Abstract
A semantic sensor network describes the physical world using the metadata obtained from a sensor network. In this paper, we present our design and implementation of MeT, a real world oriented metadata management system for semantic sensor networks. MeT generates metadata either statically based on the application semantics, or dynamically using inference rules. It then constructs relationships between physical objects through these metadata. The sensor devices in MeT include RFID tags, position sensors and Motes. The users can query MeT about physical objects through either a Graphic User Interace, or Robovie, a communication robot. We give several concrete examples of querying physical objects in MeT to demonstrate the functionality of our system.
| Original language | English |
|---|---|
| Title of host publication | 3rd International Workshop on Data Management in Sensor Networks, DMSN'06, in Conjunction with Very Large Data Bases, VLDB 2006 |
| Pages | 13-18 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2006 |
| Event | 3rd International Workshop on Data Management in Sensor Networks, DMSN'06, in Conjunction with Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of Duration: 2006 Sep 11 → 2006 Sep 11 |
Other
| Other | 3rd International Workshop on Data Management in Sensor Networks, DMSN'06, in Conjunction with Very Large Data Bases, VLDB 2006 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 06/9/11 → 06/9/11 |
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ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
Cite this
MeT : A real world oriented metadata management system for semantic sensor networks. / Kawashima, Hideyuki; Hirota, Yutaka; Satake, Satoru; Imai, Michita.
3rd International Workshop on Data Management in Sensor Networks, DMSN'06, in Conjunction with Very Large Data Bases, VLDB 2006. 2006. p. 13-18.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - MeT
T2 - A real world oriented metadata management system for semantic sensor networks
AU - Kawashima, Hideyuki
AU - Hirota, Yutaka
AU - Satake, Satoru
AU - Imai, Michita
PY - 2006
Y1 - 2006
N2 - A semantic sensor network describes the physical world using the metadata obtained from a sensor network. In this paper, we present our design and implementation of MeT, a real world oriented metadata management system for semantic sensor networks. MeT generates metadata either statically based on the application semantics, or dynamically using inference rules. It then constructs relationships between physical objects through these metadata. The sensor devices in MeT include RFID tags, position sensors and Motes. The users can query MeT about physical objects through either a Graphic User Interace, or Robovie, a communication robot. We give several concrete examples of querying physical objects in MeT to demonstrate the functionality of our system.
AB - A semantic sensor network describes the physical world using the metadata obtained from a sensor network. In this paper, we present our design and implementation of MeT, a real world oriented metadata management system for semantic sensor networks. MeT generates metadata either statically based on the application semantics, or dynamically using inference rules. It then constructs relationships between physical objects through these metadata. The sensor devices in MeT include RFID tags, position sensors and Motes. The users can query MeT about physical objects through either a Graphic User Interace, or Robovie, a communication robot. We give several concrete examples of querying physical objects in MeT to demonstrate the functionality of our system.
UR - http://www.scopus.com/inward/record.url?scp=60649117770&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=60649117770&partnerID=8YFLogxK
U2 - 10.1145/1315903.1315907
DO - 10.1145/1315903.1315907
M3 - Conference contribution
SP - 13
EP - 18
BT - 3rd International Workshop on Data Management in Sensor Networks, DMSN'06, in Conjunction with Very Large Data Bases, VLDB 2006
ER -