Skip to main content
Contribution to Book
PRO-Fit: Exercise with friends
Proceedings of the 2016 IEEE/ACM Intl. Conf. on Advances in Social Networks Analysis and Mining (2016)
  • Saumil Dharia, San Jose State University
  • Vijesh Jain, San Jose State University
  • Jvalant Patel, San Jose State University
  • Jainikkumar Vora, San Jose State University
  • Rizen Yamauchi, San Jose State University
  • Magdalini Eirinaki, San Jose State University
  • Iraklis Varlamis, University of Athens
The advancements in wearable technology, where embedded accelerometers, gyroscopes and other sensors enable the users to actively monitor their activity have made it easier for individuals to pursue a healthy lifestyle. However, most of the existing applications expect continuous commitment from the end users, who need to proactively interact with the application in order to connect with friends and attain their goals. These applications fail to engage and motivate users who have busy schedules, or are not as committed and self-motivated. In this work, we present PRO-Fit, a personalized fitness assistant application that employs machine learning and recommendation algorithms in order to smartly track and identify user's activity, synchronizes with the user's calendar, recommends personalized workout sessions based on the user's preferences, fitness goals, and availability. Moreover, PRO-Fit integrates with the user's social network and recommends “fitness buddies” with similar preferences and availability.
  • personalized assistant,
  • wearable technology,
  • activity tracking,
  • classification,
  • recommendations
Publication Date
Publisher Statement
SJSU users: use the following link to login and access the article via SJSU databases.
Citation Information
Saumil Dharia, Vijesh Jain, Jvalant Patel, Jainikkumar Vora, et al.. "PRO-Fit: Exercise with friends" San Francisco, CA, USAProceedings of the 2016 IEEE/ACM Intl. Conf. on Advances in Social Networks Analysis and Mining (2016)
Available at: