@inproceedings{c224dca520274d64ae28b42e16e70c0b,
title = "Analytics Using Activity Trackers in the Field of Education",
abstract = "Today activity trackers are used as a major tool for tracking, monitoring, and quantifying health aspects in the form of physiological data. Such wearable trackers can be efficiently utilised in other fields apart from healthcare. This paper shows how an activity tracker can be used to create a real time application for monitoring the activity of a student by parents as well as school/college authority thereby deducing whether the student is actually present in the class or not. Various activity trackers provide an Application Programming Interface (API) of their own to allow a third party application to access user's data from their server. Other data sets like surrounding noise level and location of the student have been used in combination with the step count of the student to produce real time inferences. This research paper gives an insight of how activity trackers can be utilised in the field of education thereby opening vast opportunities of data analysis and prediction in this field.",
keywords = "activity trackers, fuzzy neural network, oAuth, predictive analysis, real time activity monitoring, step count",
author = "Ankit Sharma and Udita Prajapati and Vivekanandan Kumar and Kinshuk",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 7th IEEE International Conference on Technology for Education, T4E 2015 ; Conference date: 10-12-2015 Through 12-12-2015",
year = "2016",
month = jan,
day = "29",
doi = "10.1109/T4E.2015.7",
language = "English",
series = "Proceedings - IEEE 7th International Conference on Technology for Education, T4E 2015",
pages = "31--34",
editor = "Sridhar Iyer and Kinshuk and Venkatesh Choppella",
booktitle = "Proceedings - IEEE 7th International Conference on Technology for Education, T4E 2015",
}