  <?xml version="1.0"?>
<journal>
 <journal_metadata>
  <full_title>Journal of Intelligent Systems and Internet of Things</full_title>
  <abbrev_title>JISIoT</abbrev_title>
  <issn media_type="print">2690-6791</issn>
  <issn media_type="electronic">2769-786X</issn>
  <doi_data>
   <doi>10.54216/JISIoT</doi>
   <resource>https://www.americaspg.com/journals/show/2920</resource>
  </doi_data>
 </journal_metadata>
 <journal_issue>
  <publication_date media_type="print">
   <year>2019</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2019</year>
  </publication_date>
 </journal_issue>
 <journal_article publication_type="full_text">
  <titles>
   <title>Intelligent Integration of Wearable Sensors and  Artificial Intelligence for  Real-time Athletic Performance Enhancement</title>
  </titles>
  <contributors>
   <organization sequence="first" contributor_role="author">Department of Computer Science and Engineering, IMS Engineering College, Ghaziabad, UP, India</organization>
   <person_name sequence="first" contributor_role="author">
    <given_name>Aditi</given_name>
    <surname>Aditi</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">1RDG Info. Services, Lucknow, U.P., India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Ram Kinkar</given_name>
    <surname>Pandey</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Computer Science and Engineering, PSIT,Kanpur, Uttar Pradesh India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Gaurav Kumar</given_name>
    <surname>Srivastava</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Computer Science and Engineering, IMS Engineering College, Ghaziabad, UP, India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Nishant</given_name>
    <surname>Anand</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of CSIT, KL University, Vaddeswaram, Guntur</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Kunchanapalli Rama</given_name>
    <surname>Krishna</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Computer Science and Engineering, Maharshi University of Information Technology, Lucknow</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Prateek</given_name>
    <surname>Singhal</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Computer Science and Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Aditi</given_name>
    <surname>Sharma</surname>
   </person_name>
  </contributors>
  <jats:abstract xml:lang="en">
   <jats:p>The amalgamation of wearable sensor technologies and artificial intelligence (AI) presents a transformative paradigm for optimising athletic performance in real time. This paper explores the integration of cutting-edge sensors - including bioimpedance sensors, accelerometers, and gyroscopes - with advanced AI algorithms such as machine learning and decision support systems. By capturing diverse physiological, biomechanical, and environmental data, the proposed framework aims to offer personalized, actionable insights for athletes. This research synthesizes the current landscape of wearable sensor technology in sports and highlights the evolving role of AI in interpreting data for enhancing athletic performance. It delineates an innovative framework designed for real-time analysis, personalized feedback, and training optimization. The seamless interaction between sensors and AI models empowers athletes and coaches to make informed decisions, optimizing training regimens and minimizing injury risks. The paper discusses the practical implications, challenges, and ethical considerations associated with this integration, emphasizing its potential benefits in diverse sports disciplines. Results from real-world trials underscore the efficacy of the proposed framework in providing dynamic guidance to athletes, thereby augmenting their performance through tailored interventions.</jats:p>
  </jats:abstract>
  <publication_date media_type="print">
   <year>2024</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2024</year>
  </publication_date>
  <pages>
   <first_page>60</first_page>
   <last_page>77</last_page>
  </pages>
  <doi_data>
   <doi>10.54216/JISIoT.130205</doi>
   <resource>https://www.americaspg.com/articleinfo/18/show/2920</resource>
  </doi_data>
 </journal_article>
</journal>
