V. Komašilovs, A. Zacepins, A. Kviesis, S. Fiedler, S. Kirchner
{"title":"Modular sensory hardware and data processing solution for implementation of the precision beekeeping","authors":"V. Komašilovs, A. Zacepins, A. Kviesis, S. Fiedler, S. Kirchner","doi":"10.15159/AR.19.038","DOIUrl":null,"url":null,"abstract":"For successful implementation of the Precision Apiculture (Precision Beekeeping) approach, immense amount of bee colony data collection and processing using various hardware and software solutions is needed. This paper presents standalone wireless hardware system for bee colony main parameters monitoring (temperature, weight and sound). Monitoring system is based on Raspberry Pi 3 computer with connected sensors. Power supply is granted by the solar panel for reliable operation in places without constant source for power. For convenient data management cloud based data warehouse (DW) is proposed and developed for ease data storage and analysis. Proposed data warehouse is scalable and extendable and can be used for variety of other ready hardware solutions, using variety of data-in/data-out interfaces. The core of the data warehouse is designed to provide data processing flexibility and versatility, whereas data flow within the core is organized between data vaults in a controllable and reliable way. Our paper presents an approach for linking together hardware for bee colony real-time monitoring with cloud software for data processing and visualisation. Integrating specific algorithms and models to the system will help the beekeepers to remotely identify different states of their colonies, like swarming, brood rearing, death of the colony etc. and inform the beekeepers to make appropriate decisions/actions. This research work is carried out within the SAMS project, which is funded by the European Union within the H2020-ICT-39-2016-2017 call. To find out more visit the project website https://sams-project.eu/.","PeriodicalId":7924,"journal":{"name":"Agronomy research","volume":"50 1","pages":"509-517"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agronomy research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15159/AR.19.038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 10
Abstract
For successful implementation of the Precision Apiculture (Precision Beekeeping) approach, immense amount of bee colony data collection and processing using various hardware and software solutions is needed. This paper presents standalone wireless hardware system for bee colony main parameters monitoring (temperature, weight and sound). Monitoring system is based on Raspberry Pi 3 computer with connected sensors. Power supply is granted by the solar panel for reliable operation in places without constant source for power. For convenient data management cloud based data warehouse (DW) is proposed and developed for ease data storage and analysis. Proposed data warehouse is scalable and extendable and can be used for variety of other ready hardware solutions, using variety of data-in/data-out interfaces. The core of the data warehouse is designed to provide data processing flexibility and versatility, whereas data flow within the core is organized between data vaults in a controllable and reliable way. Our paper presents an approach for linking together hardware for bee colony real-time monitoring with cloud software for data processing and visualisation. Integrating specific algorithms and models to the system will help the beekeepers to remotely identify different states of their colonies, like swarming, brood rearing, death of the colony etc. and inform the beekeepers to make appropriate decisions/actions. This research work is carried out within the SAMS project, which is funded by the European Union within the H2020-ICT-39-2016-2017 call. To find out more visit the project website https://sams-project.eu/.
Agronomy researchAgricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
2.10
自引率
0.00%
发文量
0
审稿时长
7 weeks
期刊介绍:
Agronomy Research is a peer-reviewed international Journal intended for publication of broad-spectrum original articles, reviews and short communications on actual problems of modern biosystems engineering including crop and animal science, genetics, economics, farm- and production engineering, environmental aspects, agro-ecology, renewable energy and bioenergy etc. in the temperate regions of the world.