TY - JOUR
T1 - Artificial intelligence and internet of things enabled intelligent framework for active and healthy living
AU - Alsareii, Saeed Ali
AU - Raza, Mohsin
AU - Alamri, Abdulrahman Manaa
AU - AlAsmari, Mansour Yousef
AU - Irfan, Muhammad
AU - Raza, Hasan
AU - Awais, Muhammad
PY - 2023/3/31
Y1 - 2023/3/31
N2 - Obesity poses several challenges to healthcare and the well-being of individuals. It can be linked to several life-threatening diseases. Surgery is a viable option in some instances to reduce obesity-related risks and enable weight loss. State-of-the-art technologies have the potential for long-term benefits in post-surgery living. In this work, an Internet of Things (IoT) framework is proposed to effectively communicate the daily living data and exercise routine of surgery patients and patients with excessive weight. The proposed IoT framework aims to enable seamless communications from wearable sensors and body networks to the cloud to create an accurate profile of the patients. It also attempts to automate the data analysis and represent the facts about a patient. The IoT framework proposes a co-channel interference avoidance mechanism and the ability to communicate higher activity data with minimal impact on the bandwidth requirements of the system. The proposed IoT framework also benefits from machine learning based activity classification systems, with relatively high accuracy, which allow the communicated data to be translated into meaningful information.
AB - Obesity poses several challenges to healthcare and the well-being of individuals. It can be linked to several life-threatening diseases. Surgery is a viable option in some instances to reduce obesity-related risks and enable weight loss. State-of-the-art technologies have the potential for long-term benefits in post-surgery living. In this work, an Internet of Things (IoT) framework is proposed to effectively communicate the daily living data and exercise routine of surgery patients and patients with excessive weight. The proposed IoT framework aims to enable seamless communications from wearable sensors and body networks to the cloud to create an accurate profile of the patients. It also attempts to automate the data analysis and represent the facts about a patient. The IoT framework proposes a co-channel interference avoidance mechanism and the ability to communicate higher activity data with minimal impact on the bandwidth requirements of the system. The proposed IoT framework also benefits from machine learning based activity classification systems, with relatively high accuracy, which allow the communicated data to be translated into meaningful information.
UR - http://dx.doi.org/10.32604/cmc.2023.035686
U2 - 10.32604/cmc.2023.035686
DO - 10.32604/cmc.2023.035686
M3 - Article
VL - 75
SP - 3833
EP - 3848
JO - Computers, Materials & Continua
JF - Computers, Materials & Continua
SN - 1546-2218
IS - 2
ER -