Decision support system for temperature monitoring in beehives
Autor: | Sinisa Randjic, Sladjana Djurasevic, Uros Pesovic, Dušan Marković |
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Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
0301 basic medicine
Decision support system Computer science complex event processing beehive Complex event processing Computer security computer.software_genre lcsh:Agriculture 03 medical and health sciences Wireless Beehive Event (computing) business.industry lcsh:S 04 agricultural and veterinary sciences General Medicine Honey bee internet of things 030104 developmental biology machine learning 8. Economic growth 040103 agronomy & agriculture 0401 agriculture forestry and fisheries The Internet Whole food business computer |
Zdroj: | Acta agriculturae Serbica (2016) 21(42):135-144 Acta Agriculturae Serbica, Vol 21, Iss 42, Pp 135-144 (2016) |
ISSN: | 0354-9542 |
Popis: | European honeybee colonies are the most important pollinator insects and source of honey and other useful products. Honeybee colonies today face new diseases and pests as well as pollution which threaten their survival and endanger whole food production which relies on honey bee pollination. Internet of Things (IoT) technology enables integration of wireless sensors inside beehives to enable remote monitoring of various beehive parameters from remote location using Internet. Detection of certain critical events in beehive is hard to be explicitly program due to complex dependence between multiple input parameters. Machine learning algorithms give computers the ability to learn to detect these events without being explicitly programmed. Detection of these event from streams of data collected from IoT sensors is possible using Complex Event Processing (CEP) which applies machine induced knowledge do detect and warn beekeepers about certain events in beehive. |
Databáze: | OpenAIRE |
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