Paper Info
Title
A Remote Monitoring System of IDC Room Based on ZigBee Wireless Sensor Networks
Abstract
This paper introduces an intelligent remote monitor system based on ZigBee sensor networks for IDC (Internet Data Center) room. The system consists of two parts: three types of ZigBee modules and the server module. The three types of ZigBee modules contain first-cluster node, second-cluster node and sensor end-node. The system can control remote IDC room based on the connection of the ZigBee protocols and traditional Internet networks. The data collected by the sensor end-nodes in the IDC room are transmitted through ZigBee networks to the server that can communicate with the remote monitor PC with Internet connection. The functions the system implements include data collection, analysis, management, storage, automatic alarm, display and control. By monitoring the IDC room unmanned, the proposed system reduces the energy consumption and the number of management staff, at the same time, provides reliable and robust monitoring, then control the equipments in real-time. Consequently, it ensures the safety and stable operation for the IDC room.
Year
DOI
Venue
2009
10.1109/DASC.2009.143
DASC
Keywords
Field
DocType
zigbee wireless sensor networks,internet data center,remote idc room,protocols,remote monitor,zigbee network,intelligent remote monitor system,zigbee modules,monitoring,equipment control,internet networks,zigbee,remote monitoring system,personal area networks,zigbee protocol,idc room,sensor end-node,intelligent remote monitoring system,zigbee sensor network,second-cluster node,server module,monitoring reliability,internet,first-cluster node,proposed system,zigbee protocols,wireless sensor networks,internet connection,radiotelemetry,remote monitor pc,data collection,zigbee module,real time,sensor network,data center,remote monitoring,humidity,servers,wireless communication,wireless sensor network
Wireless,ALARM,Computer science,Server,Internet access,Wireless sensor network,Energy consumption,Embedded system,NeuRFon,The Internet
Conference
ISBN
Citations 
PageRank 
978-1-4244-5421-1
0
0.34
References 
Authors
2
6
Name
Order
Citations
PageRank
Shuchao Ma100.68
Zhu Ming266.18
Lei Wang343364.21
Shu Lei42927216.78
Suran Li5162.20
Shu-Min Huang6101.21