Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)

IoT is the greatest ingenious innovation in the modern era, which can exploit also in mission-critical like the healthcare industry. This paper demonstrates effective monitoring of pregnant women mostly in a rural area of a developing country, with the help of wearable sensing enabled technology, wh...

Full description

Bibliographic Details
Main Authors:	Marzia, Ahmed, Kashem, Mohammod Abul, Rahman, Mostafijur, Sabira, Khatun
Format:	Conference or Workshop Item
Language:	English English
Published:	Universiti Malaysia Pahang 2019
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/26685/ http://umpir.ump.edu.my/id/eprint/26685/1/38.%20Review%20and%20analysis%20of%20risk%20factor%20of%20maternal.pdf http://umpir.ump.edu.my/id/eprint/26685/2/38.1%20Review%20and%20analysis%20of%20risk%20factor%20of%20maternal.pdf

id	ump-26685
recordtype	eprints
spelling	ump-266852019-12-23T08:46:11Z http://umpir.ump.edu.my/id/eprint/26685/ Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT) Marzia, Ahmed Kashem, Mohammod Abul Rahman, Mostafijur Sabira, Khatun TK Electrical engineering. Electronics Nuclear engineering IoT is the greatest ingenious innovation in the modern era, which can exploit also in mission-critical like the healthcare industry. This paper demonstrates effective monitoring of pregnant women mostly in a rural area of a developing country, with the help of wearable sensing enabled technology, which also notifies the pregnant women and her family about the health conditions. There are many researchers have been researched to reduce the maternal and fetal mortality but the mortality rate is not reducing, where it should be in zero tolerance. This research intended to use machine learning algorithms for discovering the risk level on the basis of risk factors in pregnancy. In this research, an existing dataset (Pima-Indian-diabetes dataset) has been used for the analysis of risk factor and comparison of some machine learning algorithm shows that Logistic Model Tree (LMT) gives the highest accuracy in case of classification and prediction of the risk level. Regardless, few selected pregnant women’s data has been collected (through IoT enabled devices) and the same process also applied for this dataset also by using LMT. Comparison results show that the prediction of risks is the same for the existing and real dataset. Universiti Malaysia Pahang 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26685/1/38.%20Review%20and%20analysis%20of%20risk%20factor%20of%20maternal.pdf pdf en http://umpir.ump.edu.my/id/eprint/26685/2/38.1%20Review%20and%20analysis%20of%20risk%20factor%20of%20maternal.pdf Marzia, Ahmed and Kashem, Mohammod Abul and Rahman, Mostafijur and Sabira, Khatun (2019) Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT). In: 5th International Conference on Electrical, Control and Computer Engineering (INECCE 2019), 29-30 July 2019 , Swiss Garden Kuantan. pp. 1-9.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Marzia, Ahmed Kashem, Mohammod Abul Rahman, Mostafijur Sabira, Khatun Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)
description	IoT is the greatest ingenious innovation in the modern era, which can exploit also in mission-critical like the healthcare industry. This paper demonstrates effective monitoring of pregnant women mostly in a rural area of a developing country, with the help of wearable sensing enabled technology, which also notifies the pregnant women and her family about the health conditions. There are many researchers have been researched to reduce the maternal and fetal mortality but the mortality rate is not reducing, where it should be in zero tolerance. This research intended to use machine learning algorithms for discovering the risk level on the basis of risk factors in pregnancy. In this research, an existing dataset (Pima-Indian-diabetes dataset) has been used for the analysis of risk factor and comparison of some machine learning algorithm shows that Logistic Model Tree (LMT) gives the highest accuracy in case of classification and prediction of the risk level. Regardless, few selected pregnant women’s data has been collected (through IoT enabled devices) and the same process also applied for this dataset also by using LMT. Comparison results show that the prediction of risks is the same for the existing and real dataset.
format	Conference or Workshop Item
author	Marzia, Ahmed Kashem, Mohammod Abul Rahman, Mostafijur Sabira, Khatun
author_facet	Marzia, Ahmed Kashem, Mohammod Abul Rahman, Mostafijur Sabira, Khatun
author_sort	Marzia, Ahmed
title	Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)
title_short	Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)
title_full	Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)
title_fullStr	Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)
title_full_unstemmed	Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)
title_sort	review and analysis of risk factor of maternal health in remote area using the internet of things (iot)
publisher	Universiti Malaysia Pahang
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/26685/ http://umpir.ump.edu.my/id/eprint/26685/1/38.%20Review%20and%20analysis%20of%20risk%20factor%20of%20maternal.pdf http://umpir.ump.edu.my/id/eprint/26685/2/38.1%20Review%20and%20analysis%20of%20risk%20factor%20of%20maternal.pdf
first_indexed	2023-09-18T22:41:41Z
last_indexed	2023-09-18T22:41:41Z
_version_	1777416957570580480

Review and analysis of risk factor of maternal health in remote area using the Internet of Things (IoT)

Similar Items