Wearable devices and the data generated by them gives a unique opportunity to understand the user behavior and predict future needs due to its personal nature. In coming years this data will grow exponentially due to huge popularity of wearable devices. Analysis will become a challenge with the personal data explosion and also to maintain a updated knowledge base. This calls for big data analysis model for wearable devices.We propose a big data analysis model which will update the knowledge base and give users a personalized recommendations based on the analysis of the data. We have designed a personalized adaptive analysis technique for data handling and transformation. This technique also responds to information utilization APIs in a real time manner. We are using mapreduce as our big data technology and ensure that data can be used for long term analysis for di fferent applications in the future.
History
Publication title
Lecture Notes in Computer Science 8867: Proceedings of the 8th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2014)
Volume
8867
Editors
R Hervas, S Lee, C Nugent, J Bravo
Pagination
236-242
ISSN
0302-9743
Department/School
School of Information and Communication Technology
Publisher
Springer International Publishing
Place of publication
New York, USA
Event title
8th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2014)
Event Venue
Belfast, UK
Date of Event (Start Date)
2014-12-02
Date of Event (End Date)
2014-12-05
Rights statement
Copyright 2014 Springer International Publishing Switzerland