An expert system for melon growth management based on Internet of Things

Abstract

The invention provides an Internet of Things-based melon growth management expert system, including a main interface module, an expert knowledge base module, a monitoring information module, a growth simulation prediction module, a decision-making reasoning module, an expert consulting module, a personal information module and a background maintenance module ; The system manages the real-time growth environment monitoring, growth status monitoring, water and fertilizer amount and environmental temperature early warning of melons, the judgment of diseases and insect pests combined with image recognition technology, the realization of melon growth simulation and yield and quality prediction, equipped with planting knowledge base and expert online question answering function. The invention realizes real-time monitoring of environment and plant growth information, which is helpful for planting decision-making; real-time early warning of water, fertilizer and environmental temperature reminds users to improve management conditions; realizes high-precision simulation of plant growth indicators, fruit quality and yield; based on real-time environment and crop Comprehensive analysis of growth monitoring, data processing based on machine learning methods, and crop growth model prediction provides real-time accurate decision-making solutions for water and fertilizer.

Description

Technical field [0001] The present invention relates to the field of agriculture, in particular to melon management expert system based on the growth of things. Background technique [0002] Our country is a big country grow melons in the world, but the yield per unit area is a big gap with the developed countries, its potential yield and quality are far from optimal level, many factors affect the yield and quality of melon precise management and administration of water and fertilizer which It plays a central role. Agricultural growers lack of experience, resulting in water and fertilizer management and temperature melon lack of scientific quantitative decision-making, in the course of production activities and no advisory support professionals, leading to encounter various problems difficult to resolve planting, production fell in urgent need of simple visualization expert management system or platform provides a variety of assistance to planting them. [0003] Currently there i...

AI Technical Summary

Problems solved by technology

[0004] (1) The data knowledge owned by the system cannot be updated. Many expert management systems only use past climate information and differences in cultivated varieties to reason and make decisions. Even most systems are stand-alone versions that cannot accumulate and update data

[0005] (2) The system lacks the artificial intelligence AI part. At present, AI technology has developed to rely on the deep structure artificial neural network model and deep learning stage, and can be applied to all aspects of life, but it is rarely used in agriculture. For example, it can be used through Artificial intelligence realizes the intelligent identification and management of pests and diseases, artificial intelligence identifies the growth status of crops, and makes decisions on water, fertilizer management and temperature based on the current phenotype indicators of crops

[0006] (3) Agricultural Internet of Things technology is not used. At present, the Internet of Things is developing rapidly, but there are very few related agricultural applications. Data can be transmitted to the Internet of Things through sensors, real-time data information can be transmitted to the system, and real-time corrections and correlations can be made to system decisions. early warning

[0007] (4) The functions are scattered and there is no whole-process management. At present, there are only some scattered software such as temperature monitoring, pest decision-making and other functions, which cannot help users make decisions in the whole process. The user makes the right decision, solves the user's problem

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