Name
Abstract | ||
|---|---|---|
Environmental monitoring applications are designed for supplying derived and often integrated information by tracking and analyzing phenomena. To determine the condition of a target place, they employ a geosensor network to get the heterogeneous sensor data. To effectively handle a large volume of sensor data, applications need a data abstraction model, which supports the summarized data representation by encapsulating raw data. For faster data processing to answer a user's queries with representative attributes of an abstracted model, we propose such a data abstraction model, the Layered Slopes in Grid for Sensor Data Abstraction (LSGSA), which is based on the SGSA. In a single grid-based layer for each sensor type, collected data is represented by slope directional vectors in two layered slopes, such as height and surface. To answer a user query in a central monitoring server, LSGSA is used to reduce the time needed to extract event features from raw sensor data as a preprocessing step for interpreting the observed data. The extracted features are used to understand the current data trends and the progress of a detected phenomenon without accessing raw sensor data. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.3390/s121217074 | SENSORS |
Keywords | Field | DocType |
sensor data abstraction,sensor data representation,geosensor network,slope grid,GIS,surface model | Data mining,Data processing,External Data Representation,Abstraction,Computer science,Raw data,Preprocessor,Environmental monitoring,Grid | Journal |
Volume | Issue | ISSN |
12 | 12 | 1424-8220 |
Citations | PageRank | References |
1 | 0.63 | 12 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongmi Lee | 1 | 1 | 0.96 |
| Young Jin Jung | 2 | 1 | 0.63 |
| Kwang Woo Nam | 3 | 5 | 1.10 |
| Silvia Nittel | 4 | 43 | 2.64 |
| Kate Beard | 5 | 5 | 1.44 |
| Keun Ho Ryu | 6 | 81 | 4.39 |