An Intelligent Real Time Iot Based System Irtbs for Monitoring Patients |
Researcher: | Prajapati Bharatkumar Bholabhai |
Guide(s): | Dr. S. M. Parikh |
Keywords: | Computer Science Computer Science Interdisciplinary Applications Engineering and Technology |
University: | Ganpat University |
Completed Date: | 2021 |
Abstract: | In the last decade, the world has witnessed several fundamental changes in Cardiovascular diseases (CVDs), especially heart diseases. The process of monitoring patients is manual while they are admitted to the hospitals. The World Health Organization reported the prime reason for human death is heart disease. WHO also mentioned the factors considering inappropriate blood pressure, usage of high salted food, lack of physical activities, tobacco habit, food containing TRANS-FATTY acids, etc. Cardiovascular patients can minimize the death ratio of humans if it is detected in the primary stages. The proper care and guidance of medical experts help decrease the chances of heart disease after catching it. newline newlineThe internet of things, cloud storage, and machine learning enhanced the opportunity of changing the world in the field of technology. The bedside monitor is a popular method for capturing the various body parameters with the help of sensors. The process of observing the patients using a bedside monitor is via manual mode and lacks further analysis. newline newlineThis study of Cardiovascular disease at different hospitals has been used to predict the early detection of heart disease using automated intelligent practice. Moreover, research has extended the capability of bedside monitors and store the capture body parameters on cloud storage. It took into consideration age, gender, habit of tobacco, cholesterol, blood pressure, BMI, etc., which hit the chances of the possibility of heart disease. The study helps the various stakeholders in the health care sector to understand the key results. newline newlineThe proposed research model is divided into three different phases. First phase is data capturing phases where the caretaker person creates the profile and gathers the patient information. In the secondary phase all the healthcare data uploaded on the cloud for further process. In the final stage the model is trained with the help of the existing healthcare records. newline newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/410151 |
Appears in Departments: | Faculty of Computer Applications |
Files in This Item:
File | Description | Size | Format | |
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01 front page.pdf | Attached File | 154.14 kB | Adobe PDF | View/Open |
03 abstract.pdf | 30.43 kB | Adobe PDF | View/Open | |
04 aknowledgement.pdf | 131.46 kB | Adobe PDF | View/Open | |
05 list of tables.pdf | 200.99 kB | Adobe PDF | View/Open | |
08 content.pdf | 325.75 kB | Adobe PDF | View/Open | |
09 chapter 1.pdf | 547.15 kB | Adobe PDF | View/Open | |
10 chapter 2.pdf | 513.71 kB | Adobe PDF | View/Open | |
11 chapter 3.pdf | 921.84 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 137.82 kB | Adobe PDF | View/Open | |
certificate.pdf | 226.08 kB | Adobe PDF | View/Open | |
decleration.pdf | 119.03 kB | Adobe PDF | View/Open |
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