TY - GEN
T1 - MODEL-DRIVEN PROTOTYPING SUPPORT FOR PERVASIVE HEALTH CARE APPLICATIONS
AU - Kurschl, Werner
AU - Mitsch, Stefan
AU - Schönböck, Johannes
PY - 2008
Y1 - 2008
N2 - Pervasive health care systems help to improve elderly and needy persons’ habitability by assisting them in living autonomously,and letting them participate in social communities and family life. The data gained from many wireless sensors running on different sensor platforms is usually further processed and interpreted by machine learning and
pattern recognition components. The complexity of these systems stems from different types of environmental and vital parameters, different sampling rates, heterogeneous sensor platforms, unreliable network connections, as well as different programming languages that must be tailored to the use-case and the application environment. Therefore,
the development of such applications often requires a lot of prototyping work, because significant data must be gained from individuals and from the environment through experiments and machine learning components must be trained for specific situations. In this paper we present a model driven prototyping approach for the development of pervasive health care applications. We provide tools like graphical
editors and generators to simplify the development of
pervasive health application prototypes that typically span multiple platforms.
AB - Pervasive health care systems help to improve elderly and needy persons’ habitability by assisting them in living autonomously,and letting them participate in social communities and family life. The data gained from many wireless sensors running on different sensor platforms is usually further processed and interpreted by machine learning and
pattern recognition components. The complexity of these systems stems from different types of environmental and vital parameters, different sampling rates, heterogeneous sensor platforms, unreliable network connections, as well as different programming languages that must be tailored to the use-case and the application environment. Therefore,
the development of such applications often requires a lot of prototyping work, because significant data must be gained from individuals and from the environment through experiments and machine learning components must be trained for specific situations. In this paper we present a model driven prototyping approach for the development of pervasive health care applications. We provide tools like graphical
editors and generators to simplify the development of
pervasive health application prototypes that typically span multiple platforms.
KW - MDSD
KW - Model transformation
KW - Pervasive health care
KW - Prototyping
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=74549167762&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9780889867765
T3 - Proceedings of the 9th IASTED International Conference on Software Engineering and Applications, SEA 2008
SP - 118
EP - 123
BT - Proceedings of the 9th IASTED International Conference on Software Engineering and Applications, SEA 2008
PB - ÖGB Verlag
T2 - 9th International Conference on Software Engineering and Application
Y2 - 16 November 2008 through 18 November 2008
ER -