A Wearable Device-Based Personalized Big Data Analysis Model

• Published in: Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services pp. 236 - 242
• Main Authors: Hussain, Shujaat, Kang, Byeong Ho, Lee, Sungyoung
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 2014
• Series: Lecture Notes in Computer Science
• Subjects: Android Application; MapReduce Programming; Real Time Manner; Wearable Computing; Wearable Device
• ISBN: 9783319131016; 331913101X
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-13102-3_39

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 different applications in the future.