Computer Science ›› 2014, Vol. 41 ›› Issue (10): 57-61.doi: 10.11896/j.issn.1002-137X.2014.10.013

Previous Articles     Next Articles

Scudware Mobile:Mobile Middleware for Collaboration of Data and Services between Wearable Devices

DING Yang,LI Shi-jian,YE Zhi-qiang and PAN Gang   

  • Online:2018-11-14 Published:2018-11-14

Abstract: With the developing of ubiquitous computing,the integration of software and hardware has become an important trend of personal consumer electronics field,and wearable devices are becoming the current research hotspot of academic and industry.Most of these devices have certain capabilities of sensing,computing and service.But now interface of wearable devices is different from each other,and the capability of collaboration is weak,which causes the waste of sensing and computing capabilities,also can not provide rich services.To solve this problem,this paper proposed a mobile middleware for collaboration of data and services between wearable devices-Scudware Mobile.Scudware Mobile aggregates data and services of wearable devices,and provides a unified interface of accessing to the application layer.Also we introduced collaboration mechanism into Scudware Mobile.Using Scudware Mobile,we implemented two applications:portal of personal data and shaking e-card.

Key words: Scudware mobile,Collaboration of data and services,Wearable device,Smart mobile

[1] Xively.https://xively.com/
[2] Funf.http://funf.org/
[3] Wu Zhao-hui,Wu Qing,Cheng Hong,et al.ScudWare:A semantic and adaptive middleware platform for smart vehicle space[J].IEEE Transactions on Intelligent Transportation Systems,2007,8(1):121-132
[4] Wu Zhao-hui,Pan Gang.Smartshadow:Models and Methods for Pervasive Computing[M].Springer,2013
[5] Kukkonen J,Lagerspetz E,Nurmi P,et al.Betelgeuse:A platform for gathering and processing situational data[J].IEEE Pervasive Computing,2009,8(2):49-56
[6] Beach A,Gartrell M,Xing X,et al.Fusing mobile,sensor,and social data to fully enable context-aware computing[C]∥Proceedings of the Eleventh Workshop on mobile Computing Systems & Applications.ACM,2010:60-65
[7] Brunette W,Sodt R,Chaudhri R,et al.Open data kit sensors:a sensor integration framework for android at the application-level[C]∥Proceedings of the 10th international conference on mobile systems,applications,and services.ACM,2012:351-364
[8] Atzmueller M,Hilgenberg K.Towards capturing social interactions with SDCF:an extensible framework for mobile sensing and ubiquitous data collection[C]∥Proceedings of the 4th International Workshop on Modeling Social Media.ACM,2013:6
[9] Open.Sen.Se.http://open.sen.se/
[10] Wang Yi,Lin Jia-liu,Annavaram M,et al.A framework of energy efficient mobile sensing for automatic user state recognition[C]∥Proceedings of the 7th International Conference on Mobile Systems,Applications,and Services.ACM,2009:179-192
[11] Sae-Tang A,Catasta M,McDowell L K,et al.Semantic place prediction using mobile data[C]∥Mobile Data Challenge Workshop.June 2012:18-19
[12] Chon Y,Lane N D,Li Fan,et al.Automatically characterizing places with opportunistic crowdsensing using smartphones[C] ∥Proceedings of the 2012 ACM Conference on Ubiquitous Computing.ACM,2012:481-490
[13] Wu Jia-hui,Pan Gang,Zhang Da-qing,et al.Gesture recognition with a 3-d accelerometer[M]∥Ubiquitous intelligence and computing.Springer Berlin Heidelberg,2009:25-38
[14] Pan Gang,Zhang Li,Wu Zhao-hui,et al.Pervasive Service Bus:Smart SOA Infrastructure for Ambient Intelligence[J].IEEE Intelligent Systems,2012,PP(99)

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!