Paper Info
Title
Learning from sensor network data
Abstract
Within the PermaSense project, two wireless sensor networks have been deployed for a long-term operation in the Swiss Alps. For enabling state-of-the-art permafrost research based on the collected data, highest possible data quality and yield have to be ensured. But, the operation of wireless sensors networks remains a hard research problem. Firstly, deployed wireless sensors networks are subject to continuous changes. Second, there are scenarios that can only be tested in the field as the capabilities of testbeds are too limited. Basically, it is not possible to test for many months before deploying in the field. In this poster, we present an analysis of our data that has been collected over nine months. In addition to describing our system design and methods, we also share our experiences from discovered severe incidences.
Year
DOI
Venue
2009
10.1145/1644038.1644113
SenSys
Keywords
Field
DocType
sensor network data,swiss alps,state-of-the-art permafrost research,severe incidence,continuous change,wireless sensor network,permasense project,wireless sensors network,hard research problem,long-term operation,highest possible data quality,environmental monitoring,data analysis,sensor network,wireless sensor networks,data quality,long term,system design
Wireless network,Key distribution in wireless sensor networks,Data quality,Wireless site survey,Computer science,Computer network,Real-time computing,Wireless WAN,Wi-Fi array,Mobile wireless sensor network,Wireless sensor network
Conference
Citations 
PageRank 
References 
9
0.56
4
Authors
5
Name
Order
Citations
PageRank
Matthias Keller1766.07
Jan Beutel290.56
Andreas Meier318313.55
Roman Lim420018.35
Lothar Thiele514025957.82