Design of IoT monitoring platform for intelligent agricultural weather station

Biao Yu; Wen-hua Cao; Yuan-hui Wang

doi:10.1117/12.2673516

22 May 2023 Design of IoT monitoring platform for intelligent agricultural weather station

Biao Yu, Wen-hua Cao, Yuan-hui Wang

Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 126400D (2023) https://doi.org/10.1117/12.2673516
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China

Abstract

Aiming at the lack of intelligent comprehensive monitoring and data analysis of environmental meteorology in agricultural production activities, a monitoring platform integrating IoT technology is designed for smart agricultural meteorological station. A three-layer system of sensor terminal, IoT convergence gateway and cloud monitoring platform is constructed to realize real-time uploading and recording of agricultural meteorological data through Internet wireless communication module. A cloud platform and visual monitoring background which can support the concurrent access of more than 1000 distributed meteorological monitoring stations are designed and developed. The local maintenance of the weather monitoring station is realized by the mobile APP, which can set and modify the parameters of the station. Through practical application tests, the environmental meteorological parameters can be monitored in real-time, comprehensively and accurately, and the meteorological data can be recorded flexibly by the platform. The platform is convenient to operate and maintain, and its functions are easy to expand. It can provide important data support for the development of agricultural activities and play an important role in promoting the mature development of smart agriculture.

Citation Download Citation

Biao Yu, Wen-hua Cao, and Yuan-hui Wang "Design of IoT monitoring platform for intelligent agricultural weather station", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 126400D (22 May 2023); https://doi.org/10.1117/12.2673516

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