Design of intelligent agricultural environmental big data collection system based on ZigBee and NB-IoT

Niu, Lu (2023) Design of intelligent agricultural environmental big data collection system based on ZigBee and NB-IoT. In: 2023 IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA), 24-26 February 2023, Changchun, China.

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Abstract / Description

In order to enhance the collection capability of agricultural environment monitoring big data, this paper established an intelligent agricultural environment big data mining system integrating ZigBee and NB-IoT technologies, and solved the problems of easily influenced by natural environment, thereby leading to low yield and high cost in traditional agricultural production. The system took STM32 as its core, adopted the coordinator ad hoc network with terminal nodes connecting multiple sensors, constructed three interconnected but independently operated working hierarchies of environmental data collection, transmission and processing to collect greenhouse environmental indexes. Besides, it took NB-IoT as bottom device to communicate with cloud platform, and used platform extension function to achieve the individualized design of web and cellphone apps, all which realized the real time monitoring and remote control of environmental parameters. The test results indicate that the environmental information sensors arranged in the overall structure built to collect and monitor temperature, humidity, illumination, gas and other factors that can affect agricultural production efficiency can accurately collect relevant information. This verifies that the agricultural environmental big data system constructed is capable of providing automatic monitoring technology and rich sensing information for production decision making.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	©2023 IEEE
Uncontrolled Keywords:	ZigBee; NB-IoT; big data; intelligent agriculture; environmental monitoring; system design
Subjects:	000 Computer science, information & general works
Department:	School of Computing and Digital Media
SWORD Depositor:	Pub Router
Depositing User:	Pub Router
Date Deposited:	28 Apr 2023 09:09
Last Modified:	28 Apr 2023 09:29
URI:	https://repository.londonmet.ac.uk/id/eprint/8475

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