Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf Countries
Childhood obesity has become one of the major health issues in the global population. The increasing prevalence of childhood obesity is associated with serious health issues and comorbidities related to obesity. Several studies mentioned that childhood obesity became even worse recently due to the e...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/10/6/241 |
| _version_ | 1797455168753631232 |
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| author | Mohammed Faisal Hebah ElGibreen Nora Alafif Chibli Joumaa |
| author_facet | Mohammed Faisal Hebah ElGibreen Nora Alafif Chibli Joumaa |
| author_sort | Mohammed Faisal |
| collection | DOAJ |
| description | Childhood obesity has become one of the major health issues in the global population. The increasing prevalence of childhood obesity is associated with serious health issues and comorbidities related to obesity. Several studies mentioned that childhood obesity became even worse recently due to the effect of COVID-19 and the consequent policies and regulations. For that reason, Internet of Things (IoT) technologies should be utilized to overcome the challenges related to obesity management and provide care from a distance to improve the health care services for obesity. However, IoT by itself is a limited resource and it is important to consider other artificial intelligent (AI) components. Thus, this paper contributes into the literature of child obesity management by introducing a comprehensive survey for obesity management covering clinical work measuring the association between sleep disturbances and childhood obesity alongside physical activity and diet and comparatively analyzing the emerging technologies used to prevent childhood obesity. It further contributes to the literature by proposing an interactive smart framework that combines clinical and emerging AI/telehealth technologies to manage child obesity. The proposed framework can be used to reduce children obesity and improve their quality of life using Machine Learning (ML). It utilizes IoT devices to integrate information from different sources and complement it with a mobile application and web-based platform to connect parents and physicians with their child. |
| first_indexed | 2024-03-09T15:47:39Z |
| format | Article |
| id | doaj.art-5c4898a5acba4cd0a2122856c1b8ee6f |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-09T15:47:39Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-5c4898a5acba4cd0a2122856c1b8ee6f2023-11-24T18:22:23ZengMDPI AGSystems2079-89542022-12-0110624110.3390/systems10060241Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf CountriesMohammed Faisal0Hebah ElGibreen1Nora Alafif2Chibli Joumaa3Center of AI and Robotics (CAIR), Kuwait College of Science and Technology (KCST), Kuwait City 35002, KuwaitInformation Technology Department, College of Computer and Information Science, King Saud University, Riyadh 11543, Saudi ArabiaDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11451, Saudi ArabiaCenter of AI and Robotics (CAIR), Kuwait College of Science and Technology (KCST), Kuwait City 35002, KuwaitChildhood obesity has become one of the major health issues in the global population. The increasing prevalence of childhood obesity is associated with serious health issues and comorbidities related to obesity. Several studies mentioned that childhood obesity became even worse recently due to the effect of COVID-19 and the consequent policies and regulations. For that reason, Internet of Things (IoT) technologies should be utilized to overcome the challenges related to obesity management and provide care from a distance to improve the health care services for obesity. However, IoT by itself is a limited resource and it is important to consider other artificial intelligent (AI) components. Thus, this paper contributes into the literature of child obesity management by introducing a comprehensive survey for obesity management covering clinical work measuring the association between sleep disturbances and childhood obesity alongside physical activity and diet and comparatively analyzing the emerging technologies used to prevent childhood obesity. It further contributes to the literature by proposing an interactive smart framework that combines clinical and emerging AI/telehealth technologies to manage child obesity. The proposed framework can be used to reduce children obesity and improve their quality of life using Machine Learning (ML). It utilizes IoT devices to integrate information from different sources and complement it with a mobile application and web-based platform to connect parents and physicians with their child.https://www.mdpi.com/2079-8954/10/6/241children obesitymachine learningInternet of Things |
| spellingShingle | Mohammed Faisal Hebah ElGibreen Nora Alafif Chibli Joumaa Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf Countries Systems children obesity machine learning Internet of Things |
| title | Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf Countries |
| title_full | Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf Countries |
| title_fullStr | Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf Countries |
| title_full_unstemmed | Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf Countries |
| title_short | Reducing Children’s Obesity in the Age of Telehealth and AI/IoT Technologies in Gulf Countries |
| title_sort | reducing children s obesity in the age of telehealth and ai iot technologies in gulf countries |
| topic | children obesity machine learning Internet of Things |
| url | https://www.mdpi.com/2079-8954/10/6/241 |
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