返回
BeeOpen-An Open Data Sharing Ecosystem for Apiculture
DOI:10.3390/agriculture14030470.png)
摘要
En 中文
The digital transformation of apiculture initially encompasses Internet of Things (IoT) systems, incorporating sensor technologies to capture and transmit bee-centric data. Subsequently, data analysis assumes a vital role by establishing correlations between the collected data and the biological conditions of beehives, often leveraging artificial intelligence (AI) approaches. The field of precision bee monitoring has witnessed a surge in the collection of large volumes of diverse data, ranging from the hive weight and temperature to health status, queen bee presence, pests, and overall hive activity. Further, these datasets' heterogeneous nature and lack of standardization present challenges in applying machine learning techniques directly to extract valuable insights. To address this issue, the envisioned ecosystem serves as an open and collaborative information platform, facilitating the exchange and utilization of bee monitoring datasets. The data storage architecture can process a large variety of data at high frequency, e.g., images, videos, audio, and time series data. The platform serves as a repository, providing crucial information about the condition of beehives, health assessments, pest attacks, swarming patterns, and other relevant data. Notably, this information portal is managed through a citizen scientist initiative. By consolidating data from various sources, including beekeepers, researchers, and monitoring systems, the platform offers a holistic view of the bee population's status in any given area.
Keyword:
precision agriculture
data marketplace
apiculture
AI
期刊
IF:
3.6
论文数:
1.3W
被引数:
2.8W
机构
引用论文
Acoustic and vibration monitoring of honeybee colonies for beekeeping-relevant aspects of presence of queen bee and swarming蜂群的声学和振动监测与蜂王和蜂群的存在有关的养蜂相关方面
Errors in Allen's Review of Social Evolution and Inclusive Fitness Theory: An Introduction
BioScience
IF0
Can Distributed Ledgers Help to Overcome the Need of Labeled Data for Agricultural Machine Tasks?
PLANT PHENOMICS
IF6.4

