Name
Abstract | ||
|---|---|---|
Water quality is vital to human life and economy. However, one sixth of the world's population suffers from lack of safe drinking and domestic water. Aiming to improve the capability of predicting and responding to river pollution disasters, this project collaborated with local offices of Chinese National Bureau of Water Resource to explore new solutions to coping with the ever-growing threat of river water pollution. We presented a distributed data analysis algorithm, Infinitesimal Dividing and Analysis, to efficiently locate pollution sources with data gathered from a ubiquitous wired/wireless sensor network. We elaborate on a 驴-calculus based paradigm to enhance collaboration and interaction among individual monitoring stations. Based on these two enabling technologies, we applied our framework to water quality monitoring at two carefully chosen sites in China. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s10586-009-0105-z | Cluster Computing |
Keywords | Field | DocType |
Water monitoring | Population,Environmental resource management,Computer science,China,Pollution,River pollution,River water,Wireless sensor network,Water quality,Distributed computing | Journal |
Volume | Issue | ISSN |
13 | 2 | 1386-7857 |
Citations | PageRank | References |
2 | 0.55 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Hu | 1 | 778 | 107.21 |
| Bo Hu | 2 | 161 | 27.21 |
| JiZheng Wan | 3 | 29 | 6.40 |
| Fang Zheng | 4 | 28 | 6.35 |
| Li Liu | 5 | 634 | 47.50 |