Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/14688
DC Field | Value | Language |
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dc.contributor.author | Stevanoska, Sintija | en_US |
dc.contributor.author | Davcev, Danco | en_US |
dc.contributor.author | Jovanovska, Elena M. | en_US |
dc.contributor.author | Mitreski, Kosta | en_US |
dc.date.accessioned | 2021-09-14T12:28:38Z | - |
dc.date.available | 2021-09-14T12:28:38Z | - |
dc.date.issued | 2020-11-16 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/14688 | - |
dc.description.abstract | The Internet of Things (IoT) is a relatively new concept with a number of potential uses in agriculture. In this work we propose a system based on IoT for early detection of wine moth infestation, as well as monitoring the number of pests at a particular part of the season. This leads to optimization of the use of pesticides in the vineyards. The wine moths are caught using a pheromone trap with a camera attached to it. The camera is used for real-time monitoring of the trap. The output of the program is an image that indicates how many pests are currently caught on the trap. We have implemented a prototype in one of the vineyards in a Macedonian winery near Skopje City. | en_US |
dc.language.iso | en | en_US |
dc.publisher | ACM | en_US |
dc.relation | Податочна анализа и предикција на болести во агрокултура-УКИМ-ФИНКИ | en_US |
dc.relation.ispartofseries | ;17 | - |
dc.subject | Internet of Things (IoT), Real-time monitoring system, Pests, Pesticides, Image Recognition, Vineyards | en_US |
dc.title | IoT--Based System for Real-time Monitoring and Insect Detection in Vineyards | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | Proceedings of the 18th ACM Symposium on Mobility Management and Wireless Access | en_US |
dc.identifier.doi | 10.1145/3416012.3424634 | - |
dc.identifier.url | https://dl.acm.org/doi/pdf/10.1145/3416012.3424634 | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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File | Description | Size | Format | |
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wac17s-ACM_2020.pdf | 364.31 kB | Adobe PDF | View/Open |
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