Version 1
: Received: 5 December 2023 / Approved: 6 December 2023 / Online: 6 December 2023 (10:43:27 CET)
Version 2
: Received: 12 December 2023 / Approved: 12 December 2023 / Online: 12 December 2023 (08:18:52 CET)
How to cite:
Oh, Y. Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System. Preprints2023, 2023120410. https://doi.org/10.20944/preprints202312.0410.v2
Oh, Y. Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System. Preprints 2023, 2023120410. https://doi.org/10.20944/preprints202312.0410.v2
Oh, Y. Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System. Preprints2023, 2023120410. https://doi.org/10.20944/preprints202312.0410.v2
APA Style
Oh, Y. (2023). Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System. Preprints. https://doi.org/10.20944/preprints202312.0410.v2
Chicago/Turabian Style
Oh, Y. 2023 "Development of Self-generated and LPWA-based Crop Growth Environment Monitoring and Bigdata Analysis System" Preprints. https://doi.org/10.20944/preprints202312.0410.v2
Abstract
Smart farm is a technology that greatly helps improve the productivity and quality of crops and is being actively introduced into indoor environments such as green houses. However, it has not yet been distributed to field-grown crops. The main reason is that, unlike indoor environments, it is very difficult to collect sensor data for monitoring the growth environment of crops in open fields where weather conditions change significantly and power supply is difficult. Additionally, because various sensors are used, the data formats of the devices are different, making it difficult to process. This paper presents a field crop growth environment monitoring and big data analysis system. The proposed system first solves power supply and data communication problems using solar power generation and LPWA technology. Additionally, based on the oneM2M architecture, data from various sensors is transmitted to the server using standardized technology. The transmitted data is stored and managed on the server as big data, and can be used to predict the production and quality of field-grown crops and take appropriate measures. The proposed system is expected to create an environment optimized for the growth of field crops and help prevent and manage diseases.
Keywords
Smart Farm, Field Crop Growth Environment Monitoring, Bigdata analysis, Low Power Wide Area(LPWA), One Machine to Machine(oneM2M),
Subject
Biology and Life Sciences, Agricultural Science and Agronomy
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
