Intelligent diagnosis system for rice diseases and pests based on keras model and IoT
Yan Li
Communication University of China, Nanjing
Genjuan Ma
Communication University of China, Nanjing
Yuwei Gu
Communication University of China, Nanjing
Yuqing Zhang
Communication University of China, Nanjing
Ziqing Yang
Communication University of China, Nanjing
Jiahao Cao
Communication University of China, Nanjing
Jiawen Yin
Communication University of China, Nanjing
DOI: https://doi.org/10.59429/esta.v13i1.13391
Keywords: keras model; internet of things; rice diseases and pests; intelligent diagnosis system
Abstract
As a major rice-producing country, China's rice yield and quality are critical to food security and livelihood protection. Rice diseases and pests have become a key constraint on rice production, reducing both yield and quality and seriously affecting farmers' income and food supply stability. To realize accurate prevention, real-time monitoring and scientific management of rice diseases and pests, and overcome the low efficiency, poor accuracy and complex operation of traditional monitoring methods, this paper designs an intelligent diagnosis system for rice diseases and pests based on the Keras model and Internet of Things (IoT). The system integrates lightweight edge computing devices, UAV inspection terminals and environmental sensors, taking the lightweight Keras deep learning model as the core to achieve rapid identification and accurate diagnosis. With IoT and edge intelligence, it realizes real-time collection, monitoring and analysis of field environmental parameters such as temperature, humidity and light intensity, supporting intelligent monitoring, data recording and dynamic management throughout the rice growth cycle. The system forms a complete digital and intelligent monitoring and diagnosis scheme with standardized processes, providing efficient and scientific management support for farmers and effectively improving the prevention and control efficiency of rice diseases and pests.
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