Abstract

Collecting environmental information of crop growth and dynamically adjusting agricultural production has been proved an effective way to improve the total agricultural yield. Agricultural IoT technology, which integrates the information sensing equipment, communication network, and information processing systems, can support such an intelligent manner in the agricultural environment. Traditional agricultural IoT could meet the service demand of small-scale agricultural production scenarios to a certain extent. However, the emerging application scenario of the agricultural environment is becoming more and more complicated, and the data nodes of the underlying access to IoT backend system are increasing in large number, while the upper-layer applications are requiring high quality of data service. Hence, the traditional architecture-based (i.e., centralised cloud computing) IoT systems suffer from the problems such as small network coverage, data security issue, and limited power supply time while attempting to provide high-quality services at the edge of the network. Emerging edge computing offers the opportunity to solve these issues. This paper builds an intelligent IoT system for agricultural environment monitoring by integrating edge computing and artificial intelligence. We conducted an experiment to validate the proposed system considering the reliability and usability. The experimental results prove the system’s reliability (e.g., data packet loss rate is less than 0.1%). The proposed system achieves the concurrency of 500TPS and the average response time of 300 ms, which meet the practical requirements in agricultural environment monitoring.

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