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Journal Article IoT-Based Strawberry Disease Prediction System for Smart Farming
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Authors
Sehan Kim, Meonghun Lee, Changsun Shin
Issue Date
2018-11
Citation
Sensors, v.18, no.11, pp.1-17
ISSN
1424-8220
Publisher
MDPI AG
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.3390/s18114051
Abstract
Crop diseases cannot be accurately predicted by merely analyzing individual disease causes. Only through construction of a comprehensive analysis system can users be provided with predictions of highly probable diseases. In this study, cloud-based technology capable of handling the collection, analysis, and prediction of agricultural environment information in one common platform was developed. The proposed Farm as a Service (FaaS) integrated system supports high-level application services by operating and monitoring farms as well as managing associated devices, data, and models. This system registers, connects, and manages Internet of Things (IoT) devices and analyzes environmental and growth information. In addition, the IoT-Hub network model was constructed in this study. This model supports efficient data transfer for each IoT device as well as communication for non-standard products, and exhibits high communication reliability even in poor communication environments. Thus, IoT-Hub ensures the stability of technology specialized for agricultural environments. The integrated agriculture-specialized FaaS system implements specific systems at different levels. The proposed system was verified through design and analysis of a strawberry infection prediction system, which was compared with other infection models.
KSP Keywords
Agricultural environment, Cloud-based technology, Communication reliability, Data transfer, Disease prediction, Environment information, Growth information, Integrated system, Internet of thing(IoT), IoT Devices, IoT-based
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
CC BY