An Efficient Data Gathering System for Home Medical Treatment

Autor: Yi-Lun Wen, Jen-Chu Liu, Kuo-Yu Chuang
Rok vydání: 2012
Předmět:
Zdroj: ICGEC
DOI: 10.1109/icgec.2012.44
Popis: With the widely used of wellness self-management devices, more and more services provide people up-to-date wellness information such as blood pressure, SpO2, rate of heartbeat, etc. How to gather these data more efficiently is an important issue. Moreover, these data may be combined with the information of geographic location. the data gathering system need to deal with GIS-based information. We had proposed an innovated sensor observation service with web-based and GIS-based architecture, which is named WSN Application Service Platform (WASP) [25]. Then, we proposed a flexible SWE-based Data Observation and Event Notification Framework on Social Networks for smart home applications [26] based on WASP. All sensors and devices provide their location information to data center and form a community. in this paper, we continue the frameworks that have proposed in [25] and [26]. We design an efficient platform to gather the wellness data from devices through wireless networks automatically. We also proposed an scheme can saving more power and bandwidth. Moreover, these wellness information can be shown immediately on social networks in specified groups. the proposed data gathering system is helpful and efficient for home medical treatment.
Databáze: OpenAIRE