Predicton With Smart Phones
Gowtham Mamidisetti1, B.Venkatesh2
1Gowtham.Mamidisetti is an assistant Professor in Information Technology at Shri Vishnu Engineering College for Women, Bhimavaram, Andhra Pradesh, India.
2B.Venkatesh is an assistant Professor in Information Technology at Shri Vishnu Engineering College for Women, Bhimavaram, Andhra Pradesh, India.
Manuscript received on October 20, 2013. | Revised Manuscript received on November 01, 2013. | Manuscript published on November 05, 2013. | PP: 174-176 | Volume-3 Issue-5, November 2013. | Retrieval Number: E1956113513/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper predicts two aspects of human behavior using smart phones as sensing devices. This paper introduces a method for predicting where users will go and which application they will use next by exploiting the rich contextual information from smart phone sensors. Our first goal is to understand which smart phone sensor data types are important for the two prediction tasks. Secondly, we aim at extracting user independent behavioral patterns and study how user independent behavior models can improve the predictive performance.
Keywords: Smart phone data, human behavior, mobility prediction, app usage prediction.