Artificial Intelligence and Internet of Things Enabled Intelligent Framework for Active and Healthy Living

Saeed Ali Alsareii, Mohsin Raza, Abdulrahman Manaa Alamri, Mansour Yousef AlAsmari, Muhammad Irfan, Hasan Raza, Muhammad Awais

Research output: Contribution to journalArticle (journal)peer-review

1 Citation (Scopus)
63 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)3833-3848
JournalComputers, Materials and Continua
Volume75
Issue number2
Early online date31 Mar 2023
DOIs
Publication statusPublished - 31 Mar 2023

Keywords

  • physical activity classification
  • activity monitoring
  • Artificial intelligence
  • healthcare
  • obesity
  • Internet of Things
  • machine learning

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