IoT based health monitoring system for pregnant women & children
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021.
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10361-159442022-01-17T21:01:40Z IoT based health monitoring system for pregnant women & children Ohana, Fariha Islam Rahmina, Nabita Ahmed, Farin Basak, Anindita Mohsin, Abu S.M. Department of Electrical and Electronic Engineering, Brac University IoT IoT health monitoring system Pregnant women and child Fall detection Vaccination reminder Internet of things This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 107-111). This research inspects the monitoring of pregnant women and children using the Internet of Things in the modern healthcare system. The main focus is to ensure the safety of pregnant women and their children. Through our current project, we put forward a system that can firmly influence the standard of living for pregnant women and children positively. Our IoT-based device can monitor temperature & humidity, stress, and fetal heart rate. We can also use this device to monitor a child's health parameters. The microcontroller collects all the data of these parameters with the help of sensors and sends these data to the ThingSpeak server via Wi-Fi module ESP8266 and further analyzes it. This system is fully automated to be able to notify the user and an emergency contact in case of emergency whenever any sensor threshold value crosses. Our second device, which incorporates fall detection along with the monitoring of the pregnant woman’s heart rate and SpO2, is integrated with a vaccination reminder system that will notify the user about the immunization dates and the vaccine to be provided on a particular day. Through the different sensors incorporated in the devices, we can get all the specific health-related parameters of the pregnant woman and her child. The motive is to unobtrusively obtain crucial information about the health status of pregnant women and their children. Fariha Islam Ohana Nabita Rahmina Farin Ahmed Anindita Basak B. Electrical and Electronic Engineering 2022-01-17T06:04:02Z 2022-01-17T06:04:02Z 2021 2021-09 Thesis ID 18121028 ID 18110003 ID 18121039 ID 18121002 http://hdl.handle.net/10361/15944 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 125 pages application/pdf Brac University |
institution |
Brac University |
collection |
Institutional Repository |
language |
English |
topic |
IoT IoT health monitoring system Pregnant women and child Fall detection Vaccination reminder Internet of things |
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IoT IoT health monitoring system Pregnant women and child Fall detection Vaccination reminder Internet of things Ohana, Fariha Islam Rahmina, Nabita Ahmed, Farin Basak, Anindita IoT based health monitoring system for pregnant women & children |
description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021. |
author2 |
Mohsin, Abu S.M. |
author_facet |
Mohsin, Abu S.M. Ohana, Fariha Islam Rahmina, Nabita Ahmed, Farin Basak, Anindita |
format |
Thesis |
author |
Ohana, Fariha Islam Rahmina, Nabita Ahmed, Farin Basak, Anindita |
author_sort |
Ohana, Fariha Islam |
title |
IoT based health monitoring system for pregnant women & children |
title_short |
IoT based health monitoring system for pregnant women & children |
title_full |
IoT based health monitoring system for pregnant women & children |
title_fullStr |
IoT based health monitoring system for pregnant women & children |
title_full_unstemmed |
IoT based health monitoring system for pregnant women & children |
title_sort |
iot based health monitoring system for pregnant women & children |
publisher |
Brac University |
publishDate |
2022 |
url |
http://hdl.handle.net/10361/15944 |
work_keys_str_mv |
AT ohanafarihaislam iotbasedhealthmonitoringsystemforpregnantwomenchildren AT rahminanabita iotbasedhealthmonitoringsystemforpregnantwomenchildren AT ahmedfarin iotbasedhealthmonitoringsystemforpregnantwomenchildren AT basakanindita iotbasedhealthmonitoringsystemforpregnantwomenchildren |
_version_ |
1814308000580501504 |