A modified WBANs MAC superframe using priority-criticality index table for managing pilgrims’ emergency traffic in Hajj

Masud, Shah Murtaza Rashid Al; Bakar, Asmidar Abu; Yussof, Salman

doi:10.11591/ijeecs.v14.i3.pp1499-1507

Cited by 3 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e suggested ICS can aid in elucidating crowd characteristics such as density, velocity, location, and direction. In other research [5,[37][38][39][40], similar networks are also mentioned.…”

Section: Related Workmentioning

confidence: 99%

A Technology Survey on IoT Applications Serving Umrah and Hajj

Binsawad

Albahar

2022

Applied Computational Intelligence and Soft Computing

View full text Add to dashboard Cite

Emerging technologies provide a highly compatible platform for analyzing substantial data volumes relating to crowd management. These technologies are not only effective in providing remedial solutions but they are also cutting-edge, saving both time and money, and user-friendly. About twenty percent of the world’s Muslims are granted the ability to take part in religious observances on an annual basis. An in-depth analysis of the technologies and applications used in the Hajj and Umrah systems is required given the importance of utilizing and adapting technology to assist pilgrims performing the Hajj and Umrah. Both of these pilgrimages are considered acts of worship by Muslims. As a result, the services provided during Umrah and Hajj will be significantly enhanced if the numerous technological advancements that are evaluated in this paper are implemented. The majority of previous research is shown to revolve around artificial intelligence and embedded Internet of Things technologies in the paper, highlighting a gap in the research that should be filled by investigating the necessity of discussing and introducing immersive technologies. During the annual pilgrimage to Makkah, Saudi Arabia, several different technologies are utilized with the goal of enhancing the quality of services provided to pilgrims performing the Umrah and Hajj. This paper provides an analysis of these technologies. The findings of this paper point to new research directions as well as a more realistic and practical approach to improving services during Umrah and Hajj.

show abstract

Section: Related Workmentioning

confidence: 99%

A Technology Survey on IoT Applications Serving Umrah and Hajj

Binsawad

Albahar

2022

Applied Computational Intelligence and Soft Computing

View full text Add to dashboard Cite

show abstract

Progress of IoT Research Technologies and Applications Serving Hajj and Umrah

Shambour

Gutub

2021

Arab J Sci Eng

View full text Add to dashboard Cite

The term IoT technology is associated with many fields, including scientific, commercial, industrial, health, transportation and other fields, which became a necessity of daily life across all segments of society. Artificial intelligence, the Internet of things, data science and big data are among the most prominent fields of technologies in the modern era of e-knowledge, which are increasingly being relied on in many areas of our life. This research is considered very special and urgent affecting around 20% of the humanities, i.e., Muslim people, whom try to be selected to perform Islamic rituals every year. Given this importance of applying and adapting technologies to serve Hajj and Umrah performers, it is necessary to conduct an analytical study for the technologies and their applications that have been applied in the Hajj and Umrah system. The surveyed studies have been classified, according to their targeted services (focus area), into four main branches, including studies of the two holy mosques and the holy sites, studies of the pre-arrival visitors, housing and services studies, and transportation and crowd management studies. The classified studies were analyzed according to research field, research instrument, statistical method, nature of statistical data, data collection tools, and research citations. The paper outcome opens novel research practical directions selected based on holistic overview of the current technologies analytical survey, which is essential to be considered to improve Hajj and Umrah services coping with today’s technology, in addition to discussing other open issues that need further deep research.

show abstract

MedAi: A Smartwatch-Based Application Framework for the Prediction of Common Diseases Using Machine Learning

et al. 2023

View full text Add to dashboard Cite

Health information technology is one of today's fastest-growing and most powerful technologies. This technology is used predominantly for predicting illness and obtaining medications quickly because visiting a doctor and performing pathological tests can be time-consuming and expensive. This has prompted many researchers to contribute by developing new disease prediction systems or improving existing ones. This paper presents a smartwatch-based prediction system for multiple diseases such as ischemic heart disease, hypertension, respiratory disease, hyperthyroidism, hypothyroidism, stroke, myocardial infarction, kidney failure, gallstones, diabetes, and dyslipidemia using machine learning algorithms; and it is called 'MedAi'. It comprises three core modules: a prototype smartwatch 'Sense O'Clock' equipped with eleven sensors to collect bodily statistics, a machine learning model to analyze the data and make a prediction, and a mobile application to display the prediction result. A dataset consisting of patient bodily statistics was obtained from a local hospital according to ethical guidelines, such as obtaining the prior consent of both patients and doctors. We employ several machine learning algorithms, including Support Vector Machine (SVM), Support Vector Regression (SVR), K-Nearest Neighbor (KNN), Extreme Gradient Boosting (XGBoost), Long Short Term Memory (LSTM), and Random Forest (RF) to investigate the best performing algorithm. Experimentation using our dataset shows that the RF algorithm outperforms other machine learning algorithms such as SVM, KNN, XGBoost etc., in predicting aforementioned diseases with an accuracy of 99.4%. The system provides full-time assistance to the user by reporting his or her body condition and suggesting requisite remedies. It is a notable addition to early disease prediction systems and can predict multiple disease vulnerabilities before they reach an irrecoverable stage. Finally, we compare our method with the related existing methods.

show abstract

A modified WBANs MAC superframe using priority-criticality index table for managing pilgrims’ emergency traffic in Hajj

Cited by 3 publications

References 5 publications

A Technology Survey on IoT Applications Serving Umrah and Hajj

A Technology Survey on IoT Applications Serving Umrah and Hajj

Progress of IoT Research Technologies and Applications Serving Hajj and Umrah

MedAi: A Smartwatch-Based Application Framework for the Prediction of Common Diseases Using Machine Learning

Contact Info

Product

Resources

About