Name
Abstract | ||
|---|---|---|
In recent years, damage to rural areas by vermin such as deer, wild boars or monkeys has increased in both frequency and severity. This problem is expected to be counteracted by wireless sensor networks constructed from multiple sensor nodes with wireless communication devices. These systems reduce the damage by detecting vermin and repelling them by signals such as sounds and light. However, owing to their fixed monitoring cameras, general monitoring systems cannot always cope with plant growth and other obscurations that decrease the monitored area. This paper proposes a ropeway-type vermin detection system that moves the monitoring cameras on ropes, and a method that minimizes the number of required ropes in the expected monitoring scenario. For efficient monitoring with as few cameras as possible, the method groups several target areas into one by a clustering procedure. The grouped area can then be monitored from a single position. Subsequently, our algorithm finds the most efficient rope deployment that completely monitors the grouped areas. In simulations, the proposed method monitored all target areas with 26% fewer monitoring cameras than a general clustering method (k-means clustering). |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/AINA.2018.00060 | 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) |
Keywords | Field | DocType |
vermin monitoring,sensor network,sensing | Software deployment,Wireless,Monitoring system,Computer science,Plant growth,Real-time computing,Vermin,Cluster analysis,Wireless sensor network,Rope,Distributed computing | Conference |
ISSN | ISBN | Citations |
1550-445X | 978-1-5386-2196-7 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kodai Ogura | 1 | 0 | 0.68 |
| Kei Nihonyanagi | 2 | 0 | 0.34 |
| Ryo Katsuma | 3 | 20 | 5.53 |