Research on Intelligent Diagnosis of Rice Diseases and Pests Based on IoT and Keras Model
LiYan  MaGenjuan  GuYuwei  ZhangYuqing  YangZiqing  CaoJiahao  YinJiawen  TianRongxi

Nanjing Communication Institute, Nanjing, Jiangsu，211100；

Abstract：As a core crop safeguarding global food security, rice production has long been threatened by diseases and pests. The traditional manual diagnosis model, limited by low efficiency and strong subjectivity, can hardly meet the needs of large-scale agricultural production. With the iteration of Internet of Things (IoT) sensing technology and deep learning algorithms, building an integrated intelligent system of "perception-analysis-diagnosis" has become a key path to break through the bottleneck. Focusing on technological collaborative innovation, this paper proposes an intelligent diagnosis scheme for rice diseases and pests based on IoT and Keras Model: IoT technology is used to realize real-time perception and data transmission of field crop status, and a lightweight deep learning model is constructed based on the Keras framework to complete the feature recognition and classification of diseases and pests, forming a full-process intelligent system from field data collection to diagnosis result output. The research focuses on the design of system collaborative architecture, the adaptation and optimization of perception modules, the logic of model feature extraction, and the construction of closed-loop diagnosis process. It provides a technical paradigm for crop disease and pest control in smart agricultural scenarios and promotes the transformation of agricultural production from "experience-driven" to "technology-driven".

Keywords：Internet of Things (IoT); Keras Model; Rice Diseases and Pests; Intelligent Diagnosis; Technology Synergy; Deep Learning

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